An Independent Look at Albany Crime Data: Part 2

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Note - This is the second of a multi-part article on Albany's Crime.  In Part 1, we focused on the overall crime trends in Albany. Part 2 of this series focuses on OUTSIDE crime throughout Albany. Part 3 will look at INSIDE crimes at domestic locations and businesses.

In our analysis below, we come to several directional statements:

1. The highest density of reported crimes that were categorized as OUTSIDE occurs along the Central Ave corridor from Lark St to Partridge St, extending SW along Washington Ave and NE along Clinton Ave.  Areas around South Pearl and the Delaware and Second Ave/Whitehall intersection also stood out.

2. Separating crimes under the THEFT and VIOLENCE categories shows that crimes tend to fall under the THEFT category as crime density decreases.

3.  THEFT crimes were further split into crimes related to CARS and NOT CARS, which showed these were the most common crimes in areas where crime density was low.

4. The HOT and COLD months have different crime trends, however they seem to show that the rate of occurrence differs, but not the location. 

In our article below we will show maps that highlight areas with high and low crime.  Importantly, we can say what we are NOT trying to do with these maps - we're not trying to marginalize, deride or shame any particular neighborhood.  What we DO believe is that highlighting where crime does and doesn't happen is an important step towards developing policies that make streets safer for everyone. 

In Part 1, we analyzed the 78,094 incidents reported between Jan. 1st, 2020, through Mar. 8th, 2025, and whittled them down by first eliminating incidents labeled as NO CRIME and ALL OTHER. We grouped the crime data by month, and a pattern emerged that showed a cyclical increase of crime during summer months. This led us to further filter the crime data by location type, grouping several of these into a broad category to cover crimes occurring OUTSIDE. 

As a reminder, every incident comes with a Location Type.  The following Location Types were collectively classified as OUTSIDE -  STREET, PARKING LOT, YARD, OTHER OUTSIDE LOCATION, GAS STATION, AUTO SALES LOT, FIELD WOODS, CONSTRUCTION SITE, PARK PLAYGROUND, LAKE WATERWAY, CEMETERY.

Part 1 concluded by showing an increase in VIOLENCE occurring during warmer months and a drop in colder months. As a reminder, heading into this story, OUTSIDE crimes listed under UNIFORM CRIME REPORT were split into three categories - THEFT, VIOLENCE, and OTHER (consisting of all remaining crimes without a clear distinction between theft or violence). 

We found that our division of crimes was mostly inline with the grouping the FBI uses to denote these crimes, except the FBI's labelings are Crimes Against Persons, Crimes Against Property, