Tyche Insights - User contributions [en]

Main Page

2026-03-30T17:54:18Z

KarlTyche:

3/20/2026 - Hi, this is Karl from Tyche Insights. The Tyche Insights wiki is now read-only and we have de-activated new account creation. Thank you so much to all contributors and readers. Tyche Insights is now focused on local government financial data and analytical products. We will keep our wiki live as a reference site. It is highly likely that we will use the wiki in the future for publishing financial content on local governments.

<big>'''''Unbiased data storytelling and data journalism using public, government data - by citizens, for citizens.'''''</big>[[File:Data Story Collage.png|none|thumb|950x950px]]
== About Tyche Insights ==

* What is a [[TycheAbout:WhatIsADataStory|Data Story]]?
* What are the [[TycheAbout:DataStoryComponents|components of a Data Story]]?
* What is [[TycheAbout:WhatIs|Tyche Insights]]?
* What is the [[TycheAbout:Purpose|purpose]] of Tyche Insights?
* [[TycheAbout:WhoContributes|Who contributes]] to Tyche Insights and why?
* What is the [[TycheAbout:CopyrightLicensing|licensing and copyright]] of Tyche Insights content?
* Who [[TycheAbout:ReadersAndUsers|reads and uses]] Tyche Insights content?
* What is the Tyche Insights [[TycheAbout:OriginStory|origin story]]?

== Search for data stories & data journalism ==
As we launch Tyche Insights℠ we begin with a set of content that we have populated for [[:Category:Albany NY|Albany, New York]]. These are stories that analyze the [[:Category:Albany NY|City of Albany]]'s housing, crime, population, taxes, state funding and more. To understand the types of stories that you will see over time (and potentially to give you some ideas on data stories that you can write!), search using terms such as "Albany", "Crime", "Finance" and more.

We also have the concept of a "[[Hub:Albany Data Stories|Hub]]" where a group is focused on a broader storytelling effort.

== Featured data story ==
[[File:Excel Example CrashDataAndChart.png|thumb|300x300px|Analyze NY-wide pedestrian crash data ]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - are available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

See our list of prior [[FeaturedDataStories|Featured Stories]].

== Opinions and News ==

* [[TycheOpEd:OpenDataFlywheel|The Open Data Flywheel]] - December 18, 2025
* [[TycheOpEd:FiveThingsWeLearned|What we learned from our Albany, NY test]] - January 11, 2026

== Join us, follow us, talk to us ==
Join the Tyche Insights community by clicking '''"Create account"''' at the top of this page. When you create an account you can write a data story, ask for assistance as you write your data story, comment and ask questions on existing data stories, participate in our Talk pages, receive email updates from Tyche Insights and more. Feel free to create an account even if you only want to read public data-driven stories & journalism which will help us understand the reach of our community's storytelling.

Want to talk to someone at Tyche Insights? If you're interested in writing your first story, discussing a challenge that you've had in obtaining the right data, talking about the company and its mission, or for any other reason - [https://calendly.com/karl-tycheinsights/learn-about-the-tyche-community Click this link] to schedule a 15 minute Zoom with the Tyche Insights team.

Other ways to follow and contact us? [https://www.linkedin.com/company/tycheinsights follow us on LinkedIn] to receive updates and see our emails at the bottom of the page.

== Data storytelling & data journalism as a Collaboration ==
We want to support anyone or any group of people who wants to use public data for data storytelling and journalism. If you are a solo data storyteller or a group of concerned citizens in a community, you are welcome here.

We also believe that data storytelling as a collaboration is powerful - many people from different cities and towns, analyzing similar data from their local governments, using the same tools, supporting each other.
[[File:HFDP Overview.png|thumb|400x400px]]
We're excited to support our first group data storytelling project - the [https://hudsonfinancedecoder.com/ Hudson Finance Decoder Project]. The purpose of this project is "Citizens working together to analyze the financial health of their cities, towns and counties across the USA and Canada." We will support anyone, anywhere who wants to create a Strong Towns Finance Decoder for their community, and then to turn that Finance Deocoder into a data story, [[Albany, New York Financial State|like we did for Albany, NY]].

And we are creating a queue of future data storytelling collaborations. Helping anyone, anywhere analyze your community's crime and budgets are at the top of the queue.

== Interested in Contributing? ==

What does data storytelling look like? What is the process? Walk through the process [[TycheHowTo:WhereToStart|here]].

As your read and contribut to Tyche Insights, please abide by our [[TycheAbout:CodeOfConduct|Code of Conduct]].
== Acquiring and understanding Public Data ==
What is public data? What types of public data exist that you might use? How do you acquire public data?

We provide a number of answers to these questions [[TycheHowTo:AcquireUnderstandPublicData|here]].

== Asking questions and Talk Pages ==
Want to ask questions, share ideas, discuss policy and approaches? We have set up Talk pages for all of these. Each of these are a subject-specific discussion forum. See our [[TycheTalk:UsingTalk|Talk Pages overview]].
== Data news story conventions ==
We are developing a set of conventions that guide the data storytelling process and articles. We have created [[TycheConventions:Overview|a set of initial documents]] and will be expanding this based on the community's feedback and guidance.
== Data news story how-to ==
You may already know how to analyze data using many different tools and methods, or you may need some hints or even complete recipes for how you perform certain analysis. We are creating various how-to documents and will be expanding this list. [[TycheHowTo:Overview|Access our document]] with links to various how-to documents.

== Any Other Questions? ==
You can reach out to us via email.

* General questions about joining? JoinUs@TycheInsights.com
* Co-founder Karl Urich ([[User:KarlTyche|KarlTyche]]) - karl@tycheinsights.com
* Co-founder Keith Gargiulo ([[User:KeithTyche|KeithTyche)]] - keith@tycheinsights.com

TycheAbout:OriginStory

2026-01-28T13:33:14Z

KarlTyche: added service mark

== What is the Tyche Insights origin story? ==
[[User:KarlTyche|Karl]] and [[User:KeithTyche|Keith]] came with the idea for Tyche Insights℠ without ever looking to start a business. We have been big fans of [https://usafacts.org/ USAFacts] since its inception and that’s what catalyzed the idea behind Tyche. What we like about USAFacts is that their stories validate, challenge and inform anyone's understanding about our government and how it does (and doesn't!) work.

As a test we analyzed public data from the City of Albany, NY government, exploring housing, property, crime, etc. We had a realization that we could turn this analysis into USAFacts-like stories and inform local community members. From there the discussion became “how do do we support citizen-led local data storytelling anywhere?” and the idea for Tyche Insights was born.

Tyche Insights is a [[wikipedia:Benefit_corporation|Public Benefit Corporation]] that balances profit and public good motivations. Tyche Insights will create, grow and support a community that does local data storytelling & data journalism. "Support" means that Tyche Insights will assist anyone throughout the whole data storytelling lifecycle - conceiving ideas, acquiring public data from local governments (cities, counties), analyzing data, creating visualizations (graphs, charts, dynamic visualizations), writing stories, editing, publishing. This support is available for free, to anyone.

From the beginning Tyche Insights has three foundational elements - 1) stories must be told in an unbiased fashion, 2) stories must be based on public, government data and 3) any data story is available to anyone, forever, for free via a [[TycheAbout:CopyrightLicensing|Creative Commons license]] - there is no subscription or any cost to read and use the data.

Return to [[Main Page]]

TycheAbout:ReadersAndUsers

2026-01-28T13:33:00Z

KarlTyche: added service mark

== Who reads and uses Tyche Insights content? ==
When we first envisioned Tyche Insights℠ we started with the concept of '''Readers'''. We want data stories to inform anyone who reads a single article to satisfy a question on their mind. We also want articles to support a person who is taking a journey equivalent to Wikipedia, where you start with one data story and you glide through a dozen articles about a community or a topic.

Data stories will also have '''Users''' - we think of a User as a person who takes action or utilizes the story in a particular manner. What are some types of Users?

A '''Citizen''' can use data stories to hold their elected officials accountable or to understand the connection between the actions and spending of their government and outcomes:
* “In the news I saw that developers are concerned about how long construction takes. I looked in the city’s budget at our planning department allocation and it looks very small. This is something I would like to bring up at the next city council meeting”
* “Our mayor said that she is keeping budget costs under control and I can validate that by looking at the budget numbers for the past 5 years”

A '''Journalist''' may use data stories to identify a journalistic topic that was not on their radar or inform an article with real data:
* “I have a treatment for an article about business growth in our city but didn’t know if objective data was available. This data story contains business data - counts and business types - harvested from state sources. I can weave this data into the story for context.”
* “This data story uncovered an area of the city’s operations that we haven’t been following. We’re going to use the data and inferences from this article to ask some questions”

'''Elected Officials''' can be Users too, they may use data stories to validate existing policy performance or identify other communities with similar issues that we can collaborate with on solutions:
* “We have made establishing budget controls a key component of our policy. The recent budget-related data story shows the trajectory of our budget and provides an independent validation that we’re doing the right things”
* “We have dramatic issues with homelessness and their healthcare. What other communities are highlighting this same challenge so that we can have some collaboration explorations with them?”

'''Academics and Researchers''' are users when they use data stories to identify subjects for research and acquire real world data that has been contextualized:
* “We are reviewing specific topics for social science research. We are looking through various data stories to find themes that are primary or adjacent to our area of study; this will help us come up with questions & hypothesis”
* “Capturing relevant data for our study is consuming our resources. We can reuse the data that is showing up in data stories which will decrease our costs and time”

Those are just a few of the ways that we want people to Use data stories, other examples include:
* City employees
* Nonprofits
* Major funders and foundations
* Businesses
* Data product creators
* Lobbyists
* Artifical intelligence creators
* Students

Next: What is the Tyche Insights [[TycheAbout:OriginStory|origin story]]?

TycheAbout:CopyrightLicensing

2026-01-28T13:32:44Z

KarlTyche:

== What is the licensing and copyright of Tyche Insights content? ==
We have a number of principles regarding Tyche Insights℠ content and its use:

* Access to the content is free, there is no gatekeeping or paywall
* All content should be available for anyone to use, share, remix, build upon and create derivative work
* When content is used downstream the content creators must be credited
* All content is copyrighted by the content creators (authors, editors, anyone creating a data visualization or aid) and Tyche Insights

== ShareAlike License ==
All Tyche Insights content will be governed by the [https://creativecommons.org/licenses/by/4.0/ Creative Commons Attribution 4.0 International License] (CC BY).

== Credits ==
The credits for the data story will include the Author, all editors, any other contributors (e.g. providing advice, data visualizations) and Tyche Insights. We will use the Creative Commons [https://wiki.creativecommons.org/wiki/Recommended_practices_for_attribution recommended practices for attribution].

Every article must have a Credits section. This section will 1) make sure that we are overtly crediting all contributors to an article, and 2) make it easy for a User of the content who is going to Share or Adapt the content to understand what attribution statement they should use.

Credits Parameters

* Every article credits Tyche Insights - and we can use “Tyche Insights, P.B.C.”
* Copyright - “© Copyright 2025”
* Individuals that contribute to an article get recognized by their handle and (parenthetically) their full name, e.g. “KarlTyche (Karl Urich)”
* We provide a suggested attribution statement

The Credits section should look like this:
[[File:Credits Example BY.png|none|thumb|700x700px]]Next: Who [[TycheAbout:ReadersAndUsers|reads and uses]] Tyche Insights content?

TycheAbout:WhoContributes

2026-01-28T13:32:33Z

KarlTyche: added service mark

== Who contributes to Tyche Insights and why? ==
In the movie [[wikipedia:Ratatouille_(film)|Ratatouille]] there is a line "Anyone can cook" which takes on surprising meaning in the movie; similarly we like to think that "Anyone can tell a data story" and contribute in some manner.

You may contribute to Tyche Insights℠ for many different reasons. You may want to...

* Learn more about your government and community and how they operate
* Contribute to larger efforts that provide a better understanding of your community
* Assist with making your government more transparent
* Test out your existing technical and communications skills in new ways
* Learn new technical and writing skills
* Create data stories that you can put on your resume, CV or your LinkedIn page
* Learn from other data storytellers in other communities

In addition, when you contribute to a data story you are enabling other people to build on your work:

* Someone in another city may use your story (and its source data, process, analysis, etc) to create a similar story for their community
* Someone in your city may use the public data that you have unlocked to create a new story that utilizes the same public data
* Someone in your city may build upon the research that you have done to dig deeper into the subject, or perform analysis to provide a contraritan or supporting view

The technical barrier for basic data storytelling is very low. If you have used Microsoft Excel or Google Sheets, you too can data storytell. Most data storytelling - importing data, studying it, sorting it, summarizing it, creating charts and graphs - can be done with these tools using + - * / operators, basic spreadsheet formulas and pivot tables.

There is also a place for sophisticated data science and big data manipulation - using Python NumPy & SciPy, Google Big Query and more. You may also be creating sophisticated data stories as a part of your job or research; Tyche is a commmunity that can support you making your research accessible to lay people, which increases the reach of your work.

Next: What is the [[TycheAbout:CopyrightLicensing|licensing and copyright]] of Tyche Insights content?

TycheAbout:Purpose

2026-01-28T13:32:17Z

KarlTyche: /* What is the purpose of Tyche Insights? */

== What is the purpose of Tyche Insights? ==
At Tyche Insights℠ we believe that public data - available to citizens and contextualized with stories, maps and charts - informs citizens, holds our government entities accountable, identifies challenges that our communities face, and provides insight into potential policy solutions.

Our inspiration for Tyche Insights is [https://usafacts.org/ USAFacts] and their mission - “No one at USAFacts is trying to convince you of anything. The only opinion we have is that government data should be easier to access. Our entire mission is to provide you with facts about the United States that are rooted in data. We believe once you have the solid, unbiased numbers behind the issues you can make up your own mind.”

At Tyche Insights we took the work that USAFacts is doing at the national and state level and are piloting an approach that empowers a community to tell data stories related to the nearly 100,000 government entities that exist in the USA and to support data storytelling anywhere in the world.

Tyche Insights will support this community in several ways. We will...

* create a technology stack that automates and simplifies the identification, access (via FOIA/FOIL or otherwise), receipt, management, analysis, initial contextualizing, long-term monitoring, and cross referencing of public data from government entities to support story writing.
* develop and maintain a portfolio of potential stories that, when complete, can be used to fully cross reference and assess cities, counties, and states across our standard story categories.

* recruit, educate, and support a community of citizen authors, analysts, and content creators to use data to tell stories both to complete a core set of data stories for each community, and to tell additional stories of sufficient import and timeliness to their communities.
* enlist partnerships with city, county, and state governments, nonprofits, educational institutions, journalists, and other suitable commercial or institutional entities to begin using stories in their own research and organizational efforts.

Next: Who [[TycheAbout:WhoContributes|contributes]] to Tyche Insights and why?

TycheAbout:WhatIs

2026-01-28T13:32:05Z

KarlTyche: added service mark

== What is Tyche Insights? ==
'''''How does my city earn and spend money?'''''

'''''Is the crime rate increasing or decreasing in my neighborhood?'''''

'''''Is there enough housing being built to support all demographics of residents?'''''

These are three of thousands of questions that can be asked and answered using public data from your city, county, or other government agency.

Tyche Insights℠ is an online community that supports unbiased local data storytelling using public data. Our community’s data stories can be used by anyone - for free - to understand, inform and take action.

Tyche community members may be data analysts or data scientists, or they are new to understanding data and how to use it. Community members have an interest in understanding and communicating insight about their city or local area.

At Tyche we will support community members from the start to the finish in their data storytelling. We help community members…

… identify a topic to explore, either through inspiration from existing data stories or brainstorming new ideas

… identify and acquire public data through open data or public information requests

… work with public data using data analysis or data science

… author their findings in an accessible story

… craft visualizations that make the story understandable

… publish and make their data stories findable

Any Tyche data story has readers and users. A Tyche reader is anyone who is using a data story to become more informed and aware. A Tyche user takes the data and data story as an input to what they do - a journalist writing an article, an academic conducting research, a nonprofit leader determining direction, a government official evaluating programs in other cities.

Free… free to write, free to get help, free to read, free to use.

Next: What is the [[TycheAbout:Purpose|purpose]] of Tyche Insights?

Main Page

2026-01-28T13:31:15Z

KarlTyche: /* Search for data stories & data journalism */ added service mark

<big>'''''Unbiased data storytelling and data journalism using public, government data - by citizens, for citizens.'''''</big>[[File:Data Story Collage.png|none|thumb|950x950px]]
== About Tyche Insights ==

* What is a [[TycheAbout:WhatIsADataStory|Data Story]]?
* What are the [[TycheAbout:DataStoryComponents|components of a Data Story]]?
* What is [[TycheAbout:WhatIs|Tyche Insights]]?
* What is the [[TycheAbout:Purpose|purpose]] of Tyche Insights?
* [[TycheAbout:WhoContributes|Who contributes]] to Tyche Insights and why?
* What is the [[TycheAbout:CopyrightLicensing|licensing and copyright]] of Tyche Insights content?
* Who [[TycheAbout:ReadersAndUsers|reads and uses]] Tyche Insights content?
* What is the Tyche Insights [[TycheAbout:OriginStory|origin story]]?

== Search for data stories & data journalism ==
As we launch Tyche Insights℠ we begin with a set of content that we have populated for [[:Category:Albany NY|Albany, New York]]. These are stories that analyze the [[:Category:Albany NY|City of Albany]]'s housing, crime, population, taxes, state funding and more. To understand the types of stories that you will see over time (and potentially to give you some ideas on data stories that you can write!), search using terms such as "Albany", "Crime", "Finance" and more.

We also have the concept of a "[[Hub:Albany Data Stories|Hub]]" where a group is focused on a broader storytelling effort.

== Featured data story ==
[[File:Excel Example CrashDataAndChart.png|thumb|300x300px|Analyze NY-wide pedestrian crash data ]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - are available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

See our list of prior [[FeaturedDataStories|Featured Stories]].

== Opinions and News ==

* [[TycheOpEd:OpenDataFlywheel|The Open Data Flywheel]] - December 18, 2025
* [[TycheOpEd:FiveThingsWeLearned|What we learned from our Albany, NY test]] - January 11, 2026

== Join us, follow us, talk to us ==
Join the Tyche Insights community by clicking '''"Create account"''' at the top of this page. When you create an account you can write a data story, ask for assistance as you write your data story, comment and ask questions on existing data stories, participate in our Talk pages, receive email updates from Tyche Insights and more. Feel free to create an account even if you only want to read public data-driven stories & journalism which will help us understand the reach of our community's storytelling.

Want to talk to someone at Tyche Insights? If you're interested in writing your first story, discussing a challenge that you've had in obtaining the right data, talking about the company and its mission, or for any other reason - [https://calendly.com/karl-tycheinsights/learn-about-the-tyche-community Click this link] to schedule a 15 minute Zoom with the Tyche Insights team.

Other ways to follow and contact us? [https://www.linkedin.com/company/tycheinsights follow us on LinkedIn] to receive updates and see our emails at the bottom of the page.

== Data storytelling & data journalism as a Collaboration ==
We want to support anyone or any group of people who wants to use public data for data storytelling and journalism. If you are a solo data storyteller or a group of concerned citizens in a community, you are welcome here.

We also believe that data storytelling as a collaboration is powerful - many people from different cities and towns, analyzing similar data from their local governments, using the same tools, supporting each other.
[[File:HFDP Overview.png|thumb|400x400px]]
We're excited to support our first group data storytelling project - the [https://hudsonfinancedecoder.com/ Hudson Finance Decoder Project]. The purpose of this project is "Citizens working together to analyze the financial health of their cities, towns and counties across the USA and Canada." We will support anyone, anywhere who wants to create a Strong Towns Finance Decoder for their community, and then to turn that Finance Deocoder into a data story, [[Albany, New York Financial State|like we did for Albany, NY]].

And we are creating a queue of future data storytelling collaborations. Helping anyone, anywhere analyze your community's crime and budgets are at the top of the queue.

== Interested in Contributing? ==

What does data storytelling look like? What is the process? Walk through the process [[TycheHowTo:WhereToStart|here]].

As your read and contribut to Tyche Insights, please abide by our [[TycheAbout:CodeOfConduct|Code of Conduct]].
== Acquiring and understanding Public Data ==
What is public data? What types of public data exist that you might use? How do you acquire public data?

We provide a number of answers to these questions [[TycheHowTo:AcquireUnderstandPublicData|here]].

== Asking questions and Talk Pages ==
Want to ask questions, share ideas, discuss policy and approaches? We have set up Talk pages for all of these. Each of these are a subject-specific discussion forum. See our [[TycheTalk:UsingTalk|Talk Pages overview]].
== Data news story conventions ==
We are developing a set of conventions that guide the data storytelling process and articles. We have created [[TycheConventions:Overview|a set of initial documents]] and will be expanding this based on the community's feedback and guidance.
== Data news story how-to ==
You may already know how to analyze data using many different tools and methods, or you may need some hints or even complete recipes for how you perform certain analysis. We are creating various how-to documents and will be expanding this list. [[TycheHowTo:Overview|Access our document]] with links to various how-to documents.

== Any Other Questions? ==
You can reach out to us via email.

* General questions about joining? JoinUs@TycheInsights.com
* Co-founder Karl Urich ([[User:KarlTyche|KarlTyche]]) - karl@tycheinsights.com
* Co-founder Keith Gargiulo ([[User:KeithTyche|KeithTyche)]] - keith@tycheinsights.com

New York Pedestrian Crash Data

2026-01-27T13:00:35Z

KarlTyche: /* Examples */

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts; we also have the data in a GIS format for download as well. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine. We hope that is a starting point for you extending the analysis, creating extracts of data specific to your area, putting the data into a data visualization tool, or ...

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may freely share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide proper attribution for the source of the data.

== Examples ==
We can show some examples of charts and pivot tables that you can make with the statewide data.
[[File:BuffaloNY DoW DayNight.png|none|thumb|700x700px|Analyze pedestrian crash deaths in Buffalo, NY by day of week, day vs. night]]
[[File:OrangeCounty QuarterlyTrend.png|none|thumb|700x700px|Analyze pedestrian crash trends by quarter for Orange County, NY, complete with trendline]]
[[File:Rochester CrashesByIntersection.png|none|thumb|400x400px|Understand pedestrian crashes by intersection - which intersections and the number of crashes - for Rochester, NY]]

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Sources]]

New York Pedestrian Crash Data

2026-01-27T12:59:55Z

KarlTyche: /* Overview */

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts; we also have the data in a GIS format for download as well. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine. We hope that is a starting point for you extending the analysis, creating extracts of data specific to your area, putting the data into a data visualization tool, or ...

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may freely share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide proper attribution for the source of the data.

== Examples ==
We can show some examples of charts and pivot tables that you can make with the statewide data.
[[File:BuffaloNY DoW DayNight.png|none|thumb|700x700px|Analyze pedestrian crash deaths in Buffalo, NY by day of week, day vs. night]]
[[File:OrangeCounty QuarterlyTrend.png|none|thumb|700x700px|Analyze pedestrian crash trends by quarter for Orange County, NY, complete with trendline]]
[[File:Rochester CrashesByIntersection.png|none|thumb|400x400px|Understand pedestrian crashes by intersection - which intersections and how many - for Rochester, NY]]

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Sources]]

New York Pedestrian Crash Data

2026-01-26T21:27:14Z

KarlTyche:

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine.

The data is also available as a geospatial file in .shp format.

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may freely share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide propert attribution for the source of the data.

== Examples ==
We can show some examples of charts and pivot tables that you can make with the statewide data.
[[File:BuffaloNY DoW DayNight.png|none|thumb|700x700px|Analyze pedestrian crash deaths in Buffalo, NY by day of week, day vs. night]]
[[File:OrangeCounty QuarterlyTrend.png|none|thumb|700x700px|Analyze pedestrian crash trends by quarter for Orange County, NY, complete with trendline]]
[[File:Rochester CrashesByIntersection.png|none|thumb|400x400px|Understand pedestrian crashes by intersection - which intersections and how many - for Rochester, NY]]

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Sources]]

File:Rochester CrashesByIntersection.png

2026-01-26T21:26:45Z

KarlTyche:

Understand pedestrian crashes by intersection - which intersections and how many - for Rochester, NY

File:OrangeCounty QuarterlyTrend.png

2026-01-26T21:25:52Z

KarlTyche:

Analyze pedestrian crash trends by quarter for Orange County, NY, complete with trendline

File:BuffaloNY DoW DayNight.png

2026-01-26T21:25:01Z

KarlTyche:

Analyze pedestrian crash deaths in Buffalo, NY by day of week, day vs. night

Albany, New York Pedestrian Crash

2026-01-26T20:36:43Z

KarlTyche: /* The Data and Preliminary Analysis */

== Analyzing Pedestrian Crashes in Albany ==
[[File:CoreAlbany.png|none|thumb|600x600px|Pedestrian Crash Locations in Albany, NY]]
''“The annual number of crashes in the city has trended downward over the past three years. In 2022, there were 3,838 traffic crashes, with 575 involving some level of injury. Last year city police responded to 3,649 crashes, which included everything from minor scrapes and fender benders to head-on collisions, with 562 crashes involving some level of injury.”''

* “Albany sees traffic crashes drop with new speed limit”, Times Union, [https://www.timesunion.com/news/article/albany-sees-traffic-crashes-drop-new-25-mph-speed-20250081.php April 6, 2025]

''“This year we added more than 70 speed humps, implemented a new 25 MPH citywide speed limit, and completed installation of speed cameras across 20 school zones to enforce the existing 20 MPH speed limit where our younger residents learn every day. These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”''

* City of Albany [https://www.albanyny.gov/DocumentCenter/View/13182/2026-Proposed-Budget-PDF Proposed budget], p 6

== Overview ==
Traffic safety, both actions to make our streets safer and using data to analyze trends, is receiving significant attention nationwide and in the City of Albany. [https://visionzeronetwork.org/resources/vision-zero-communities/ Vision Zero] is the nationwide road and pedestrian safety organization that communities are rallying around, which includes [https://www.capitalregionvisionzero.org/ Capital District Vision Zero].

Nationwide, car-on-pedestrian crashes are more likely to cause serious injuries or fatalities than car-on-car accidents; pedestrian deaths are [https://www.cdc.gov/mmwr/volumes/74/wr/mm7408a2.htm growing at a faster rate] than overall traffic-related deaths. Yet car-on-pedestrian crashes get bundled into overall traffic safety reporting, and the volume, severity and visibility of pedestrian crashes get diluted in the discussion.

What is missing for us is the data, specifically data on pedestrian crashes - not just "traffic accidents" - within the City of Albany. We want to understand Albany’s pedestrian crash data - where it happens, when it happens, and what the trends are. Our goal is pretty simple - we want to demonstrate that pedestrian crash data is available and it should visibly inform the City of Albany’s planning, goal setting, analysis and communication about the progress that we are making.

We are also aware that the science and analysis of pedestrian safety is evolving. Writing this article we looked for research on the benefit of specific pedestrian safety infrastructure and programs. We communicated with several people involved in pedestrian safety research. From our point of view the linkage between pedestrian safety and the introduction of pedestrian safety measures can best be described as directional and/or early stage. For us this validates the need for the City to be using data to inform the actions that we take and to connect those actions to observable, objective benefits; or identify where our safety measures do not appear to be providing benefit.

Before we move to the analysis, a quick prefacing word. Our analysis may come across as dispassionate - reducing pedestrian crashes, injuries and deaths to numbers. We are well aware that behind these numbers are people - people who die, people who are injured, and families that are impacted by pedestrian crashes.

== The Data and Preliminary Analysis ==
We FOILed statewide pedestrian crash data from New York State DOT and received a file of over 75,000 car-on-pedestrian crashes statewide between January 1, 2020 and October 27, 2025.
[[File:InputData.png|none|thumb|500x500px|Pedestrian crash source data from New York Department of Transportation]]
Each crash record (image above) contains the data, time of day, injury and fatality information, reporting agency, and then other information on the conditions, circumstances and road network.

We extracted the 644 pedestrian crashes reported by the Albany Police Department over the time period to create our analysis dataset. While other law enforcement agencies (State Police, Campus Police, etc) reported pedestrian crashes within the City limits the numbers were not material or were associated with Interstate highway pedestrian crashes.

We mapped out every crash (below) and computed a few data points that we would use in our analysis:

* The name of the road where the crash happened
* The major road or minor road designation of the road where the crash happened
* The neighborhood where the crash happened
* Whether the crash happened in a school camera speed zone

[[File:OverviewMap.png|none|thumb|700x700px|Overview map of City of Albany Pedestrian Crashes, Jan 2020 to Oct 2025]]Note - we are making this data available state-wide for anyone to use the data for analysis. See the page [[New York Pedestrian Crash Data|here]] for more information.

== How Severe are the Crashes? ==
The DOT data collected by local law enforcement agencies contains three pieces of data on the severity of the pedestrian crash - how many people died, how many people sustained serious injuries, how many people sustained other injuries.
[[File:PedestrianCrashOutcome.png|none|thumb|400x400px|City of Albany Pedestrian Crash Outcomes]]
Our understanding of a “Serious Injury” is one where a person suffers dismemberment, fracture, loss of a fetus, permanent loss of a body organ, and/or any injury that limits a person’s ability to live normally for at least 90 days during the 180 days immediately following the crash. Any crash can have 0, 1 or more people who fall in each of the three categories.

For the 644 pedestrian crashes in the City of Albany between Jan 2020 and October 2025, 2% result in a fatality, 17% result in one or more serious injuries, 69% result in one or more other injuries, and 15% result in no injuries.

Note - percentages do not add to 100% - any crash can have more than one outcome. There are three streets where multiple fatality-producing crashes occurred: Washington Ave, Central Ave and Everett Road.

== What is the Overall Trend in Pedestrian Crashes? ==
Is the rate of pedestrian crashes increasing, decreasing or static? Prior to answering this question we can explain the time period that we chose to study. We stopped the trend study at the end of Q2 2025 (June 30th). While we have pedestrian crash data from NY State through late October 2025 we found that there is a latency in entering pedestrian crash data into the system. Each crash record lists the crash data and the date of data entry; typically there is a week or more delay, however many crashes take 90+ days to be entered into the system. We concluded that the Q3 (July-September) data was likely missing crash data due to this delay.

We can review crashes by quarter in a chart from Q1 2020 through Q2 2025. We also overlaid a trendline that uses a statistical method (polynomial) to show the overall trend.
[[File:CrashesByQuarter.png|none|thumb|700x700px|City of Albany, NY Quarterly trend in pedestrian crashes]]
Are pedestrian crashes going down? That is a tough question to answer with any certainty. A few bullet points capture our observations:

* The data from the first half of 2025 suggests improvement in pedestrian safety
* The pandemic likely, but not certainly, had some effect on minimizing traffic incidents in 2020 and 2021
* We do not know how the crash reporting processes may have changed, which may have caused over- or understatements for certain quarters
* Some of the large spikes and troughs may be just statistical chance

GIven those considerations, we would suggest two takeaways:

# the 2025 trend suggests improvement however 3-5 quarters of additional data are required before anyone can make broad claims of pedestrian safety improvement
# the pedestrian crash data, regardless of trend, demonstrates that there is a big gap to get to Vision Zero.

== Where do pedestrian crashes happen? ==
A quick point about our analysis before we describe where accidents happen. To determine the level (minor or major) of any given road we use DOT Arterial Classification Codes (ACC) associated with each road. A road gets an ACC based on its importance, usage, traffic volume, etc. In the map below ACC=3 (yellow), ACC=4 (purple), ACC=5 (red).
[[File:ACC AlbanyStreets.png|none|thumb|500x500px|Albany's streets displaying Arterial Classification Codes]]
In our analysis below we consider major roads to include ACC 3 & 4, and minor roads to be ACC 5. We linked each pedestrian crash to a road and determined if each crash was associated with a major road or a minor road. For a handful of crashes (13) we could not reliably determine the associated road.

* 486 pedestrian crashes (77%) occurred on '''Major Roads'''
* 145 pedestrian crashes (23%) occurred on '''Minor Roads'''

We can then analyze where pedestrian crashes happen, by street and by neighborhood.

The streets (by name) with more than 10 pedestrian crashes between 2020 and 2025:
{| class="wikitable sortable"
|+City of Albany, Crashes by Street
!Street
!Incident Count
!Percentage of Total Pedestrian Crashes
|-
|Central Avenue
| align="right" |83
| align="right" |13.2%
|-
|Washington Avenue
| align="right" |49
| align="right" |7.8%
|-
|Madison Avenue
| align="right" |47
| align="right" |7.5%
|-
|New Scotland Avenue
| align="right" |42
| align="right" |6.6%
|-
|Lark Street
| align="right" |28
| align="right" |4.4%
|-
|Delaware Avenue
| align="right" |24
| align="right" |3.8%
|-
|South Pearl Street
| align="right" |22
| align="right" |3.5%
|-
|Western Avenue
| align="right" |20
| align="right" |3.2%
|-
|Henry Johnson Boulevard
| align="right" |19
| align="right" |3.0%
|-
|Livingston Avenue
| align="right" |18
| align="right" |2.9%
|-
|Clinton Avenue
| align="right" |18
| align="right" |2.8%
|-
|Quail Street
| align="right" |11
| align="right" |1.8%
|-
|Morton Avenue
| align="right" |10
| align="right" |1.6%
|-
|Broadway
| align="right" |10
| align="right" |1.6%
|-
|North Allen Street
| align="right" |10
| align="right" |1.6%
|}
The neighborhoods with the most pedestrian crashes (more than 5% of overall pedestrian crashes) include these 6 neighborhoods:
{| class="wikitable sortable"
|+City of Albany, Crashes by Neighborhood
!Neighborhood
!Number of Pedestrian Crashes
!Percentage of Total Pedestrian Crashes
|-
|West Hill
| align="right" |84
| align="right" |13.3%
|-
|Pine Hills
| align="right" |70
| align="right" |11.1%
|-
|Central Avenue
| align="right" |53
| align="right" |8.4%
|-
|Arbor Hill
| align="right" |42
| align="right" |6.7%
|-
|Upper Washington Avenue
| align="right" |34
| align="right" |5.4%
|-
|Delaware Avenue
| align="right" |34
| align="right" |5.4%
|}
We reviewed the number of accidents that are within 200 yards of a school zone speed camera. (Map above). Between 2020 and October 2025 there were:

* 5 serious injuries in a school zone between the hours of 7am and 6pm, not including July and August. 2 serious injuries occurred in 2020 and 3 serious injuries occurred in 2023.
* 19 other injuries in a school zone between the hours of 7am and 6pm, not including July and August

[[File:SchoolZones.png|none|thumb|400x400px|Map of neighborhood school zones]]
We can use this historical data to understand the current and future pedestrian safety benefit of the school zone speed camera program.

Lastly, the pedestrian crash data identifies, for each crash, whether the accident occurred at an intersection or not at an intersection. The map below - the south end of Lark St near Madison Ave - shows pedestrian crashes at intersections using green circles, and pedestrian crashes that happened in-between intersections are identified with black squares.
[[File:Albany Intersection NonInts.png|none|thumb|400x400px|Map of pedestrian crashes at intersections and non-intersection crashes]]
Roughly 60% of pedestrian crashes occur at intersections, 40% in-between intersections. We doubt the value of ranking the “top 10 most dangerous intersections in Albany”, however we can note that intersections with the highest number of pedestrian crashes during the study period include Lark St & Washington Ave, New Scotland & Madison Ave, and Central Ave & Henry Johnson Blvd.

== When do Pedestrian Crashes Happen? ==
What insight could we find from understanding when - day vs. night, day of week - pedestrian crashes happen? The pedestrian crash data codes “Light conditions” in 5 categories - DAYLIGHT, DAWN, DUSK, DARK-ROAD LIGHTED, and DARK-ROAD UNLIGHTED. We created two categories for Day vs. Night, where Day consists of DAYLIGHT and DAWN, and Night consists of the other three categories. 63% of the City’s pedestrian crashes happen during the day, 37% at night.

We then plotted pedestrian crashes by day of week and day vs. night. We had some thoughts about when pedestrian crashes are most prevalent and none proved to be correct. We were extremely surprised by the day-to-day variability in overall pedestrian accidents, and the day-to-day consistency in night pedestrian crashes.
[[File:PedestrianCrashes DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Crashes by Day of Week, Night vs. Day]]
Similarly, we can examine when pedestrian deaths happen. Deaths generally track the day of week rate, with a much higher percentage of deaths happening at Night (72%).
[[File:PedestrianDeaths DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Deaths by Day of Week, Night vs Day]]
As we analyze when pedestrian deaths happen we can look at broader analysis. The National Safety Council’s [https://injuryfacts.nsc.org/motor-vehicle/road-users/pedestrians/ analysis of pedestrian crashes], states:

''“The largest number of pedestrian deaths occurs on Fridays (1,155), closely followed by Saturdays (1,150). Except for a decline on Sundays, the number of pedestrian deaths during daylight hours is relatively consistent throughout the week. However, pedestrian fatalities at night (during dark with or without artificial lighting) vary substantially. Nighttime pedestrian deaths are at their lowest point on Tuesday and peak on Saturday and Sunday.”''

These statements do and don’t align with the City of Albany’s pedestrian deaths, however this could be due to the low volume of pedestrian deaths on the City’s roads.

== How does Albany compare against Capital District cities? ==
We ran the same trend analysis for Troy and Schenectady - a quarterly analysis of pedestrian crashes for each city between 2020 and Q2 2025. While Troy and Schenectady have fewer pedestrian crashes we wanted to identify how each city’s trend compares. In the graph below the quarter-to-quarter pedestrian crash data and trends are in solid lines. The statistical trend for each city is shown with a dashed line.
[[File:PedestrianCrashes 3Cities.png|none|thumb|700x700px|Pedestrian crash comparison for Albany, Troy and Schenectady]]
Troy has seen a slight downturn in pedestrian crashes while Schenectady has shown a slight uptick. Both communities are a part of Capital Region Vision Zero, similar to the City of Albany. We have not examined if either Schenectady or Troy has been making the same investment in traffic calming measures as the City of Albany.

Our takeaway from the inter-city comparison is that this is an interesting data point for us to track. Within these three peers cities we can examine broad trends in pedestrian safety and the linkage between safety investment and awareness and reduction in pedestrian crashes.

== Summary ==
We picked a few of the many ways to examine the City of Albany’s pedestrian crashes since 2025. We wrote this article to highlight some of the data points that we are seeing from examining the pedestrian crash data.

We also want to ask our readers - what questions do you have that we can attempt to answer? If you have a question concerning pedestrian safety and crashes that you think we may be able to answer, drop us an email at [[MailTo:AlbanyDataStories@gmail.com|AlbanyDataStories@gmail.com]].

The City makes significant investments year-over-year in our streets and related safety. The City’s budget items that directly or indirectly support transportation safety in the 2026 proposed budget include:

* $1 million for traffic speed reduction measures
* $15 million for traffic signal improvements
* $14.5 million for street reconstruction
* $0.65 million for streetlight improvements
* $0.65 million for sidewalk reconstruction
* $0.4 million for roadway striping
* $0.3 million for traffic safety equipment

Net, the City invests over $30 million in road maintenance and improvements. Optimizing or directing this spending for traffic safety should be an important consideration. For example, the data could guide whether we should or shouldn't be installing speed humps on minor streets with no history of pedestrian crashes.

We can suggest a few outcomes from our analysis:

# New York must make pedestrian safety data and all other traffic crash data available to the public proactively, not requiring a FOIL
# The City of Albany should make all pedestrian and traffic safety analysis available on the City’s [https://data.albanyny.gov/ open data website]. Quoting statistics and studies must be accompanied by visibility of the analysis. For example, let’s see the data and analysis behind our opening quote from the 2026 budget “These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”
# Data should be used to analyze our new and improved infrastructure. If we have installed speed humps, pedestrian walkway improvements of various types, speed zone cameras and more, can we identify which improvements are or are not making a difference?
# Data should inform our goals. Our City should set targets or goals for the total number of pedestrian crashes, or related fatalities and serious injuries. As an illustrative example, in 2027 can we strive to have fewer than 70 pedestrian crashes and no fatalities?
# If we have data on our improvements to date (#3) and our goals (#4), can we use those data points to prioritize how and where we make improvements and additions to our infrastructure? Data should inform our $30 million of 2026 infrastructure spending.
# Let’s use the word “crash” rather than “accident” when we are talking about public safety. “Crash” conveys the tragic consequences of what are, in most cases, avoidable scenarios.

For further reading regarding the City’s pedestrian safety programs we suggest looking at:

* City of Albany [https://www.capitalmpo.org/wp-content/CRTC/images/linkage_program/AlbCoFinal/albanyCSPolicyandDesignManual_Final.pdf Complete Streets Design Guidelines]
* City of Albany [https://99a4b737-7711-4d6a-854e-2e74e07f3d6a.filesusr.com/ugd/b59736_f67b877056c54b5e9ce9754ae4fe4650.pdf Bicycle and Pedestrian Master Plan]

We have also posted the datasets that we received via FOIL in this Google Drive for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Data ==
For this article we FOILed pedestrian crash data from NY State Department of Transportation.

We have also posted the datasets that we received via FOIL in this [https://drive.google.com/drive/folders/1RUt4k5V_JT1OvGBzq6g1nFTrqwiANk4o Google Drive] for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Process ==
We added numerous fields to the data using QGIS. The details of these additional fields include:
{| class="wikitable"
!Field Name
!Field details
|-
|X
|Longitude value, WGS 84 - derived from UTMEasting
|-
|Y
|Latitude value, WGS 84 - derived from UTMNorthing
|-
|ACC_Intersection
|Arterial Class Code of the primary or most important road at the intersection, where the pedestrian crash is an intersection crash
<nowiki> </nowiki> Note that Arterial Class Code data - here and in other fields - comes from the NY State Street Network - <nowiki>https://gis.ny.gov/streets-addresses</nowiki>
|-
|ACC_Middle
|Arterial Class Code of the street associated with a non-intersection crash. Note that ACC values of 1-4 are considered "Major Roads" and ACC = 5-6 are considered "Minor Roads"
|-
|CrashStreetName
|The main street name associated with the crash regardless of intersection vs non-intersection crashes. This field is populated with StrtMid for non-intersection crashes. This field is populated with IntPriStNm for intersection crashes
|-
|StrtIntersection
|The street names of the roads that are associated with the intersection of the pedestrian crash. Note that the street names are in alphabetical order for standardization purposes.
|-
|StrtMiddle
|The name of the street associated with a non-intersection pedestrian crash
|-
|Neighborhood
|Where found, the neighborhood where the pedestrian crash happened. Neighborhood data derived from the Zillow neighborhoods file. <nowiki>https://www.arcgis.com/home/item.html?id=56b89613f9f7450fb44e857691a244e7</nowiki>
|-
|County
|The county where the pedestrian crash happened. County boundaries are from US Census Bureau TIGER data, 2025.
|-
|MajorMinor
|A determination if a pedestrian crash happened at a major or minor road or intersection. This MajMin value conflates information from ACC_MID and IntMajMin. If ACC_MID <=4 then it is major; the value of IntMajMin is moved over to this field for intersection pedestrian crashes
|-
|City
|The incorporated city or place where the pedestrian crash happened. Place boundaries are from US Census Bureau TIGER data, 2025.
|-
|Town
|The subdivision where the pedestrian crash happened. Subdivision boundaries are from US Census Bureau TIGER data, 2025.
|-
|IntersectionMajorMinor
|A determination if a pedestrian crash happened at a major or minor intersection. An intersection is deemed "Major" if one or both streets have an ACC value <= 4
|-
|IntersectionPrimaryStreet
|The primary street name at the intersection. Note that this is determined first by the street with the lower (more important) Arterial Class Code value; if streets share the same ACC then the street that is chose is the first alphabetically.
|}

== Credits ==
This data story and its content is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'Albany NY Pedestrian Crash', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:Albany_NY]]
[[Category:Pedestrian_Crash]]

FeaturedDataStories

2026-01-26T20:34:48Z

KarlTyche: /* Our first Finance Decoders from the Hudson Finance Decoder Project */

[[File:Excel Example CrashDataAndChart.png|thumb|300x300px]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - are available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

=== Our first Finance Decoders from the Hudson Finance Decoder Project ===
[[File:HFDP Overview.png|thumb|300x300px|The Hudson Finance Decoder Project]]
We started the Hudson Finance Decoder Project to help anyone, anywhere create a Finance Decoder. We [[TycheNews:FirstFinanceDecoders|posted an article]] describing the first Finance Decoders that have been created and posted. We now have stories that examine local government finances for cities such as Gainesville, FL and Pueblo, CO, and counties like Washoe County, NV.

These stories extend the basic Finance Decoder template to provide additional analysis (e.g. on local government debt), comparisons against neighboring cities, and more.

=== Wichita, Kansas LandValuePerAcre ===
One way to examine the utilization and value of the land use in your community is to create a Total Value Per Acre (TVPA) analysis for your town. The idea is that various areas of your city, town or county contribute to the property tax roll at different rates. See this [[Wichita, Kansas LandValuePerAcre|new article on TVPA analysis]] for Wichita, Kansas.
[[File:NorthAndSouthOf54.png|thumb|200x200px]]

Sometimes this contribution is obvious; an undeveloped one-acre parcel of land contributes less tax than a one-acre parcel of developed land. Sometimes the contributions are counterintuitive. A 2-acre property with a two million dollar home might contribute less to the property tax roll than if there were 10 0.2 acre houses on the same property.

We like this story for a number of reasons. First, it builds on Strong Towns and their championing of TVPA analysis. Secondly, we [[TycheHowTo:CreateValuePerAcreMap|laid out a process]] that explains how anyone can perform similar analysis for their community.

Lastly, TVPA analysis doesn't necessarily get you to an outcome of "this area is good, this area is bad", rather it shows you how land has been built up and used, and what the impact is from an improved value perspective. We want this analysis to inform future decisions that support the next generation of housing development.

=== Analyzing Albany NY's Crime ===
[[File:CrimeMap 15.png|thumb|200x200px]]
Our community member, Adam, [[Albany, New York Crime Maps|analyzed Albany, NY's crime]] and where it happens as a two-part exploration into the types, trends and locations of crime.

We like this data story for a number of reasons. Crime mapping highlights both where crime happens and, just as importantly, where crime is low - the mapping teased out some areas of high and low crime that weren't intuitive. Adam also built the crime mapping analysis never having done any geospatial work prior. We wrote a short how-to on [[TycheHowTo:CreateHeatMap|creating heat maps]] that supported this analysis.

Lastly, a Criminology professor from our local university read the article and brought us into their classroom to talk to students about our work. While this was an unexpected outcome, it's just what we want to have happen - a data story informs and is used by others.

FeaturedDataStories

2026-01-26T20:33:02Z

KarlTyche:

[[File:Excel Example CrashDataAndChart.png|thumb|300x300px]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - are available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

=== Our first Finance Decoders from the Hudson Finance Decoder Project ===
We started the Hudson Finance Decoder Project to help anyone, anywhere create a Finance Decoder. We [[TycheNews:FirstFinanceDecoders|posted an article]] describing the first Finance Decoders that have been created and posted. We now have stories that examine local government finances for cities such as Gainesville, FL and Pueblo, CO, and counties like Washoe County, NV.

These stories extend the basic Finance Decoder template to provide additional analysis (e.g. on local government debt), comparisons against neighboring cities, and more.

=== Wichita, Kansas LandValuePerAcre ===
One way to examine the utilization and value of the land use in your community is to create a Total Value Per Acre (TVPA) analysis for your town. The idea is that various areas of your city, town or county contribute to the property tax roll at different rates. See this [[Wichita, Kansas LandValuePerAcre|new article on TVPA analysis]] for Wichita, Kansas.
[[File:NorthAndSouthOf54.png|thumb|200x200px]]

Sometimes this contribution is obvious; an undeveloped one-acre parcel of land contributes less tax than a one-acre parcel of developed land. Sometimes the contributions are counterintuitive. A 2-acre property with a two million dollar home might contribute less to the property tax roll than if there were 10 0.2 acre houses on the same property.

We like this story for a number of reasons. First, it builds on Strong Towns and their championing of TVPA analysis. Secondly, we [[TycheHowTo:CreateValuePerAcreMap|laid out a process]] that explains how anyone can perform similar analysis for their community.

Lastly, TVPA analysis doesn't necessarily get you to an outcome of "this area is good, this area is bad", rather it shows you how land has been built up and used, and what the impact is from an improved value perspective. We want this analysis to inform future decisions that support the next generation of housing development.

=== Analyzing Albany NY's Crime ===
[[File:CrimeMap 15.png|thumb|200x200px]]
Our community member, Adam, [[Albany, New York Crime Maps|analyzed Albany, NY's crime]] and where it happens as a two-part exploration into the types, trends and locations of crime.

We like this data story for a number of reasons. Crime mapping highlights both where crime happens and, just as importantly, where crime is low - the mapping teased out some areas of high and low crime that weren't intuitive. Adam also built the crime mapping analysis never having done any geospatial work prior. We wrote a short how-to on [[TycheHowTo:CreateHeatMap|creating heat maps]] that supported this analysis.

Lastly, a Criminology professor from our local university read the article and brought us into their classroom to talk to students about our work. While this was an unexpected outcome, it's just what we want to have happen - a data story informs and is used by others.

Main Page

2026-01-26T20:32:17Z

KarlTyche: /* Featured data story */

<big>'''''Unbiased data storytelling and data journalism using public, government data - by citizens, for citizens.'''''</big>[[File:Data Story Collage.png|none|thumb|950x950px]]
== About Tyche Insights ==

* What is a [[TycheAbout:WhatIsADataStory|Data Story]]?
* What are the [[TycheAbout:DataStoryComponents|components of a Data Story]]?
* What is [[TycheAbout:WhatIs|Tyche Insights]]?
* What is the [[TycheAbout:Purpose|purpose]] of Tyche Insights?
* [[TycheAbout:WhoContributes|Who contributes]] to Tyche Insights and why?
* What is the [[TycheAbout:CopyrightLicensing|licensing and copyright]] of Tyche Insights content?
* Who [[TycheAbout:ReadersAndUsers|reads and uses]] Tyche Insights content?
* What is the Tyche Insights [[TycheAbout:OriginStory|origin story]]?

== Search for data stories & data journalism ==
As we launch Tyche Insights we begin with a set of content that we have populated for [[:Category:Albany NY|Albany, New York]]. These are stories that analyze the [[:Category:Albany NY|City of Albany]]'s housing, crime, population, taxes, state funding and more. To understand the types of stories that you will see over time (and potentially to give you some ideas on data stories that you can write!), search using terms such as "Albany", "Crime", "Finance" and more.

We also have the concept of a "[[Hub:Albany Data Stories|Hub]]" where a group is focused on a broader storytelling effort.

== Featured data story ==
[[File:Excel Example CrashDataAndChart.png|thumb|300x300px|Analyze NY-wide pedestrian crash data ]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - are available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

See our list of prior [[FeaturedDataStories|Featured Stories]].

== Opinions and News ==

* [[TycheOpEd:OpenDataFlywheel|The Open Data Flywheel]] - December 18, 2025
* [[TycheOpEd:FiveThingsWeLearned|What we learned from our Albany, NY test]] - January 11, 2026

== Join us, follow us, talk to us ==
Join the Tyche Insights community by clicking '''"Create account"''' at the top of this page. When you create an account you can write a data story, ask for assistance as you write your data story, comment and ask questions on existing data stories, participate in our Talk pages, receive email updates from Tyche Insights and more. Feel free to create an account even if you only want to read public data-driven stories & journalism which will help us understand the reach of our community's storytelling.

Want to talk to someone at Tyche Insights? If you're interested in writing your first story, discussing a challenge that you've had in obtaining the right data, talking about the company and its mission, or for any other reason - [https://calendly.com/karl-tycheinsights/learn-about-the-tyche-community Click this link] to schedule a 15 minute Zoom with the Tyche Insights team.

Other ways to follow and contact us? [https://www.linkedin.com/company/tycheinsights follow us on LinkedIn] to receive updates and see our emails at the bottom of the page.

== Data storytelling & data journalism as a Collaboration ==
We want to support anyone or any group of people who wants to use public data for data storytelling and journalism. If you are a solo data storyteller or a group of concerned citizens in a community, you are welcome here.

We also believe that data storytelling as a collaboration is powerful - many people from different cities and towns, analyzing similar data from their local governments, using the same tools, supporting each other.
[[File:HFDP Overview.png|thumb|400x400px]]
We're excited to support our first group data storytelling project - the [https://hudsonfinancedecoder.com/ Hudson Finance Decoder Project]. The purpose of this project is "Citizens working together to analyze the financial health of their cities, towns and counties across the USA and Canada." We will support anyone, anywhere who wants to create a Strong Towns Finance Decoder for their community, and then to turn that Finance Deocoder into a data story, [[Albany, New York Financial State|like we did for Albany, NY]].

And we are creating a queue of future data storytelling collaborations. Helping anyone, anywhere analyze your community's crime and budgets are at the top of the queue.

== Interested in Contributing? ==

What does data storytelling look like? What is the process? Walk through the process [[TycheHowTo:WhereToStart|here]].

As your read and contribut to Tyche Insights, please abide by our [[TycheAbout:CodeOfConduct|Code of Conduct]].
== Acquiring and understanding Public Data ==
What is public data? What types of public data exist that you might use? How do you acquire public data?

We provide a number of answers to these questions [[TycheHowTo:AcquireUnderstandPublicData|here]].

== Asking questions and Talk Pages ==
Want to ask questions, share ideas, discuss policy and approaches? We have set up Talk pages for all of these. Each of these are a subject-specific discussion forum. See our [[TycheTalk:UsingTalk|Talk Pages overview]].
== Data news story conventions ==
We are developing a set of conventions that guide the data storytelling process and articles. We have created [[TycheConventions:Overview|a set of initial documents]] and will be expanding this based on the community's feedback and guidance.
== Data news story how-to ==
You may already know how to analyze data using many different tools and methods, or you may need some hints or even complete recipes for how you perform certain analysis. We are creating various how-to documents and will be expanding this list. [[TycheHowTo:Overview|Access our document]] with links to various how-to documents.

== Any Other Questions? ==
You can reach out to us via email.

* General questions about joining? JoinUs@TycheInsights.com
* Co-founder Karl Urich ([[User:KarlTyche|KarlTyche]]) - karl@tycheinsights.com
* Co-founder Keith Gargiulo ([[User:KeithTyche|KeithTyche)]] - keith@tycheinsights.com

Main Page

2026-01-26T20:31:16Z

KarlTyche: /* Featured data story */

<big>'''''Unbiased data storytelling and data journalism using public, government data - by citizens, for citizens.'''''</big>[[File:Data Story Collage.png|none|thumb|950x950px]]
== About Tyche Insights ==

* What is a [[TycheAbout:WhatIsADataStory|Data Story]]?
* What are the [[TycheAbout:DataStoryComponents|components of a Data Story]]?
* What is [[TycheAbout:WhatIs|Tyche Insights]]?
* What is the [[TycheAbout:Purpose|purpose]] of Tyche Insights?
* [[TycheAbout:WhoContributes|Who contributes]] to Tyche Insights and why?
* What is the [[TycheAbout:CopyrightLicensing|licensing and copyright]] of Tyche Insights content?
* Who [[TycheAbout:ReadersAndUsers|reads and uses]] Tyche Insights content?
* What is the Tyche Insights [[TycheAbout:OriginStory|origin story]]?

== Search for data stories & data journalism ==
As we launch Tyche Insights we begin with a set of content that we have populated for [[:Category:Albany NY|Albany, New York]]. These are stories that analyze the [[:Category:Albany NY|City of Albany]]'s housing, crime, population, taxes, state funding and more. To understand the types of stories that you will see over time (and potentially to give you some ideas on data stories that you can write!), search using terms such as "Albany", "Crime", "Finance" and more.

We also have the concept of a "[[Hub:Albany Data Stories|Hub]]" where a group is focused on a broader storytelling effort.

== Featured data story ==
[[File:Excel Example CrashDataAndChart.png|thumb|200x200px|Analyze NY-wide pedestrian crash data ]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - is available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

See our list of prior [[FeaturedDataStories|Featured Stories]].

== Opinions and News ==

* [[TycheOpEd:OpenDataFlywheel|The Open Data Flywheel]] - December 18, 2025
* [[TycheOpEd:FiveThingsWeLearned|What we learned from our Albany, NY test]] - January 11, 2026

== Join us, follow us, talk to us ==
Join the Tyche Insights community by clicking '''"Create account"''' at the top of this page. When you create an account you can write a data story, ask for assistance as you write your data story, comment and ask questions on existing data stories, participate in our Talk pages, receive email updates from Tyche Insights and more. Feel free to create an account even if you only want to read public data-driven stories & journalism which will help us understand the reach of our community's storytelling.

Want to talk to someone at Tyche Insights? If you're interested in writing your first story, discussing a challenge that you've had in obtaining the right data, talking about the company and its mission, or for any other reason - [https://calendly.com/karl-tycheinsights/learn-about-the-tyche-community Click this link] to schedule a 15 minute Zoom with the Tyche Insights team.

Other ways to follow and contact us? [https://www.linkedin.com/company/tycheinsights follow us on LinkedIn] to receive updates and see our emails at the bottom of the page.

== Data storytelling & data journalism as a Collaboration ==
We want to support anyone or any group of people who wants to use public data for data storytelling and journalism. If you are a solo data storyteller or a group of concerned citizens in a community, you are welcome here.

We also believe that data storytelling as a collaboration is powerful - many people from different cities and towns, analyzing similar data from their local governments, using the same tools, supporting each other.
[[File:HFDP Overview.png|thumb|400x400px]]
We're excited to support our first group data storytelling project - the [https://hudsonfinancedecoder.com/ Hudson Finance Decoder Project]. The purpose of this project is "Citizens working together to analyze the financial health of their cities, towns and counties across the USA and Canada." We will support anyone, anywhere who wants to create a Strong Towns Finance Decoder for their community, and then to turn that Finance Deocoder into a data story, [[Albany, New York Financial State|like we did for Albany, NY]].

And we are creating a queue of future data storytelling collaborations. Helping anyone, anywhere analyze your community's crime and budgets are at the top of the queue.

== Interested in Contributing? ==

What does data storytelling look like? What is the process? Walk through the process [[TycheHowTo:WhereToStart|here]].

As your read and contribut to Tyche Insights, please abide by our [[TycheAbout:CodeOfConduct|Code of Conduct]].
== Acquiring and understanding Public Data ==
What is public data? What types of public data exist that you might use? How do you acquire public data?

We provide a number of answers to these questions [[TycheHowTo:AcquireUnderstandPublicData|here]].

== Asking questions and Talk Pages ==
Want to ask questions, share ideas, discuss policy and approaches? We have set up Talk pages for all of these. Each of these are a subject-specific discussion forum. See our [[TycheTalk:UsingTalk|Talk Pages overview]].
== Data news story conventions ==
We are developing a set of conventions that guide the data storytelling process and articles. We have created [[TycheConventions:Overview|a set of initial documents]] and will be expanding this based on the community's feedback and guidance.
== Data news story how-to ==
You may already know how to analyze data using many different tools and methods, or you may need some hints or even complete recipes for how you perform certain analysis. We are creating various how-to documents and will be expanding this list. [[TycheHowTo:Overview|Access our document]] with links to various how-to documents.

== Any Other Questions? ==
You can reach out to us via email.

* General questions about joining? JoinUs@TycheInsights.com
* Co-founder Karl Urich ([[User:KarlTyche|KarlTyche]]) - karl@tycheinsights.com
* Co-founder Keith Gargiulo ([[User:KeithTyche|KeithTyche)]] - keith@tycheinsights.com

Main Page

2026-01-26T20:29:52Z

KarlTyche: /* Featured data story */

<big>'''''Unbiased data storytelling and data journalism using public, government data - by citizens, for citizens.'''''</big>[[File:Data Story Collage.png|none|thumb|950x950px]]
== About Tyche Insights ==

* What is a [[TycheAbout:WhatIsADataStory|Data Story]]?
* What are the [[TycheAbout:DataStoryComponents|components of a Data Story]]?
* What is [[TycheAbout:WhatIs|Tyche Insights]]?
* What is the [[TycheAbout:Purpose|purpose]] of Tyche Insights?
* [[TycheAbout:WhoContributes|Who contributes]] to Tyche Insights and why?
* What is the [[TycheAbout:CopyrightLicensing|licensing and copyright]] of Tyche Insights content?
* Who [[TycheAbout:ReadersAndUsers|reads and uses]] Tyche Insights content?
* What is the Tyche Insights [[TycheAbout:OriginStory|origin story]]?

== Search for data stories & data journalism ==
As we launch Tyche Insights we begin with a set of content that we have populated for [[:Category:Albany NY|Albany, New York]]. These are stories that analyze the [[:Category:Albany NY|City of Albany]]'s housing, crime, population, taxes, state funding and more. To understand the types of stories that you will see over time (and potentially to give you some ideas on data stories that you can write!), search using terms such as "Albany", "Crime", "Finance" and more.

We also have the concept of a "[[Hub:Albany Data Stories|Hub]]" where a group is focused on a broader storytelling effort.

== Featured data story ==
[[File:TownofColonie GTTR.png|thumb|200x200px|A Finance Decoder chart for Colonie, NY ]]

=== Analyzing pedestrian crash data in the City of Albany, NY and making pedestrian crash data available state-wide ===
This featured data story is a two-for. We [[Albany, New York Pedestrian Crash|analyzed the City of Albany's pedestrian crash data]] using a state-wide dataset FOILed from New York's Department of Transportation covering 2020-2025. We were astounded at what we found; over 600 pedestrian crashes since 2020, 14 pedestrian crash deaths, 111 pedestrian crashes with serious injuries. Where are these crashes taking place? Is the rate of pedestrian crashes going down or up? Do most crashes & deaths happen during the day or night, and on which day of the week? These are questions that we dig into with the data.

Secondly, while our initial story was focused on Albany, we ran all of the same enrichment and data prep processes on the state-wide data. We have [[New York Pedestrian Crash Data|posted the all of this state-wide data]] in GIS and Excel formats. Anyone can use these state-wide datasets for their analysis or for their own data storytelling. These datasets - as with all Tyche Insights content - is available using a Creative Commons license that allows anyone to freely use, share and build upon the data without restrictions.

See our list of prior [[FeaturedDataStories|Featured Stories]].

== Opinions and News ==

* [[TycheOpEd:OpenDataFlywheel|The Open Data Flywheel]] - December 18, 2025
* [[TycheOpEd:FiveThingsWeLearned|What we learned from our Albany, NY test]] - January 11, 2026

== Join us, follow us, talk to us ==
Join the Tyche Insights community by clicking '''"Create account"''' at the top of this page. When you create an account you can write a data story, ask for assistance as you write your data story, comment and ask questions on existing data stories, participate in our Talk pages, receive email updates from Tyche Insights and more. Feel free to create an account even if you only want to read public data-driven stories & journalism which will help us understand the reach of our community's storytelling.

Want to talk to someone at Tyche Insights? If you're interested in writing your first story, discussing a challenge that you've had in obtaining the right data, talking about the company and its mission, or for any other reason - [https://calendly.com/karl-tycheinsights/learn-about-the-tyche-community Click this link] to schedule a 15 minute Zoom with the Tyche Insights team.

Other ways to follow and contact us? [https://www.linkedin.com/company/tycheinsights follow us on LinkedIn] to receive updates and see our emails at the bottom of the page.

== Data storytelling & data journalism as a Collaboration ==
We want to support anyone or any group of people who wants to use public data for data storytelling and journalism. If you are a solo data storyteller or a group of concerned citizens in a community, you are welcome here.

We also believe that data storytelling as a collaboration is powerful - many people from different cities and towns, analyzing similar data from their local governments, using the same tools, supporting each other.
[[File:HFDP Overview.png|thumb|400x400px]]
We're excited to support our first group data storytelling project - the [https://hudsonfinancedecoder.com/ Hudson Finance Decoder Project]. The purpose of this project is "Citizens working together to analyze the financial health of their cities, towns and counties across the USA and Canada." We will support anyone, anywhere who wants to create a Strong Towns Finance Decoder for their community, and then to turn that Finance Deocoder into a data story, [[Albany, New York Financial State|like we did for Albany, NY]].

And we are creating a queue of future data storytelling collaborations. Helping anyone, anywhere analyze your community's crime and budgets are at the top of the queue.

== Interested in Contributing? ==

What does data storytelling look like? What is the process? Walk through the process [[TycheHowTo:WhereToStart|here]].

As your read and contribut to Tyche Insights, please abide by our [[TycheAbout:CodeOfConduct|Code of Conduct]].
== Acquiring and understanding Public Data ==
What is public data? What types of public data exist that you might use? How do you acquire public data?

We provide a number of answers to these questions [[TycheHowTo:AcquireUnderstandPublicData|here]].

== Asking questions and Talk Pages ==
Want to ask questions, share ideas, discuss policy and approaches? We have set up Talk pages for all of these. Each of these are a subject-specific discussion forum. See our [[TycheTalk:UsingTalk|Talk Pages overview]].
== Data news story conventions ==
We are developing a set of conventions that guide the data storytelling process and articles. We have created [[TycheConventions:Overview|a set of initial documents]] and will be expanding this based on the community's feedback and guidance.
== Data news story how-to ==
You may already know how to analyze data using many different tools and methods, or you may need some hints or even complete recipes for how you perform certain analysis. We are creating various how-to documents and will be expanding this list. [[TycheHowTo:Overview|Access our document]] with links to various how-to documents.

== Any Other Questions? ==
You can reach out to us via email.

* General questions about joining? JoinUs@TycheInsights.com
* Co-founder Karl Urich ([[User:KarlTyche|KarlTyche]]) - karl@tycheinsights.com
* Co-founder Keith Gargiulo ([[User:KeithTyche|KeithTyche)]] - keith@tycheinsights.com

FeaturedDataStories

2026-01-26T20:21:36Z

KarlTyche:

=== Our first Finance Decoders from the Hudson Finance Decoder Project ===
We started the Hudson Finance Decoder Project to help anyone, anywhere create a Finance Decoder. We [[TycheNews:FirstFinanceDecoders|posted an article]] describing the first Finance Decoders that have been created and posted. We now have stories that examine local government finances for cities such as Gainesville, FL and Pueblo, CO, and counties like Washoe County, NV.

These stories extend the basic Finance Decoder template to provide additional analysis (e.g. on local government debt), comparisons against neighboring cities, and more.

=== Wichita, Kansas LandValuePerAcre ===
One way to examine the utilization and value of the land use in your community is to create a Total Value Per Acre (TVPA) analysis for your town. The idea is that various areas of your city, town or county contribute to the property tax roll at different rates. See this [[Wichita, Kansas LandValuePerAcre|new article on TVPA analysis]] for Wichita, Kansas.
[[File:NorthAndSouthOf54.png|thumb|200x200px]]

Sometimes this contribution is obvious; an undeveloped one-acre parcel of land contributes less tax than a one-acre parcel of developed land. Sometimes the contributions are counterintuitive. A 2-acre property with a two million dollar home might contribute less to the property tax roll than if there were 10 0.2 acre houses on the same property.

We like this story for a number of reasons. First, it builds on Strong Towns and their championing of TVPA analysis. Secondly, we [[TycheHowTo:CreateValuePerAcreMap|laid out a process]] that explains how anyone can perform similar analysis for their community.

Lastly, TVPA analysis doesn't necessarily get you to an outcome of "this area is good, this area is bad", rather it shows you how land has been built up and used, and what the impact is from an improved value perspective. We want this analysis to inform future decisions that support the next generation of housing development.

=== Analyzing Albany NY's Crime ===
[[File:CrimeMap 15.png|thumb|200x200px]]
Our community member, Adam, [[Albany, New York Crime Maps|analyzed Albany, NY's crime]] and where it happens as a two-part exploration into the types, trends and locations of crime.

We like this data story for a number of reasons. Crime mapping highlights both where crime happens and, just as importantly, where crime is low - the mapping teased out some areas of high and low crime that weren't intuitive. Adam also built the crime mapping analysis never having done any geospatial work prior. We wrote a short how-to on [[TycheHowTo:CreateHeatMap|creating heat maps]] that supported this analysis.

Lastly, a Criminology professor from our local university read the article and brought us into their classroom to talk to students about our work. While this was an unexpected outcome, it's just what we want to have happen - a data story informs and is used by others.

New York Pedestrian Crash Data

2026-01-26T20:05:35Z

KarlTyche: /* Overview */

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine.

The data is also available as a geospatial file in .shp format.

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may freely share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide propert attribution for the source of the data.

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Sources]]

Category:Data Sources

2026-01-26T20:04:26Z

KarlTyche: Created page with "The purpose of this page is to link to data stories that contain content that can be downloaded or analyzed. At Tyche Insights we will have certain data that we ready and enable for analysis for data storytellers."

The purpose of this page is to link to data stories that contain content that can be downloaded or analyzed. At Tyche Insights we will have certain data that we ready and enable for analysis for data storytellers.

New York Pedestrian Crash Data

2026-01-26T20:03:18Z

KarlTyche: /* Credits */

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine.

The data is also available as a geospatial file in .shp format.

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide propert attribution for the source of the data.

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Sources]]

New York Pedestrian Crash Data

2026-01-26T20:02:07Z

KarlTyche: /* Data Downloads */

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine.

The data is also available as a geospatial file in .shp format.

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide propert attribution for the source of the data.

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Source]]

New York Pedestrian Crash Data

2026-01-26T20:01:47Z

KarlTyche:

[[File:Excel Example CrashDataAndChart.png|none|thumb|700x700px|An image from the New York State pedestrian crash data and analysis]]

== Overview ==

When we [[Albany, New York Pedestrian Crash|analyzed pedestrian crash data for the City of Albany, NY]] and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for other counties and cities within New York. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, so you can perform much of the same analysis (or more!) without having to go through various processes to clean up and enrich the data. We enriched the NY DOT data with processes that include:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the names of streets where the crashes took place
* adding the notion of whether an accident happened on a major or minor street
* changing the coordinate information to a coordinate system that is more readily mappable 

From there, we put the data into Microsoft Excel format and added various pivot tables and charts. The purpose of these tables and charts is to demonstrate various ways that the data can be used and examine.

The data is also available as a geospatial file in .shp format.

The data is available via a Creative Commons Attribution license that allows you to do whatever you want with the data. You may share the data, build upon it, storytell on top of the data, turn the data into a commerical product, create derivative work, etc. The only requirement is to provide propert attribution for the source of the data.

== Data Downloads ==

We have placed two files in a [https://drive.google.com/drive/folders/1BBF547mEa8AbSbC7J7qRNikuoMHhlBN8?usp=sharing Google Drive folder for download]. If you are unable to see these folders please send an email to karl@tycheinsights.com.

Two files:

# NYPedestrianCrashData_Final_Version1.xlsx - This is the Microsoft Excel file that is available for download. See the following sheets for more details:
#* Cover_sheet - provides details on the version of the file and the Creative Commons license
#* Data_Descirption - provides details on the data schema
#* Sheets_Description - provides an overview of each of the sheets that have pivot tables and charts
#* NYPedestrianCrashData - is the original data from NY DOT along with the columns of additional enrichment
#* Other sheets - 14 other sheets that demonstrate various ways to use and examine the data
# PedestrianEvents_Base.zip - This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file

[[File:PedestrianEvents Base.zip|none|thumb|GIS .shp file of enriched pedestrian crash data for New York State]]

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Source]]

File:Excel Example CrashDataAndChart.png

2026-01-26T19:47:41Z

KarlTyche:

An image from the New York State pedestrian crash data and analysis

New York Pedestrian Crash Data

2026-01-26T19:42:49Z

KarlTyche:

== Overview ==

When we analyzed pedestrian crash data for the City of Albany, NY and then wrote a data story, we utilized a state-wide dataset of pedestrian crash data from New York State Department of Transporation.

We want to make this dataset available state-wide, in a manner than can be studied or used to write similar data stories for counties and states. We ran the same enrichment processes on the state-wide data that we did for the City of Albany study, including:

* adding in data for the boundaries - City, County, Town and Neighborhood - where each pedestrian crash happened
* linking intersection- and non-intersection-based crashes to the named intersection
* linking 

[[Albany, New York Pedestrian Crash]]

== Data Downloads ==

This is the Geospatial file representation of the source data. If you would like to analyze this data in QGIS, ArcGIS or other mapping technologies, use this file.
[[File:PedestrianEvents Base.zip|none|thumb|GIS .shp file of enriched pedestrian crash data for New York State]]

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Source]]

File:PedestrianEvents Base.zip

2026-01-26T19:38:54Z

KarlTyche:

GIS .shp file of enriched pedestrian crash data for New York State

Category:New York

2026-01-26T19:36:37Z

KarlTyche: Created page with "This is a page for links to New York State-wide data stories and content."

This is a page for links to New York State-wide data stories and content.

New York Pedestrian Crash Data

2026-01-26T19:36:10Z

KarlTyche: /* Credits */

== Overview ==

[[Albany, New York Pedestrian Crash]]

== Credits ==
The data is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'New York Pedestrian Crash Data', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:New_York]]
[[Category:Pedestrian_Crash]]
[[Category:Data_Source]]

New York Pedestrian Crash Data

2026-01-26T19:35:36Z

KarlTyche: Created page with "== Overview == Albany, New York Pedestrian Crash == Credits == The data is available under the Creative Commons Attribution license. Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes: * © Copyright 2026 * Tyche Insights, P.B.C. * KarlTyche (Karl Urich) For example, a data product or service that utilizes this article could include attribution such as: "Po..."

Albany, New York Pedestrian Crash

2026-01-26T19:27:01Z

KarlTyche:

== Analyzing Pedestrian Crashes in Albany ==
[[File:CoreAlbany.png|none|thumb|600x600px|Pedestrian Crash Locations in Albany, NY]]
''“The annual number of crashes in the city has trended downward over the past three years. In 2022, there were 3,838 traffic crashes, with 575 involving some level of injury. Last year city police responded to 3,649 crashes, which included everything from minor scrapes and fender benders to head-on collisions, with 562 crashes involving some level of injury.”''

* “Albany sees traffic crashes drop with new speed limit”, Times Union, [https://www.timesunion.com/news/article/albany-sees-traffic-crashes-drop-new-25-mph-speed-20250081.php April 6, 2025]

''“This year we added more than 70 speed humps, implemented a new 25 MPH citywide speed limit, and completed installation of speed cameras across 20 school zones to enforce the existing 20 MPH speed limit where our younger residents learn every day. These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”''

* City of Albany [https://www.albanyny.gov/DocumentCenter/View/13182/2026-Proposed-Budget-PDF Proposed budget], p 6

== Overview ==
Traffic safety, both actions to make our streets safer and using data to analyze trends, is receiving significant attention nationwide and in the City of Albany. [https://visionzeronetwork.org/resources/vision-zero-communities/ Vision Zero] is the nationwide road and pedestrian safety organization that communities are rallying around, which includes [https://www.capitalregionvisionzero.org/ Capital District Vision Zero].

Nationwide, car-on-pedestrian crashes are more likely to cause serious injuries or fatalities than car-on-car accidents; pedestrian deaths are [https://www.cdc.gov/mmwr/volumes/74/wr/mm7408a2.htm growing at a faster rate] than overall traffic-related deaths. Yet car-on-pedestrian crashes get bundled into overall traffic safety reporting, and the volume, severity and visibility of pedestrian crashes get diluted in the discussion.

What is missing for us is the data, specifically data on pedestrian crashes - not just "traffic accidents" - within the City of Albany. We want to understand Albany’s pedestrian crash data - where it happens, when it happens, and what the trends are. Our goal is pretty simple - we want to demonstrate that pedestrian crash data is available and it should visibly inform the City of Albany’s planning, goal setting, analysis and communication about the progress that we are making.

We are also aware that the science and analysis of pedestrian safety is evolving. Writing this article we looked for research on the benefit of specific pedestrian safety infrastructure and programs. We communicated with several people involved in pedestrian safety research. From our point of view the linkage between pedestrian safety and the introduction of pedestrian safety measures can best be described as directional and/or early stage. For us this validates the need for the City to be using data to inform the actions that we take and to connect those actions to observable, objective benefits; or identify where our safety measures do not appear to be providing benefit.

Before we move to the analysis, a quick prefacing word. Our analysis may come across as dispassionate - reducing pedestrian crashes, injuries and deaths to numbers. We are well aware that behind these numbers are people - people who die, people who are injured, and families that are impacted by pedestrian crashes.

== The Data and Preliminary Analysis ==
We FOILed statewide pedestrian crash data from New York State DOT and received a file of over 75,000 car-on-pedestrian crashes statewide between January 1, 2020 and October 27, 2025.
[[File:InputData.png|none|thumb|500x500px|Pedestrian crash source data from New York Department of Transportation]]
Each crash record (image above) contains the data, time of day, injury and fatality information, reporting agency, and then other information on the conditions, circumstances and road network.

We extracted the 644 pedestrian crashes reported by the Albany Police Department over the time period to create our analysis dataset. While other law enforcement agencies (State Police, Campus Police, etc) reported pedestrian crashes within the City limits the numbers were not material or were associated with Interstate highway pedestrian crashes.

We mapped out every crash (below) and computed a few data points that we would use in our analysis:

* The name of the road where the crash happened
* The major road or minor road designation of the road where the crash happened
* The neighborhood where the crash happened
* Whether the crash happened in a school camera speed zone

[[File:OverviewMap.png|none|thumb|700x700px|Overview map of City of Albany Pedestrian Crashes, Jan 2020 to Oct 2025]]

== How Severe are the Crashes? ==
The DOT data collected by local law enforcement agencies contains three pieces of data on the severity of the pedestrian crash - how many people died, how many people sustained serious injuries, how many people sustained other injuries.
[[File:PedestrianCrashOutcome.png|none|thumb|400x400px|City of Albany Pedestrian Crash Outcomes]]
Our understanding of a “Serious Injury” is one where a person suffers dismemberment, fracture, loss of a fetus, permanent loss of a body organ, and/or any injury that limits a person’s ability to live normally for at least 90 days during the 180 days immediately following the crash. Any crash can have 0, 1 or more people who fall in each of the three categories.

For the 644 pedestrian crashes in the City of Albany between Jan 2020 and October 2025, 2% result in a fatality, 17% result in one or more serious injuries, 69% result in one or more other injuries, and 15% result in no injuries.

Note - percentages do not add to 100% - any crash can have more than one outcome. There are three streets where multiple fatality-producing crashes occurred: Washington Ave, Central Ave and Everett Road.

== What is the Overall Trend in Pedestrian Crashes? ==
Is the rate of pedestrian crashes increasing, decreasing or static? Prior to answering this question we can explain the time period that we chose to study. We stopped the trend study at the end of Q2 2025 (June 30th). While we have pedestrian crash data from NY State through late October 2025 we found that there is a latency in entering pedestrian crash data into the system. Each crash record lists the crash data and the date of data entry; typically there is a week or more delay, however many crashes take 90+ days to be entered into the system. We concluded that the Q3 (July-September) data was likely missing crash data due to this delay.

We can review crashes by quarter in a chart from Q1 2020 through Q2 2025. We also overlaid a trendline that uses a statistical method (polynomial) to show the overall trend.
[[File:CrashesByQuarter.png|none|thumb|700x700px|City of Albany, NY Quarterly trend in pedestrian crashes]]
Are pedestrian crashes going down? That is a tough question to answer with any certainty. A few bullet points capture our observations:

* The data from the first half of 2025 suggests improvement in pedestrian safety
* The pandemic likely, but not certainly, had some effect on minimizing traffic incidents in 2020 and 2021
* We do not know how the crash reporting processes may have changed, which may have caused over- or understatements for certain quarters
* Some of the large spikes and troughs may be just statistical chance

GIven those considerations, we would suggest two takeaways:

# the 2025 trend suggests improvement however 3-5 quarters of additional data are required before anyone can make broad claims of pedestrian safety improvement
# the pedestrian crash data, regardless of trend, demonstrates that there is a big gap to get to Vision Zero.

== Where do pedestrian crashes happen? ==
A quick point about our analysis before we describe where accidents happen. To determine the level (minor or major) of any given road we use DOT Arterial Classification Codes (ACC) associated with each road. A road gets an ACC based on its importance, usage, traffic volume, etc. In the map below ACC=3 (yellow), ACC=4 (purple), ACC=5 (red).
[[File:ACC AlbanyStreets.png|none|thumb|500x500px|Albany's streets displaying Arterial Classification Codes]]
In our analysis below we consider major roads to include ACC 3 & 4, and minor roads to be ACC 5. We linked each pedestrian crash to a road and determined if each crash was associated with a major road or a minor road. For a handful of crashes (13) we could not reliably determine the associated road.

* 486 pedestrian crashes (77%) occurred on '''Major Roads'''
* 145 pedestrian crashes (23%) occurred on '''Minor Roads'''

We can then analyze where pedestrian crashes happen, by street and by neighborhood.

The streets (by name) with more than 10 pedestrian crashes between 2020 and 2025:
{| class="wikitable sortable"
|+City of Albany, Crashes by Street
!Street
!Incident Count
!Percentage of Total Pedestrian Crashes
|-
|Central Avenue
| align="right" |83
| align="right" |13.2%
|-
|Washington Avenue
| align="right" |49
| align="right" |7.8%
|-
|Madison Avenue
| align="right" |47
| align="right" |7.5%
|-
|New Scotland Avenue
| align="right" |42
| align="right" |6.6%
|-
|Lark Street
| align="right" |28
| align="right" |4.4%
|-
|Delaware Avenue
| align="right" |24
| align="right" |3.8%
|-
|South Pearl Street
| align="right" |22
| align="right" |3.5%
|-
|Western Avenue
| align="right" |20
| align="right" |3.2%
|-
|Henry Johnson Boulevard
| align="right" |19
| align="right" |3.0%
|-
|Livingston Avenue
| align="right" |18
| align="right" |2.9%
|-
|Clinton Avenue
| align="right" |18
| align="right" |2.8%
|-
|Quail Street
| align="right" |11
| align="right" |1.8%
|-
|Morton Avenue
| align="right" |10
| align="right" |1.6%
|-
|Broadway
| align="right" |10
| align="right" |1.6%
|-
|North Allen Street
| align="right" |10
| align="right" |1.6%
|}
The neighborhoods with the most pedestrian crashes (more than 5% of overall pedestrian crashes) include these 6 neighborhoods:
{| class="wikitable sortable"
|+City of Albany, Crashes by Neighborhood
!Neighborhood
!Number of Pedestrian Crashes
!Percentage of Total Pedestrian Crashes
|-
|West Hill
| align="right" |84
| align="right" |13.3%
|-
|Pine Hills
| align="right" |70
| align="right" |11.1%
|-
|Central Avenue
| align="right" |53
| align="right" |8.4%
|-
|Arbor Hill
| align="right" |42
| align="right" |6.7%
|-
|Upper Washington Avenue
| align="right" |34
| align="right" |5.4%
|-
|Delaware Avenue
| align="right" |34
| align="right" |5.4%
|}
We reviewed the number of accidents that are within 200 yards of a school zone speed camera. (Map above). Between 2020 and October 2025 there were:

* 5 serious injuries in a school zone between the hours of 7am and 6pm, not including July and August. 2 serious injuries occurred in 2020 and 3 serious injuries occurred in 2023.
* 19 other injuries in a school zone between the hours of 7am and 6pm, not including July and August

[[File:SchoolZones.png|none|thumb|400x400px|Map of neighborhood school zones]]
We can use this historical data to understand the current and future pedestrian safety benefit of the school zone speed camera program.

Lastly, the pedestrian crash data identifies, for each crash, whether the accident occurred at an intersection or not at an intersection. The map below - the south end of Lark St near Madison Ave - shows pedestrian crashes at intersections using green circles, and pedestrian crashes that happened in-between intersections are identified with black squares.
[[File:Albany Intersection NonInts.png|none|thumb|400x400px|Map of pedestrian crashes at intersections and non-intersection crashes]]
Roughly 60% of pedestrian crashes occur at intersections, 40% in-between intersections. We doubt the value of ranking the “top 10 most dangerous intersections in Albany”, however we can note that intersections with the highest number of pedestrian crashes during the study period include Lark St & Washington Ave, New Scotland & Madison Ave, and Central Ave & Henry Johnson Blvd.

== When do Pedestrian Crashes Happen? ==
What insight could we find from understanding when - day vs. night, day of week - pedestrian crashes happen? The pedestrian crash data codes “Light conditions” in 5 categories - DAYLIGHT, DAWN, DUSK, DARK-ROAD LIGHTED, and DARK-ROAD UNLIGHTED. We created two categories for Day vs. Night, where Day consists of DAYLIGHT and DAWN, and Night consists of the other three categories. 63% of the City’s pedestrian crashes happen during the day, 37% at night.

We then plotted pedestrian crashes by day of week and day vs. night. We had some thoughts about when pedestrian crashes are most prevalent and none proved to be correct. We were extremely surprised by the day-to-day variability in overall pedestrian accidents, and the day-to-day consistency in night pedestrian crashes.
[[File:PedestrianCrashes DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Crashes by Day of Week, Night vs. Day]]
Similarly, we can examine when pedestrian deaths happen. Deaths generally track the day of week rate, with a much higher percentage of deaths happening at Night (72%).
[[File:PedestrianDeaths DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Deaths by Day of Week, Night vs Day]]
As we analyze when pedestrian deaths happen we can look at broader analysis. The National Safety Council’s [https://injuryfacts.nsc.org/motor-vehicle/road-users/pedestrians/ analysis of pedestrian crashes], states:

''“The largest number of pedestrian deaths occurs on Fridays (1,155), closely followed by Saturdays (1,150). Except for a decline on Sundays, the number of pedestrian deaths during daylight hours is relatively consistent throughout the week. However, pedestrian fatalities at night (during dark with or without artificial lighting) vary substantially. Nighttime pedestrian deaths are at their lowest point on Tuesday and peak on Saturday and Sunday.”''

These statements do and don’t align with the City of Albany’s pedestrian deaths, however this could be due to the low volume of pedestrian deaths on the City’s roads.

== How does Albany compare against Capital District cities? ==
We ran the same trend analysis for Troy and Schenectady - a quarterly analysis of pedestrian crashes for each city between 2020 and Q2 2025. While Troy and Schenectady have fewer pedestrian crashes we wanted to identify how each city’s trend compares. In the graph below the quarter-to-quarter pedestrian crash data and trends are in solid lines. The statistical trend for each city is shown with a dashed line.
[[File:PedestrianCrashes 3Cities.png|none|thumb|700x700px|Pedestrian crash comparison for Albany, Troy and Schenectady]]
Troy has seen a slight downturn in pedestrian crashes while Schenectady has shown a slight uptick. Both communities are a part of Capital Region Vision Zero, similar to the City of Albany. We have not examined if either Schenectady or Troy has been making the same investment in traffic calming measures as the City of Albany.

Our takeaway from the inter-city comparison is that this is an interesting data point for us to track. Within these three peers cities we can examine broad trends in pedestrian safety and the linkage between safety investment and awareness and reduction in pedestrian crashes.

== Summary ==
We picked a few of the many ways to examine the City of Albany’s pedestrian crashes since 2025. We wrote this article to highlight some of the data points that we are seeing from examining the pedestrian crash data.

We also want to ask our readers - what questions do you have that we can attempt to answer? If you have a question concerning pedestrian safety and crashes that you think we may be able to answer, drop us an email at [[MailTo:AlbanyDataStories@gmail.com|AlbanyDataStories@gmail.com]].

The City makes significant investments year-over-year in our streets and related safety. The City’s budget items that directly or indirectly support transportation safety in the 2026 proposed budget include:

* $1 million for traffic speed reduction measures
* $15 million for traffic signal improvements
* $14.5 million for street reconstruction
* $0.65 million for streetlight improvements
* $0.65 million for sidewalk reconstruction
* $0.4 million for roadway striping
* $0.3 million for traffic safety equipment

Net, the City invests over $30 million in road maintenance and improvements. Optimizing or directing this spending for traffic safety should be an important consideration. For example, the data could guide whether we should or shouldn't be installing speed humps on minor streets with no history of pedestrian crashes.

We can suggest a few outcomes from our analysis:

# New York must make pedestrian safety data and all other traffic crash data available to the public proactively, not requiring a FOIL
# The City of Albany should make all pedestrian and traffic safety analysis available on the City’s [https://data.albanyny.gov/ open data website]. Quoting statistics and studies must be accompanied by visibility of the analysis. For example, let’s see the data and analysis behind our opening quote from the 2026 budget “These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”
# Data should be used to analyze our new and improved infrastructure. If we have installed speed humps, pedestrian walkway improvements of various types, speed zone cameras and more, can we identify which improvements are or are not making a difference?
# Data should inform our goals. Our City should set targets or goals for the total number of pedestrian crashes, or related fatalities and serious injuries. As an illustrative example, in 2027 can we strive to have fewer than 70 pedestrian crashes and no fatalities?
# If we have data on our improvements to date (#3) and our goals (#4), can we use those data points to prioritize how and where we make improvements and additions to our infrastructure? Data should inform our $30 million of 2026 infrastructure spending.
# Let’s use the word “crash” rather than “accident” when we are talking about public safety. “Crash” conveys the tragic consequences of what are, in most cases, avoidable scenarios.

For further reading regarding the City’s pedestrian safety programs we suggest looking at:

* City of Albany [https://www.capitalmpo.org/wp-content/CRTC/images/linkage_program/AlbCoFinal/albanyCSPolicyandDesignManual_Final.pdf Complete Streets Design Guidelines]
* City of Albany [https://99a4b737-7711-4d6a-854e-2e74e07f3d6a.filesusr.com/ugd/b59736_f67b877056c54b5e9ce9754ae4fe4650.pdf Bicycle and Pedestrian Master Plan]

We have also posted the datasets that we received via FOIL in this Google Drive for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Data ==
For this article we FOILed pedestrian crash data from NY State Department of Transportation.

We have also posted the datasets that we received via FOIL in this [https://drive.google.com/drive/folders/1RUt4k5V_JT1OvGBzq6g1nFTrqwiANk4o Google Drive] for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Process ==
We added numerous fields to the data using QGIS. The details of these additional fields include:
{| class="wikitable"
!Field Name
!Field details
|-
|X
|Longitude value, WGS 84 - derived from UTMEasting
|-
|Y
|Latitude value, WGS 84 - derived from UTMNorthing
|-
|ACC_Intersection
|Arterial Class Code of the primary or most important road at the intersection, where the pedestrian crash is an intersection crash
<nowiki> </nowiki> Note that Arterial Class Code data - here and in other fields - comes from the NY State Street Network - <nowiki>https://gis.ny.gov/streets-addresses</nowiki>
|-
|ACC_Middle
|Arterial Class Code of the street associated with a non-intersection crash. Note that ACC values of 1-4 are considered "Major Roads" and ACC = 5-6 are considered "Minor Roads"
|-
|CrashStreetName
|The main street name associated with the crash regardless of intersection vs non-intersection crashes. This field is populated with StrtMid for non-intersection crashes. This field is populated with IntPriStNm for intersection crashes
|-
|StrtIntersection
|The street names of the roads that are associated with the intersection of the pedestrian crash. Note that the street names are in alphabetical order for standardization purposes.
|-
|StrtMiddle
|The name of the street associated with a non-intersection pedestrian crash
|-
|Neighborhood
|Where found, the neighborhood where the pedestrian crash happened. Neighborhood data derived from the Zillow neighborhoods file. <nowiki>https://www.arcgis.com/home/item.html?id=56b89613f9f7450fb44e857691a244e7</nowiki>
|-
|County
|The county where the pedestrian crash happened. County boundaries are from US Census Bureau TIGER data, 2025.
|-
|MajorMinor
|A determination if a pedestrian crash happened at a major or minor road or intersection. This MajMin value conflates information from ACC_MID and IntMajMin. If ACC_MID <=4 then it is major; the value of IntMajMin is moved over to this field for intersection pedestrian crashes
|-
|City
|The incorporated city or place where the pedestrian crash happened. Place boundaries are from US Census Bureau TIGER data, 2025.
|-
|Town
|The subdivision where the pedestrian crash happened. Subdivision boundaries are from US Census Bureau TIGER data, 2025.
|-
|IntersectionMajorMinor
|A determination if a pedestrian crash happened at a major or minor intersection. An intersection is deemed "Major" if one or both streets have an ACC value <= 4
|-
|IntersectionPrimaryStreet
|The primary street name at the intersection. Note that this is determined first by the street with the lower (more important) Arterial Class Code value; if streets share the same ACC then the street that is chose is the first alphabetically.
|}

== Credits ==
This data story and its content is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'Albany NY Pedestrian Crash', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:Albany_NY]]
[[Category:Pedestrian_Crash]]

Category:Pedestrian Crash

2026-01-26T19:26:11Z

KarlTyche: Created page with "This page contains links to any data stories that analyze pedestrian crash data in any form, and at any geographic level."

This page contains links to any data stories that analyze pedestrian crash data in any form, and at any geographic level.

Albany, New York Pedestrian Crash

2026-01-26T19:25:31Z

KarlTyche: /* Credits */

== Analyzing Pedestrian Crashes in Albany ==
[[File:CoreAlbany.png|none|thumb|600x600px|Pedestrian Crash Locations in Albany, NY]]
''“The annual number of crashes in the city has trended downward over the past three years. In 2022, there were 3,838 traffic crashes, with 575 involving some level of injury. Last year city police responded to 3,649 crashes, which included everything from minor scrapes and fender benders to head-on collisions, with 562 crashes involving some level of injury.”''

* “Albany sees traffic crashes drop with new speed limit”, Times Union, [https://www.timesunion.com/news/article/albany-sees-traffic-crashes-drop-new-25-mph-speed-20250081.php April 6, 2025]

''“This year we added more than 70 speed humps, implemented a new 25 MPH citywide speed limit, and completed installation of speed cameras across 20 school zones to enforce the existing 20 MPH speed limit where our younger residents learn every day. These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”''

* City of Albany [https://www.albanyny.gov/DocumentCenter/View/13182/2026-Proposed-Budget-PDF Proposed budget], p 6

Traffic safety, both actions to make our streets safer and using data to analyze trends, is receiving significant attention nationwide and in the City of Albany. [https://visionzeronetwork.org/resources/vision-zero-communities/ Vision Zero] is the nationwide road and pedestrian safety organization that communities are rallying around, which includes [https://www.capitalregionvisionzero.org/ Capital District Vision Zero].

Nationwide, car-on-pedestrian crashes are more likely to cause serious injuries or fatalities than car-on-car accidents; pedestrian deaths are [https://www.cdc.gov/mmwr/volumes/74/wr/mm7408a2.htm growing at a faster rate] than overall traffic-related deaths. Yet car-on-pedestrian crashes get bundled into overall traffic safety reporting, and the volume, severity and visibility of pedestrian crashes get diluted in the discussion.

What is missing for us is the data, specifically data on pedestrian crashes - not just "traffic accidents" - within the City of Albany. We want to understand Albany’s pedestrian crash data - where it happens, when it happens, and what the trends are. Our goal is pretty simple - we want to demonstrate that pedestrian crash data is available and it should visibly inform the City of Albany’s planning, goal setting, analysis and communication about the progress that we are making.

We are also aware that the science and analysis of pedestrian safety is evolving. Writing this article we looked for research on the benefit of specific pedestrian safety infrastructure and programs. We communicated with several people involved in pedestrian safety research. From our point of view the linkage between pedestrian safety and the introduction of pedestrian safety measures can best be described as directional and/or early stage. For us this validates the need for the City to be using data to inform the actions that we take and to connect those actions to observable, objective benefits; or identify where our safety measures do not appear to be providing benefit.

Before we move to the analysis, a quick prefacing word. Our analysis may come across as dispassionate - reducing pedestrian crashes, injuries and deaths to numbers. We are well aware that behind these numbers are people - people who die, people who are injured, and families that are impacted by pedestrian crashes.

== The Data and Preliminary Analysis ==
We FOILed statewide pedestrian crash data from New York State DOT and received a file of over 75,000 car-on-pedestrian crashes statewide between January 1, 2020 and October 27, 2025.
[[File:InputData.png|none|thumb|500x500px|Pedestrian crash source data from New York Department of Transportation]]
Each crash record (image above) contains the data, time of day, injury and fatality information, reporting agency, and then other information on the conditions, circumstances and road network.

We extracted the 644 pedestrian crashes reported by the Albany Police Department over the time period to create our analysis dataset. While other law enforcement agencies (State Police, Campus Police, etc) reported pedestrian crashes within the City limits the numbers were not material or were associated with Interstate highway pedestrian crashes.

We mapped out every crash (below) and computed a few data points that we would use in our analysis:

* The name of the road where the crash happened
* The major road or minor road designation of the road where the crash happened
* The neighborhood where the crash happened
* Whether the crash happened in a school camera speed zone

[[File:OverviewMap.png|none|thumb|700x700px|Overview map of City of Albany Pedestrian Crashes, Jan 2020 to Oct 2025]]

== How Severe are the Crashes? ==
The DOT data collected by local law enforcement agencies contains three pieces of data on the severity of the pedestrian crash - how many people died, how many people sustained serious injuries, how many people sustained other injuries.
[[File:PedestrianCrashOutcome.png|none|thumb|400x400px|City of Albany Pedestrian Crash Outcomes]]
Our understanding of a “Serious Injury” is one where a person suffers dismemberment, fracture, loss of a fetus, permanent loss of a body organ, and/or any injury that limits a person’s ability to live normally for at least 90 days during the 180 days immediately following the crash. Any crash can have 0, 1 or more people who fall in each of the three categories.

For the 644 pedestrian crashes in the City of Albany between Jan 2020 and October 2025, 2% result in a fatality, 17% result in one or more serious injuries, 69% result in one or more other injuries, and 15% result in no injuries.

Note - percentages do not add to 100% - any crash can have more than one outcome. There are three streets where multiple fatality-producing crashes occurred: Washington Ave, Central Ave and Everett Road.

== What is the Overall Trend in Pedestrian Crashes? ==
Is the rate of pedestrian crashes increasing, decreasing or static? Prior to answering this question we can explain the time period that we chose to study. We stopped the trend study at the end of Q2 2025 (June 30th). While we have pedestrian crash data from NY State through late October 2025 we found that there is a latency in entering pedestrian crash data into the system. Each crash record lists the crash data and the date of data entry; typically there is a week or more delay, however many crashes take 90+ days to be entered into the system. We concluded that the Q3 (July-September) data was likely missing crash data due to this delay.

We can review crashes by quarter in a chart from Q1 2020 through Q2 2025. We also overlaid a trendline that uses a statistical method (polynomial) to show the overall trend.
[[File:CrashesByQuarter.png|none|thumb|700x700px|City of Albany, NY Quarterly trend in pedestrian crashes]]
Are pedestrian crashes going down? That is a tough question to answer with any certainty. A few bullet points capture our observations:

* The data from the first half of 2025 suggests improvement in pedestrian safety
* The pandemic likely, but not certainly, had some effect on minimizing traffic incidents in 2020 and 2021
* We do not know how the crash reporting processes may have changed, which may have caused over- or understatements for certain quarters
* Some of the large spikes and troughs may be just statistical chance

GIven those considerations, we would suggest two takeaways:

# the 2025 trend suggests improvement however 3-5 quarters of additional data are required before anyone can make broad claims of pedestrian safety improvement
# the pedestrian crash data, regardless of trend, demonstrates that there is a big gap to get to Vision Zero.

== Where do pedestrian crashes happen? ==
A quick point about our analysis before we describe where accidents happen. To determine the level (minor or major) of any given road we use DOT Arterial Classification Codes (ACC) associated with each road. A road gets an ACC based on its importance, usage, traffic volume, etc. In the map below ACC=3 (yellow), ACC=4 (purple), ACC=5 (red).
[[File:ACC AlbanyStreets.png|none|thumb|500x500px|Albany's streets displaying Arterial Classification Codes]]
In our analysis below we consider major roads to include ACC 3 & 4, and minor roads to be ACC 5. We linked each pedestrian crash to a road and determined if each crash was associated with a major road or a minor road. For a handful of crashes (13) we could not reliably determine the associated road.

* 486 pedestrian crashes (77%) occurred on '''Major Roads'''
* 145 pedestrian crashes (23%) occurred on '''Minor Roads'''

We can then analyze where pedestrian crashes happen, by street and by neighborhood.

The streets (by name) with more than 10 pedestrian crashes between 2020 and 2025:
{| class="wikitable sortable"
|+City of Albany, Crashes by Street
!Street
!Incident Count
!Percentage of Total Pedestrian Crashes
|-
|Central Avenue
| align="right" |83
| align="right" |13.2%
|-
|Washington Avenue
| align="right" |49
| align="right" |7.8%
|-
|Madison Avenue
| align="right" |47
| align="right" |7.5%
|-
|New Scotland Avenue
| align="right" |42
| align="right" |6.6%
|-
|Lark Street
| align="right" |28
| align="right" |4.4%
|-
|Delaware Avenue
| align="right" |24
| align="right" |3.8%
|-
|South Pearl Street
| align="right" |22
| align="right" |3.5%
|-
|Western Avenue
| align="right" |20
| align="right" |3.2%
|-
|Henry Johnson Boulevard
| align="right" |19
| align="right" |3.0%
|-
|Livingston Avenue
| align="right" |18
| align="right" |2.9%
|-
|Clinton Avenue
| align="right" |18
| align="right" |2.8%
|-
|Quail Street
| align="right" |11
| align="right" |1.8%
|-
|Morton Avenue
| align="right" |10
| align="right" |1.6%
|-
|Broadway
| align="right" |10
| align="right" |1.6%
|-
|North Allen Street
| align="right" |10
| align="right" |1.6%
|}
The neighborhoods with the most pedestrian crashes (more than 5% of overall pedestrian crashes) include these 6 neighborhoods:
{| class="wikitable sortable"
|+City of Albany, Crashes by Neighborhood
!Neighborhood
!Number of Pedestrian Crashes
!Percentage of Total Pedestrian Crashes
|-
|West Hill
| align="right" |84
| align="right" |13.3%
|-
|Pine Hills
| align="right" |70
| align="right" |11.1%
|-
|Central Avenue
| align="right" |53
| align="right" |8.4%
|-
|Arbor Hill
| align="right" |42
| align="right" |6.7%
|-
|Upper Washington Avenue
| align="right" |34
| align="right" |5.4%
|-
|Delaware Avenue
| align="right" |34
| align="right" |5.4%
|}
We reviewed the number of accidents that are within 200 yards of a school zone speed camera. (Map above). Between 2020 and October 2025 there were:

* 5 serious injuries in a school zone between the hours of 7am and 6pm, not including July and August. 2 serious injuries occurred in 2020 and 3 serious injuries occurred in 2023.
* 19 other injuries in a school zone between the hours of 7am and 6pm, not including July and August

[[File:SchoolZones.png|none|thumb|400x400px|Map of neighborhood school zones]]
We can use this historical data to understand the current and future pedestrian safety benefit of the school zone speed camera program.

Lastly, the pedestrian crash data identifies, for each crash, whether the accident occurred at an intersection or not at an intersection. The map below - the south end of Lark St near Madison Ave - shows pedestrian crashes at intersections using green circles, and pedestrian crashes that happened in-between intersections are identified with black squares.
[[File:Albany Intersection NonInts.png|none|thumb|400x400px|Map of pedestrian crashes at intersections and non-intersection crashes]]
Roughly 60% of pedestrian crashes occur at intersections, 40% in-between intersections. We doubt the value of ranking the “top 10 most dangerous intersections in Albany”, however we can note that intersections with the highest number of pedestrian crashes during the study period include Lark St & Washington Ave, New Scotland & Madison Ave, and Central Ave & Henry Johnson Blvd.

== When do Pedestrian Crashes Happen? ==
What insight could we find from understanding when - day vs. night, day of week - pedestrian crashes happen? The pedestrian crash data codes “Light conditions” in 5 categories - DAYLIGHT, DAWN, DUSK, DARK-ROAD LIGHTED, and DARK-ROAD UNLIGHTED. We created two categories for Day vs. Night, where Day consists of DAYLIGHT and DAWN, and Night consists of the other three categories. 63% of the City’s pedestrian crashes happen during the day, 37% at night.

We then plotted pedestrian crashes by day of week and day vs. night. We had some thoughts about when pedestrian crashes are most prevalent and none proved to be correct. We were extremely surprised by the day-to-day variability in overall pedestrian accidents, and the day-to-day consistency in night pedestrian crashes.
[[File:PedestrianCrashes DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Crashes by Day of Week, Night vs. Day]]
Similarly, we can examine when pedestrian deaths happen. Deaths generally track the day of week rate, with a much higher percentage of deaths happening at Night (72%).
[[File:PedestrianDeaths DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Deaths by Day of Week, Night vs Day]]
As we analyze when pedestrian deaths happen we can look at broader analysis. The National Safety Council’s [https://injuryfacts.nsc.org/motor-vehicle/road-users/pedestrians/ analysis of pedestrian crashes], states:

''“The largest number of pedestrian deaths occurs on Fridays (1,155), closely followed by Saturdays (1,150). Except for a decline on Sundays, the number of pedestrian deaths during daylight hours is relatively consistent throughout the week. However, pedestrian fatalities at night (during dark with or without artificial lighting) vary substantially. Nighttime pedestrian deaths are at their lowest point on Tuesday and peak on Saturday and Sunday.”''

These statements do and don’t align with the City of Albany’s pedestrian deaths, however this could be due to the low volume of pedestrian deaths on the City’s roads.

== How does Albany compare against Capital District cities? ==
We ran the same trend analysis for Troy and Schenectady - a quarterly analysis of pedestrian crashes for each city between 2020 and Q2 2025. While Troy and Schenectady have fewer pedestrian crashes we wanted to identify how each city’s trend compares. In the graph below the quarter-to-quarter pedestrian crash data and trends are in solid lines. The statistical trend for each city is shown with a dashed line.
[[File:PedestrianCrashes 3Cities.png|none|thumb|700x700px|Pedestrian crash comparison for Albany, Troy and Schenectady]]
Troy has seen a slight downturn in pedestrian crashes while Schenectady has shown a slight uptick. Both communities are a part of Capital Region Vision Zero, similar to the City of Albany. We have not examined if either Schenectady or Troy has been making the same investment in traffic calming measures as the City of Albany.

Our takeaway from the inter-city comparison is that this is an interesting data point for us to track. Within these three peers cities we can examine broad trends in pedestrian safety and the linkage between safety investment and awareness and reduction in pedestrian crashes.

== Summary ==
We picked a few of the many ways to examine the City of Albany’s pedestrian crashes since 2025. We wrote this article to highlight some of the data points that we are seeing from examining the pedestrian crash data.

We also want to ask our readers - what questions do you have that we can attempt to answer? If you have a question concerning pedestrian safety and crashes that you think we may be able to answer, drop us an email at [[MailTo:AlbanyDataStories@gmail.com|AlbanyDataStories@gmail.com]].

The City makes significant investments year-over-year in our streets and related safety. The City’s budget items that directly or indirectly support transportation safety in the 2026 proposed budget include:

* $1 million for traffic speed reduction measures
* $15 million for traffic signal improvements
* $14.5 million for street reconstruction
* $0.65 million for streetlight improvements
* $0.65 million for sidewalk reconstruction
* $0.4 million for roadway striping
* $0.3 million for traffic safety equipment

Net, the City invests over $30 million in road maintenance and improvements. Optimizing or directing this spending for traffic safety should be an important consideration. For example, the data could guide whether we should or shouldn't be installing speed humps on minor streets with no history of pedestrian crashes.

We can suggest a few outcomes from our analysis:

# New York must make pedestrian safety data and all other traffic crash data available to the public proactively, not requiring a FOIL
# The City of Albany should make all pedestrian and traffic safety analysis available on the City’s [https://data.albanyny.gov/ open data website]. Quoting statistics and studies must be accompanied by visibility of the analysis. For example, let’s see the data and analysis behind our opening quote from the 2026 budget “These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”
# Data should be used to analyze our new and improved infrastructure. If we have installed speed humps, pedestrian walkway improvements of various types, speed zone cameras and more, can we identify which improvements are or are not making a difference?
# Data should inform our goals. Our City should set targets or goals for the total number of pedestrian crashes, or related fatalities and serious injuries. As an illustrative example, in 2027 can we strive to have fewer than 70 pedestrian crashes and no fatalities?
# If we have data on our improvements to date (#3) and our goals (#4), can we use those data points to prioritize how and where we make improvements and additions to our infrastructure? Data should inform our $30 million of 2026 infrastructure spending.
# Let’s use the word “crash” rather than “accident” when we are talking about public safety. “Crash” conveys the tragic consequences of what are, in most cases, avoidable scenarios.

For further reading regarding the City’s pedestrian safety programs we suggest looking at:

* City of Albany [https://www.capitalmpo.org/wp-content/CRTC/images/linkage_program/AlbCoFinal/albanyCSPolicyandDesignManual_Final.pdf Complete Streets Design Guidelines]
* City of Albany [https://99a4b737-7711-4d6a-854e-2e74e07f3d6a.filesusr.com/ugd/b59736_f67b877056c54b5e9ce9754ae4fe4650.pdf Bicycle and Pedestrian Master Plan]

We have also posted the datasets that we received via FOIL in this Google Drive for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Data ==
For this article we FOILed pedestrian crash data from NY State Department of Transportation.

We have also posted the datasets that we received via FOIL in this [https://drive.google.com/drive/folders/1RUt4k5V_JT1OvGBzq6g1nFTrqwiANk4o Google Drive] for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Process ==
We added numerous fields to the data using QGIS. The details of these additional fields include:
{| class="wikitable"
!Field Name
!Field details
|-
|X
|Longitude value, WGS 84 - derived from UTMEasting
|-
|Y
|Latitude value, WGS 84 - derived from UTMNorthing
|-
|ACC_Intersection
|Arterial Class Code of the primary or most important road at the intersection, where the pedestrian crash is an intersection crash
<nowiki> </nowiki> Note that Arterial Class Code data - here and in other fields - comes from the NY State Street Network - <nowiki>https://gis.ny.gov/streets-addresses</nowiki>
|-
|ACC_Middle
|Arterial Class Code of the street associated with a non-intersection crash. Note that ACC values of 1-4 are considered "Major Roads" and ACC = 5-6 are considered "Minor Roads"
|-
|CrashStreetName
|The main street name associated with the crash regardless of intersection vs non-intersection crashes. This field is populated with StrtMid for non-intersection crashes. This field is populated with IntPriStNm for intersection crashes
|-
|StrtIntersection
|The street names of the roads that are associated with the intersection of the pedestrian crash. Note that the street names are in alphabetical order for standardization purposes.
|-
|StrtMiddle
|The name of the street associated with a non-intersection pedestrian crash
|-
|Neighborhood
|Where found, the neighborhood where the pedestrian crash happened. Neighborhood data derived from the Zillow neighborhoods file. <nowiki>https://www.arcgis.com/home/item.html?id=56b89613f9f7450fb44e857691a244e7</nowiki>
|-
|County
|The county where the pedestrian crash happened. County boundaries are from US Census Bureau TIGER data, 2025.
|-
|MajorMinor
|A determination if a pedestrian crash happened at a major or minor road or intersection. This MajMin value conflates information from ACC_MID and IntMajMin. If ACC_MID <=4 then it is major; the value of IntMajMin is moved over to this field for intersection pedestrian crashes
|-
|City
|The incorporated city or place where the pedestrian crash happened. Place boundaries are from US Census Bureau TIGER data, 2025.
|-
|Town
|The subdivision where the pedestrian crash happened. Subdivision boundaries are from US Census Bureau TIGER data, 2025.
|-
|IntersectionMajorMinor
|A determination if a pedestrian crash happened at a major or minor intersection. An intersection is deemed "Major" if one or both streets have an ACC value <= 4
|-
|IntersectionPrimaryStreet
|The primary street name at the intersection. Note that this is determined first by the street with the lower (more important) Arterial Class Code value; if streets share the same ACC then the street that is chose is the first alphabetically.
|}

== Credits ==
This data story and its content is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'Albany NY Pedestrian Crash', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

[[Category:Albany_NY]]
[[Category:Pedestrian_Crash]]

Albany, New York Pedestrian Crash

2026-01-26T19:24:59Z

KarlTyche:

== Analyzing Pedestrian Crashes in Albany ==
[[File:CoreAlbany.png|none|thumb|600x600px|Pedestrian Crash Locations in Albany, NY]]
''“The annual number of crashes in the city has trended downward over the past three years. In 2022, there were 3,838 traffic crashes, with 575 involving some level of injury. Last year city police responded to 3,649 crashes, which included everything from minor scrapes and fender benders to head-on collisions, with 562 crashes involving some level of injury.”''

* “Albany sees traffic crashes drop with new speed limit”, Times Union, [https://www.timesunion.com/news/article/albany-sees-traffic-crashes-drop-new-25-mph-speed-20250081.php April 6, 2025]

''“This year we added more than 70 speed humps, implemented a new 25 MPH citywide speed limit, and completed installation of speed cameras across 20 school zones to enforce the existing 20 MPH speed limit where our younger residents learn every day. These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”''

* City of Albany [https://www.albanyny.gov/DocumentCenter/View/13182/2026-Proposed-Budget-PDF Proposed budget], p 6

Traffic safety, both actions to make our streets safer and using data to analyze trends, is receiving significant attention nationwide and in the City of Albany. [https://visionzeronetwork.org/resources/vision-zero-communities/ Vision Zero] is the nationwide road and pedestrian safety organization that communities are rallying around, which includes [https://www.capitalregionvisionzero.org/ Capital District Vision Zero].

Nationwide, car-on-pedestrian crashes are more likely to cause serious injuries or fatalities than car-on-car accidents; pedestrian deaths are [https://www.cdc.gov/mmwr/volumes/74/wr/mm7408a2.htm growing at a faster rate] than overall traffic-related deaths. Yet car-on-pedestrian crashes get bundled into overall traffic safety reporting, and the volume, severity and visibility of pedestrian crashes get diluted in the discussion.

What is missing for us is the data, specifically data on pedestrian crashes - not just "traffic accidents" - within the City of Albany. We want to understand Albany’s pedestrian crash data - where it happens, when it happens, and what the trends are. Our goal is pretty simple - we want to demonstrate that pedestrian crash data is available and it should visibly inform the City of Albany’s planning, goal setting, analysis and communication about the progress that we are making.

We are also aware that the science and analysis of pedestrian safety is evolving. Writing this article we looked for research on the benefit of specific pedestrian safety infrastructure and programs. We communicated with several people involved in pedestrian safety research. From our point of view the linkage between pedestrian safety and the introduction of pedestrian safety measures can best be described as directional and/or early stage. For us this validates the need for the City to be using data to inform the actions that we take and to connect those actions to observable, objective benefits; or identify where our safety measures do not appear to be providing benefit.

Before we move to the analysis, a quick prefacing word. Our analysis may come across as dispassionate - reducing pedestrian crashes, injuries and deaths to numbers. We are well aware that behind these numbers are people - people who die, people who are injured, and families that are impacted by pedestrian crashes.

== The Data and Preliminary Analysis ==
We FOILed statewide pedestrian crash data from New York State DOT and received a file of over 75,000 car-on-pedestrian crashes statewide between January 1, 2020 and October 27, 2025.
[[File:InputData.png|none|thumb|500x500px|Pedestrian crash source data from New York Department of Transportation]]
Each crash record (image above) contains the data, time of day, injury and fatality information, reporting agency, and then other information on the conditions, circumstances and road network.

We extracted the 644 pedestrian crashes reported by the Albany Police Department over the time period to create our analysis dataset. While other law enforcement agencies (State Police, Campus Police, etc) reported pedestrian crashes within the City limits the numbers were not material or were associated with Interstate highway pedestrian crashes.

We mapped out every crash (below) and computed a few data points that we would use in our analysis:

* The name of the road where the crash happened
* The major road or minor road designation of the road where the crash happened
* The neighborhood where the crash happened
* Whether the crash happened in a school camera speed zone

[[File:OverviewMap.png|none|thumb|700x700px|Overview map of City of Albany Pedestrian Crashes, Jan 2020 to Oct 2025]]

== How Severe are the Crashes? ==
The DOT data collected by local law enforcement agencies contains three pieces of data on the severity of the pedestrian crash - how many people died, how many people sustained serious injuries, how many people sustained other injuries.
[[File:PedestrianCrashOutcome.png|none|thumb|400x400px|City of Albany Pedestrian Crash Outcomes]]
Our understanding of a “Serious Injury” is one where a person suffers dismemberment, fracture, loss of a fetus, permanent loss of a body organ, and/or any injury that limits a person’s ability to live normally for at least 90 days during the 180 days immediately following the crash. Any crash can have 0, 1 or more people who fall in each of the three categories.

For the 644 pedestrian crashes in the City of Albany between Jan 2020 and October 2025, 2% result in a fatality, 17% result in one or more serious injuries, 69% result in one or more other injuries, and 15% result in no injuries.

Note - percentages do not add to 100% - any crash can have more than one outcome. There are three streets where multiple fatality-producing crashes occurred: Washington Ave, Central Ave and Everett Road.

== What is the Overall Trend in Pedestrian Crashes? ==
Is the rate of pedestrian crashes increasing, decreasing or static? Prior to answering this question we can explain the time period that we chose to study. We stopped the trend study at the end of Q2 2025 (June 30th). While we have pedestrian crash data from NY State through late October 2025 we found that there is a latency in entering pedestrian crash data into the system. Each crash record lists the crash data and the date of data entry; typically there is a week or more delay, however many crashes take 90+ days to be entered into the system. We concluded that the Q3 (July-September) data was likely missing crash data due to this delay.

We can review crashes by quarter in a chart from Q1 2020 through Q2 2025. We also overlaid a trendline that uses a statistical method (polynomial) to show the overall trend.
[[File:CrashesByQuarter.png|none|thumb|700x700px|City of Albany, NY Quarterly trend in pedestrian crashes]]
Are pedestrian crashes going down? That is a tough question to answer with any certainty. A few bullet points capture our observations:

* The data from the first half of 2025 suggests improvement in pedestrian safety
* The pandemic likely, but not certainly, had some effect on minimizing traffic incidents in 2020 and 2021
* We do not know how the crash reporting processes may have changed, which may have caused over- or understatements for certain quarters
* Some of the large spikes and troughs may be just statistical chance

GIven those considerations, we would suggest two takeaways:

# the 2025 trend suggests improvement however 3-5 quarters of additional data are required before anyone can make broad claims of pedestrian safety improvement
# the pedestrian crash data, regardless of trend, demonstrates that there is a big gap to get to Vision Zero.

== Where do pedestrian crashes happen? ==
A quick point about our analysis before we describe where accidents happen. To determine the level (minor or major) of any given road we use DOT Arterial Classification Codes (ACC) associated with each road. A road gets an ACC based on its importance, usage, traffic volume, etc. In the map below ACC=3 (yellow), ACC=4 (purple), ACC=5 (red).
[[File:ACC AlbanyStreets.png|none|thumb|500x500px|Albany's streets displaying Arterial Classification Codes]]
In our analysis below we consider major roads to include ACC 3 & 4, and minor roads to be ACC 5. We linked each pedestrian crash to a road and determined if each crash was associated with a major road or a minor road. For a handful of crashes (13) we could not reliably determine the associated road.

* 486 pedestrian crashes (77%) occurred on '''Major Roads'''
* 145 pedestrian crashes (23%) occurred on '''Minor Roads'''

We can then analyze where pedestrian crashes happen, by street and by neighborhood.

The streets (by name) with more than 10 pedestrian crashes between 2020 and 2025:
{| class="wikitable sortable"
|+City of Albany, Crashes by Street
!Street
!Incident Count
!Percentage of Total Pedestrian Crashes
|-
|Central Avenue
| align="right" |83
| align="right" |13.2%
|-
|Washington Avenue
| align="right" |49
| align="right" |7.8%
|-
|Madison Avenue
| align="right" |47
| align="right" |7.5%
|-
|New Scotland Avenue
| align="right" |42
| align="right" |6.6%
|-
|Lark Street
| align="right" |28
| align="right" |4.4%
|-
|Delaware Avenue
| align="right" |24
| align="right" |3.8%
|-
|South Pearl Street
| align="right" |22
| align="right" |3.5%
|-
|Western Avenue
| align="right" |20
| align="right" |3.2%
|-
|Henry Johnson Boulevard
| align="right" |19
| align="right" |3.0%
|-
|Livingston Avenue
| align="right" |18
| align="right" |2.9%
|-
|Clinton Avenue
| align="right" |18
| align="right" |2.8%
|-
|Quail Street
| align="right" |11
| align="right" |1.8%
|-
|Morton Avenue
| align="right" |10
| align="right" |1.6%
|-
|Broadway
| align="right" |10
| align="right" |1.6%
|-
|North Allen Street
| align="right" |10
| align="right" |1.6%
|}
The neighborhoods with the most pedestrian crashes (more than 5% of overall pedestrian crashes) include these 6 neighborhoods:
{| class="wikitable sortable"
|+City of Albany, Crashes by Neighborhood
!Neighborhood
!Number of Pedestrian Crashes
!Percentage of Total Pedestrian Crashes
|-
|West Hill
| align="right" |84
| align="right" |13.3%
|-
|Pine Hills
| align="right" |70
| align="right" |11.1%
|-
|Central Avenue
| align="right" |53
| align="right" |8.4%
|-
|Arbor Hill
| align="right" |42
| align="right" |6.7%
|-
|Upper Washington Avenue
| align="right" |34
| align="right" |5.4%
|-
|Delaware Avenue
| align="right" |34
| align="right" |5.4%
|}
We reviewed the number of accidents that are within 200 yards of a school zone speed camera. (Map above). Between 2020 and October 2025 there were:

* 5 serious injuries in a school zone between the hours of 7am and 6pm, not including July and August. 2 serious injuries occurred in 2020 and 3 serious injuries occurred in 2023.
* 19 other injuries in a school zone between the hours of 7am and 6pm, not including July and August

[[File:SchoolZones.png|none|thumb|400x400px|Map of neighborhood school zones]]
We can use this historical data to understand the current and future pedestrian safety benefit of the school zone speed camera program.

Lastly, the pedestrian crash data identifies, for each crash, whether the accident occurred at an intersection or not at an intersection. The map below - the south end of Lark St near Madison Ave - shows pedestrian crashes at intersections using green circles, and pedestrian crashes that happened in-between intersections are identified with black squares.
[[File:Albany Intersection NonInts.png|none|thumb|400x400px|Map of pedestrian crashes at intersections and non-intersection crashes]]
Roughly 60% of pedestrian crashes occur at intersections, 40% in-between intersections. We doubt the value of ranking the “top 10 most dangerous intersections in Albany”, however we can note that intersections with the highest number of pedestrian crashes during the study period include Lark St & Washington Ave, New Scotland & Madison Ave, and Central Ave & Henry Johnson Blvd.

== When do Pedestrian Crashes Happen? ==
What insight could we find from understanding when - day vs. night, day of week - pedestrian crashes happen? The pedestrian crash data codes “Light conditions” in 5 categories - DAYLIGHT, DAWN, DUSK, DARK-ROAD LIGHTED, and DARK-ROAD UNLIGHTED. We created two categories for Day vs. Night, where Day consists of DAYLIGHT and DAWN, and Night consists of the other three categories. 63% of the City’s pedestrian crashes happen during the day, 37% at night.

We then plotted pedestrian crashes by day of week and day vs. night. We had some thoughts about when pedestrian crashes are most prevalent and none proved to be correct. We were extremely surprised by the day-to-day variability in overall pedestrian accidents, and the day-to-day consistency in night pedestrian crashes.
[[File:PedestrianCrashes DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Crashes by Day of Week, Night vs. Day]]
Similarly, we can examine when pedestrian deaths happen. Deaths generally track the day of week rate, with a much higher percentage of deaths happening at Night (72%).
[[File:PedestrianDeaths DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Deaths by Day of Week, Night vs Day]]
As we analyze when pedestrian deaths happen we can look at broader analysis. The National Safety Council’s [https://injuryfacts.nsc.org/motor-vehicle/road-users/pedestrians/ analysis of pedestrian crashes], states:

''“The largest number of pedestrian deaths occurs on Fridays (1,155), closely followed by Saturdays (1,150). Except for a decline on Sundays, the number of pedestrian deaths during daylight hours is relatively consistent throughout the week. However, pedestrian fatalities at night (during dark with or without artificial lighting) vary substantially. Nighttime pedestrian deaths are at their lowest point on Tuesday and peak on Saturday and Sunday.”''

These statements do and don’t align with the City of Albany’s pedestrian deaths, however this could be due to the low volume of pedestrian deaths on the City’s roads.

== How does Albany compare against Capital District cities? ==
We ran the same trend analysis for Troy and Schenectady - a quarterly analysis of pedestrian crashes for each city between 2020 and Q2 2025. While Troy and Schenectady have fewer pedestrian crashes we wanted to identify how each city’s trend compares. In the graph below the quarter-to-quarter pedestrian crash data and trends are in solid lines. The statistical trend for each city is shown with a dashed line.
[[File:PedestrianCrashes 3Cities.png|none|thumb|700x700px|Pedestrian crash comparison for Albany, Troy and Schenectady]]
Troy has seen a slight downturn in pedestrian crashes while Schenectady has shown a slight uptick. Both communities are a part of Capital Region Vision Zero, similar to the City of Albany. We have not examined if either Schenectady or Troy has been making the same investment in traffic calming measures as the City of Albany.

Our takeaway from the inter-city comparison is that this is an interesting data point for us to track. Within these three peers cities we can examine broad trends in pedestrian safety and the linkage between safety investment and awareness and reduction in pedestrian crashes.

== Summary ==
We picked a few of the many ways to examine the City of Albany’s pedestrian crashes since 2025. We wrote this article to highlight some of the data points that we are seeing from examining the pedestrian crash data.

We also want to ask our readers - what questions do you have that we can attempt to answer? If you have a question concerning pedestrian safety and crashes that you think we may be able to answer, drop us an email at [[MailTo:AlbanyDataStories@gmail.com|AlbanyDataStories@gmail.com]].

The City makes significant investments year-over-year in our streets and related safety. The City’s budget items that directly or indirectly support transportation safety in the 2026 proposed budget include:

* $1 million for traffic speed reduction measures
* $15 million for traffic signal improvements
* $14.5 million for street reconstruction
* $0.65 million for streetlight improvements
* $0.65 million for sidewalk reconstruction
* $0.4 million for roadway striping
* $0.3 million for traffic safety equipment

Net, the City invests over $30 million in road maintenance and improvements. Optimizing or directing this spending for traffic safety should be an important consideration. For example, the data could guide whether we should or shouldn't be installing speed humps on minor streets with no history of pedestrian crashes.

We can suggest a few outcomes from our analysis:

# New York must make pedestrian safety data and all other traffic crash data available to the public proactively, not requiring a FOIL
# The City of Albany should make all pedestrian and traffic safety analysis available on the City’s [https://data.albanyny.gov/ open data website]. Quoting statistics and studies must be accompanied by visibility of the analysis. For example, let’s see the data and analysis behind our opening quote from the 2026 budget “These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”
# Data should be used to analyze our new and improved infrastructure. If we have installed speed humps, pedestrian walkway improvements of various types, speed zone cameras and more, can we identify which improvements are or are not making a difference?
# Data should inform our goals. Our City should set targets or goals for the total number of pedestrian crashes, or related fatalities and serious injuries. As an illustrative example, in 2027 can we strive to have fewer than 70 pedestrian crashes and no fatalities?
# If we have data on our improvements to date (#3) and our goals (#4), can we use those data points to prioritize how and where we make improvements and additions to our infrastructure? Data should inform our $30 million of 2026 infrastructure spending.
# Let’s use the word “crash” rather than “accident” when we are talking about public safety. “Crash” conveys the tragic consequences of what are, in most cases, avoidable scenarios.

For further reading regarding the City’s pedestrian safety programs we suggest looking at:

* City of Albany [https://www.capitalmpo.org/wp-content/CRTC/images/linkage_program/AlbCoFinal/albanyCSPolicyandDesignManual_Final.pdf Complete Streets Design Guidelines]
* City of Albany [https://99a4b737-7711-4d6a-854e-2e74e07f3d6a.filesusr.com/ugd/b59736_f67b877056c54b5e9ce9754ae4fe4650.pdf Bicycle and Pedestrian Master Plan]

We have also posted the datasets that we received via FOIL in this Google Drive for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Data ==
For this article we FOILed pedestrian crash data from NY State Department of Transportation.

We have also posted the datasets that we received via FOIL in this [https://drive.google.com/drive/folders/1RUt4k5V_JT1OvGBzq6g1nFTrqwiANk4o Google Drive] for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

== Process ==
We added numerous fields to the data using QGIS. The details of these additional fields include:
{| class="wikitable"
!Field Name
!Field details
|-
|X
|Longitude value, WGS 84 - derived from UTMEasting
|-
|Y
|Latitude value, WGS 84 - derived from UTMNorthing
|-
|ACC_Intersection
|Arterial Class Code of the primary or most important road at the intersection, where the pedestrian crash is an intersection crash
<nowiki> </nowiki> Note that Arterial Class Code data - here and in other fields - comes from the NY State Street Network - <nowiki>https://gis.ny.gov/streets-addresses</nowiki>
|-
|ACC_Middle
|Arterial Class Code of the street associated with a non-intersection crash. Note that ACC values of 1-4 are considered "Major Roads" and ACC = 5-6 are considered "Minor Roads"
|-
|CrashStreetName
|The main street name associated with the crash regardless of intersection vs non-intersection crashes. This field is populated with StrtMid for non-intersection crashes. This field is populated with IntPriStNm for intersection crashes
|-
|StrtIntersection
|The street names of the roads that are associated with the intersection of the pedestrian crash. Note that the street names are in alphabetical order for standardization purposes.
|-
|StrtMiddle
|The name of the street associated with a non-intersection pedestrian crash
|-
|Neighborhood
|Where found, the neighborhood where the pedestrian crash happened. Neighborhood data derived from the Zillow neighborhoods file. <nowiki>https://www.arcgis.com/home/item.html?id=56b89613f9f7450fb44e857691a244e7</nowiki>
|-
|County
|The county where the pedestrian crash happened. County boundaries are from US Census Bureau TIGER data, 2025.
|-
|MajorMinor
|A determination if a pedestrian crash happened at a major or minor road or intersection. This MajMin value conflates information from ACC_MID and IntMajMin. If ACC_MID <=4 then it is major; the value of IntMajMin is moved over to this field for intersection pedestrian crashes
|-
|City
|The incorporated city or place where the pedestrian crash happened. Place boundaries are from US Census Bureau TIGER data, 2025.
|-
|Town
|The subdivision where the pedestrian crash happened. Subdivision boundaries are from US Census Bureau TIGER data, 2025.
|-
|IntersectionMajorMinor
|A determination if a pedestrian crash happened at a major or minor intersection. An intersection is deemed "Major" if one or both streets have an ACC value <= 4
|-
|IntersectionPrimaryStreet
|The primary street name at the intersection. Note that this is determined first by the street with the lower (more important) Arterial Class Code value; if streets share the same ACC then the street that is chose is the first alphabetically.
|}

== Credits ==
This data story and its content is available under the Creative Commons Attribution license.

Persons or organizations that Share or Adapt this content should provide Attribution that provides appropriate credit, which includes:

* © Copyright 2026
* Tyche Insights, P.B.C.
* [[User:KarlTyche|KarlTyche]] (Karl Urich)

For example, a data product or service that utilizes this article could include attribution such as:

"Portions derived from 'Albany NY Pedestrian Crash', © Copyright 2026 by Tyche Insights, P.B.C., KarlTyche (Karl Urich) & licensed under the CC BY 4.0 license"

Albany, New York Pedestrian Crash

2026-01-26T19:20:37Z

KarlTyche:

== Analyzing Pedestrian Crashes in Albany ==
[[File:CoreAlbany.png|none|thumb|600x600px|Pedestrian Crash Locations in Albany, NY]]
''“The annual number of crashes in the city has trended downward over the past three years. In 2022, there were 3,838 traffic crashes, with 575 involving some level of injury. Last year city police responded to 3,649 crashes, which included everything from minor scrapes and fender benders to head-on collisions, with 562 crashes involving some level of injury.”''

* “Albany sees traffic crashes drop with new speed limit”, Times Union, [https://www.timesunion.com/news/article/albany-sees-traffic-crashes-drop-new-25-mph-speed-20250081.php April 6, 2025]

''“This year we added more than 70 speed humps, implemented a new 25 MPH citywide speed limit, and completed installation of speed cameras across 20 school zones to enforce the existing 20 MPH speed limit where our younger residents learn every day. These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”''

* City of Albany [https://www.albanyny.gov/DocumentCenter/View/13182/2026-Proposed-Budget-PDF Proposed budget], p 6

Traffic safety, both actions to make our streets safer and using data to analyze trends, is receiving significant attention nationwide and in the City of Albany. [https://visionzeronetwork.org/resources/vision-zero-communities/ Vision Zero] is the nationwide road and pedestrian safety organization that communities are rallying around, which includes [https://www.capitalregionvisionzero.org/ Capital District Vision Zero].

Nationwide, car-on-pedestrian crashes are more likely to cause serious injuries or fatalities than car-on-car accidents; pedestrian deaths are [https://www.cdc.gov/mmwr/volumes/74/wr/mm7408a2.htm growing at a faster rate] than overall traffic-related deaths. Yet car-on-pedestrian crashes get bundled into overall traffic safety reporting, and the volume, severity and visibility of pedestrian crashes get diluted in the discussion.

What is missing for us is the data, specifically data on pedestrian crashes - not just "traffic accidents" - within the City of Albany. We want to understand Albany’s pedestrian crash data - where it happens, when it happens, and what the trends are. Our goal is pretty simple - we want to demonstrate that pedestrian crash data is available and it should visibly inform the City of Albany’s planning, goal setting, analysis and communication about the progress that we are making.

We are also aware that the science and analysis of pedestrian safety is evolving. Writing this article we looked for research on the benefit of specific pedestrian safety infrastructure and programs. We communicated with several people involved in pedestrian safety research. From our point of view the linkage between pedestrian safety and the introduction of pedestrian safety measures can best be described as directional and/or early stage. For us this validates the need for the City to be using data to inform the actions that we take and to connect those actions to observable, objective benefits; or identify where our safety measures do not appear to be providing benefit.

Before we move to the analysis, a quick prefacing word. Our analysis may come across as dispassionate - reducing pedestrian crashes, injuries and deaths to numbers. We are well aware that behind these numbers are people - people who die, people who are injured, and families that are impacted by pedestrian crashes.

== The Data and Preliminary Analysis ==
We FOILed statewide pedestrian crash data from New York State DOT and received a file of over 75,000 car-on-pedestrian crashes statewide between January 1, 2020 and October 27, 2025.
[[File:InputData.png|none|thumb|500x500px|Pedestrian crash source data from New York Department of Transportation]]
Each crash record (image above) contains the data, time of day, injury and fatality information, reporting agency, and then other information on the conditions, circumstances and road network.

We extracted the 644 pedestrian crashes reported by the Albany Police Department over the time period to create our analysis dataset. While other law enforcement agencies (State Police, Campus Police, etc) reported pedestrian crashes within the City limits the numbers were not material or were associated with Interstate highway pedestrian crashes.

We mapped out every crash (below) and computed a few data points that we would use in our analysis:

* The name of the road where the crash happened
* The major road or minor road designation of the road where the crash happened
* The neighborhood where the crash happened
* Whether the crash happened in a school camera speed zone

[[File:OverviewMap.png|none|thumb|700x700px|Overview map of City of Albany Pedestrian Crashes, Jan 2020 to Oct 2025]]

== How Severe are the Crashes? ==
The DOT data collected by local law enforcement agencies contains three pieces of data on the severity of the pedestrian crash - how many people died, how many people sustained serious injuries, how many people sustained other injuries.
[[File:PedestrianCrashOutcome.png|none|thumb|400x400px|City of Albany Pedestrian Crash Outcomes]]
Our understanding of a “Serious Injury” is one where a person suffers dismemberment, fracture, loss of a fetus, permanent loss of a body organ, and/or any injury that limits a person’s ability to live normally for at least 90 days during the 180 days immediately following the crash. Any crash can have 0, 1 or more people who fall in each of the three categories.

For the 644 pedestrian crashes in the City of Albany between Jan 2020 and October 2025, 2% result in a fatality, 17% result in one or more serious injuries, 69% result in one or more other injuries, and 15% result in no injuries.

Note - percentages do not add to 100% - any crash can have more than one outcome. There are three streets where multiple fatality-producing crashes occurred: Washington Ave, Central Ave and Everett Road.

== What is the Overall Trend in Pedestrian Crashes? ==
Is the rate of pedestrian crashes increasing, decreasing or static? Prior to answering this question we can explain the time period that we chose to study. We stopped the trend study at the end of Q2 2025 (June 30th). While we have pedestrian crash data from NY State through late October 2025 we found that there is a latency in entering pedestrian crash data into the system. Each crash record lists the crash data and the date of data entry; typically there is a week or more delay, however many crashes take 90+ days to be entered into the system. We concluded that the Q3 (July-September) data was likely missing crash data due to this delay.

We can review crashes by quarter in a chart from Q1 2020 through Q2 2025. We also overlaid a trendline that uses a statistical method (polynomial) to show the overall trend.
[[File:CrashesByQuarter.png|none|thumb|700x700px|City of Albany, NY Quarterly trend in pedestrian crashes]]
Are pedestrian crashes going down? That is a tough question to answer with any certainty. A few bullet points capture our observations:

* The data from the first half of 2025 suggests improvement in pedestrian safety
* The pandemic likely, but not certainly, had some effect on minimizing traffic incidents in 2020 and 2021
* We do not know how the crash reporting processes may have changed, which may have caused over- or understatements for certain quarters
* Some of the large spikes and troughs may be just statistical chance

GIven those considerations, we would suggest two takeaways:

# the 2025 trend suggests improvement however 3-5 quarters of additional data are required before anyone can make broad claims of pedestrian safety improvement
# the pedestrian crash data, regardless of trend, demonstrates that there is a big gap to get to Vision Zero.

== Where do pedestrian crashes happen? ==
A quick point about our analysis before we describe where accidents happen. To determine the level (minor or major) of any given road we use DOT Arterial Classification Codes (ACC) associated with each road. A road gets an ACC based on its importance, usage, traffic volume, etc. In the map below ACC=3 (yellow), ACC=4 (purple), ACC=5 (red).
[[File:ACC AlbanyStreets.png|none|thumb|500x500px|Albany's streets displaying Arterial Classification Codes]]
In our analysis below we consider major roads to include ACC 3 & 4, and minor roads to be ACC 5. We linked each pedestrian crash to a road and determined if each crash was associated with a major road or a minor road. For a handful of crashes (13) we could not reliably determine the associated road.

* 486 pedestrian crashes (77%) occurred on '''Major Roads'''
* 145 pedestrian crashes (23%) occurred on '''Minor Roads'''

We can then analyze where pedestrian crashes happen, by street and by neighborhood.

The streets (by name) with more than 10 pedestrian crashes between 2020 and 2025:
{| class="wikitable sortable"
|+City of Albany, Crashes by Street
!Street
!Incident Count
!Percentage of Total Pedestrian Crashes
|-
|Central Avenue
| align="right" |83
| align="right" |13.2%
|-
|Washington Avenue
| align="right" |49
| align="right" |7.8%
|-
|Madison Avenue
| align="right" |47
| align="right" |7.5%
|-
|New Scotland Avenue
| align="right" |42
| align="right" |6.6%
|-
|Lark Street
| align="right" |28
| align="right" |4.4%
|-
|Delaware Avenue
| align="right" |24
| align="right" |3.8%
|-
|South Pearl Street
| align="right" |22
| align="right" |3.5%
|-
|Western Avenue
| align="right" |20
| align="right" |3.2%
|-
|Henry Johnson Boulevard
| align="right" |19
| align="right" |3.0%
|-
|Livingston Avenue
| align="right" |18
| align="right" |2.9%
|-
|Clinton Avenue
| align="right" |18
| align="right" |2.8%
|-
|Quail Street
| align="right" |11
| align="right" |1.8%
|-
|Morton Avenue
| align="right" |10
| align="right" |1.6%
|-
|Broadway
| align="right" |10
| align="right" |1.6%
|-
|North Allen Street
| align="right" |10
| align="right" |1.6%
|}
The neighborhoods with the most pedestrian crashes (more than 5% of overall pedestrian crashes) include these 6 neighborhoods:
{| class="wikitable sortable"
|+City of Albany, Crashes by Neighborhood
!Neighborhood
!Number of Pedestrian Crashes
!Percentage of Total Pedestrian Crashes
|-
|West Hill
| align="right" |84
| align="right" |13.3%
|-
|Pine Hills
| align="right" |70
| align="right" |11.1%
|-
|Central Avenue
| align="right" |53
| align="right" |8.4%
|-
|Arbor Hill
| align="right" |42
| align="right" |6.7%
|-
|Upper Washington Avenue
| align="right" |34
| align="right" |5.4%
|-
|Delaware Avenue
| align="right" |34
| align="right" |5.4%
|}
We reviewed the number of accidents that are within 200 yards of a school zone speed camera. (Map above). Between 2020 and October 2025 there were:

* 5 serious injuries in a school zone between the hours of 7am and 6pm, not including July and August. 2 serious injuries occurred in 2020 and 3 serious injuries occurred in 2023.
* 19 other injuries in a school zone between the hours of 7am and 6pm, not including July and August

[[File:SchoolZones.png|none|thumb|400x400px|Map of neighborhood school zones]]
We can use this historical data to understand the current and future pedestrian safety benefit of the school zone speed camera program.

Lastly, the pedestrian crash data identifies, for each crash, whether the accident occurred at an intersection or not at an intersection. The map below - the south end of Lark St near Madison Ave - shows pedestrian crashes at intersections using green circles, and pedestrian crashes that happened in-between intersections are identified with black squares.
[[File:Albany Intersection NonInts.png|none|thumb|400x400px|Map of pedestrian crashes at intersections and non-intersection crashes]]
Roughly 60% of pedestrian crashes occur at intersections, 40% in-between intersections. We doubt the value of ranking the “top 10 most dangerous intersections in Albany”, however we can note that intersections with the highest number of pedestrian crashes during the study period include Lark St & Washington Ave, New Scotland & Madison Ave, and Central Ave & Henry Johnson Blvd.

== When do Pedestrian Crashes Happen? ==
What insight could we find from understanding when - day vs. night, day of week - pedestrian crashes happen? The pedestrian crash data codes “Light conditions” in 5 categories - DAYLIGHT, DAWN, DUSK, DARK-ROAD LIGHTED, and DARK-ROAD UNLIGHTED. We created two categories for Day vs. Night, where Day consists of DAYLIGHT and DAWN, and Night consists of the other three categories. 63% of the City’s pedestrian crashes happen during the day, 37% at night.

We then plotted pedestrian crashes by day of week and day vs. night. We had some thoughts about when pedestrian crashes are most prevalent and none proved to be correct. We were extremely surprised by the day-to-day variability in overall pedestrian accidents, and the day-to-day consistency in night pedestrian crashes.
[[File:PedestrianCrashes DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Crashes by Day of Week, Night vs. Day]]
Similarly, we can examine when pedestrian deaths happen. Deaths generally track the day of week rate, with a much higher percentage of deaths happening at Night (72%).
[[File:PedestrianDeaths DayofWeek.png|none|thumb|650x650px|City of Albany Pedestrian Deaths by Day of Week, Night vs Day]]
As we analyze when pedestrian deaths happen we can look at broader analysis. The National Safety Council’s [https://injuryfacts.nsc.org/motor-vehicle/road-users/pedestrians/ analysis of pedestrian crashes], states:

''“The largest number of pedestrian deaths occurs on Fridays (1,155), closely followed by Saturdays (1,150). Except for a decline on Sundays, the number of pedestrian deaths during daylight hours is relatively consistent throughout the week. However, pedestrian fatalities at night (during dark with or without artificial lighting) vary substantially. Nighttime pedestrian deaths are at their lowest point on Tuesday and peak on Saturday and Sunday.”''

These statements do and don’t align with the City of Albany’s pedestrian deaths, however this could be due to the low volume of pedestrian deaths on the City’s roads.

== How does Albany compare against Capital District cities? ==
We ran the same trend analysis for Troy and Schenectady - a quarterly analysis of pedestrian crashes for each city between 2020 and Q2 2025. While Troy and Schenectady have fewer pedestrian crashes we wanted to identify how each city’s trend compares. In the graph below the quarter-to-quarter pedestrian crash data and trends are in solid lines. The statistical trend for each city is shown with a dashed line.
[[File:PedestrianCrashes 3Cities.png|none|thumb|700x700px|Pedestrian crash comparison for Albany, Troy and Schenectady]]
Troy has seen a slight downturn in pedestrian crashes while Schenectady has shown a slight uptick. Both communities are a part of Capital Region Vision Zero, similar to the City of Albany. We have not examined if either Schenectady or Troy has been making the same investment in traffic calming measures as the City of Albany.

Our takeaway from the inter-city comparison is that this is an interesting data point for us to track. Within these three peers cities we can examine broad trends in pedestrian safety and the linkage between safety investment and awareness and reduction in pedestrian crashes.

== Summary ==
We picked a few of the many ways to examine the City of Albany’s pedestrian crashes since 2025. We wrote this article to highlight some of the data points that we are seeing from examining the pedestrian crash data.

We also want to ask our readers - what questions do you have that we can attempt to answer? If you have a question concerning pedestrian safety and crashes that you think we may be able to answer, drop us an email at [[MailTo:AlbanyDataStories@gmail.com|AlbanyDataStories@gmail.com]].

The City makes significant investments year-over-year in our streets and related safety. The City’s budget items that directly or indirectly support transportation safety in the 2026 proposed budget include:

* $1 million for traffic speed reduction measures
* $15 million for traffic signal improvements
* $14.5 million for street reconstruction
* $0.65 million for streetlight improvements
* $0.65 million for sidewalk reconstruction
* $0.4 million for roadway striping
* $0.3 million for traffic safety equipment

Net, the City invests over $30 million in road maintenance and improvements. Optimizing or directing this spending for traffic safety should be an important consideration. For example, the data could guide whether we should or shouldn't be installing speed humps on minor streets with no history of pedestrian crashes.

We can suggest a few outcomes from our analysis:

# New York must make pedestrian safety data and all other traffic crash data available to the public proactively, not requiring a FOIL
# The City of Albany should make all pedestrian and traffic safety analysis available on the City’s [https://data.albanyny.gov/ open data website]. Quoting statistics and studies must be accompanied by visibility of the analysis. For example, let’s see the data and analysis behind our opening quote from the 2026 budget “These changes have already helped reduce traffic accidents by 40% and accidents with injuries by 50%”
# Data should be used to analyze our new and improved infrastructure. If we have installed speed humps, pedestrian walkway improvements of various types, speed zone cameras and more, can we identify which improvements are or are not making a difference?
# Data should inform our goals. Our City should set targets or goals for the total number of pedestrian crashes, or related fatalities and serious injuries. As an illustrative example, in 2027 can we strive to have fewer than 70 pedestrian crashes and no fatalities?
# If we have data on our improvements to date (#3) and our goals (#4), can we use those data points to prioritize how and where we make improvements and additions to our infrastructure? Data should inform our $30 million of 2026 infrastructure spending.
# Let’s use the word “crash” rather than “accident” when we are talking about public safety. “Crash” conveys the tragic consequences of what are, in most cases, avoidable scenarios.

For further reading regarding the City’s pedestrian safety programs we suggest looking at:

* City of Albany [https://www.capitalmpo.org/wp-content/CRTC/images/linkage_program/AlbCoFinal/albanyCSPolicyandDesignManual_Final.pdf Complete Streets Design Guidelines]
* City of Albany [https://99a4b737-7711-4d6a-854e-2e74e07f3d6a.filesusr.com/ugd/b59736_f67b877056c54b5e9ce9754ae4fe4650.pdf Bicycle and Pedestrian Master Plan]

We have also posted the datasets that we received via FOIL in this Google Drive for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

We have also posted the datasets that we received via FOIL in this [https://drive.google.com/drive/folders/1RUt4k5V_JT1OvGBzq6g1nFTrqwiANk4o Google Drive] for anyone to download. This folder contains statewide datasets of pedestrian and bicycle accidents and a documentation pdf (which has a lot of inaccuracies but it’s a starting point for understanding the data).

File:PedestrianCrashes 3Cities.png

2026-01-26T19:18:01Z

KarlTyche:

Pedestrian crash comparison for Albany, Troy and Schenectady

File:PedestrianDeaths DayofWeek.png

2026-01-26T19:16:08Z

KarlTyche:

City of Albany Pedestrian Deaths by Day of Week, Night vs Day

File:PedestrianCrashes DayofWeek.png

2026-01-26T19:15:18Z

KarlTyche:

City of Albany Pedestrian Crashes by Day of Week, Night vs. Day

File:Albany Intersection NonInts.png

2026-01-26T19:14:07Z

KarlTyche:

Map of pedestrian crashes at intersections and non-intersection crashes

File:SchoolZones.png

2026-01-26T19:13:02Z

KarlTyche:

Map of neighborhood school zones

File:ACC AlbanyStreets.png

2026-01-26T19:09:13Z

KarlTyche:

Albany's streets displaying Arterial Classification Codes

File:CrashesByQuarter.png

2026-01-26T19:07:10Z

KarlTyche:

City of Albany, NY Quarterly trend in pedestrian crashes

File:PedestrianCrashOutcome.png

2026-01-26T19:05:43Z

KarlTyche:

City of Albany Pedestrian Crash Outcomes

Albany, New York Pedestrian Crash

2026-01-26T19:03:39Z

KarlTyche: Created initial page and began populating it with existing article, moved over from Albany Data Stories

File:OverviewMap.png

2026-01-26T19:02:32Z

KarlTyche:

Overview map of City of Albany Pedestrian Crashes, Jan 2020 to Oct 2025

File:InputData.png

2026-01-26T19:01:23Z

KarlTyche:

Pedestrian crash source data from New York Department of Transportation

File:CoreAlbany.png

2026-01-26T18:54:17Z

KarlTyche:

Pedestrian Crash Locations in Albany, NY

Main Page

2026-01-15T16:18:58Z

KarlTyche: /* Opinions and News */ added "what we learned from our Albany test"

<big>'''''Unbiased data storytelling and data journalism using public, government data - by citizens, for citizens.'''''</big>[[File:Data Story Collage.png|none|thumb|950x950px]]
== About Tyche Insights ==

* What is a [[TycheAbout:WhatIsADataStory|Data Story]]?
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== Search for data stories & data journalism ==
As we launch Tyche Insights we begin with a set of content that we have populated for [[:Category:Albany NY|Albany, New York]]. These are stories that analyze the [[:Category:Albany NY|City of Albany]]'s housing, crime, population, taxes, state funding and more. To understand the types of stories that you will see over time (and potentially to give you some ideas on data stories that you can write!), search using terms such as "Albany", "Crime", "Finance" and more.

We also have the concept of a "[[Hub:Albany Data Stories|Hub]]" where a group is focused on a broader storytelling effort.

== Featured data story ==
[[File:TownofColonie GTTR.png|thumb|200x200px|A Finance Decoder chart for Colonie, NY ]]

=== Our first Finance Decoders from the Hudson Finance Decoder Project ===
We started the Hudson Finance Decoder Project to help anyone, anywhere create a Finance Decoder. We [[TycheNews:FirstFinanceDecoders|posted an article]] describing the first Finance Decoders that have been created and posted. We now have stories that examine local government finances for cities such as Gainesville, FL and Pueblo, CO, and counties like Washoe County, NV.

See our list of prior [[FeaturedDataStories|Featured Stories]].

== Opinions and News ==

* [[TycheOpEd:OpenDataFlywheel|The Open Data Flywheel]] - December 18, 2025
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== Join us, follow us, talk to us ==
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[[File:HFDP Overview.png|thumb|400x400px]]
We're excited to support our first group data storytelling project - the [https://hudsonfinancedecoder.com/ Hudson Finance Decoder Project]. The purpose of this project is "Citizens working together to analyze the financial health of their cities, towns and counties across the USA and Canada." We will support anyone, anywhere who wants to create a Strong Towns Finance Decoder for their community, and then to turn that Finance Deocoder into a data story, [[Albany, New York Financial State|like we did for Albany, NY]].

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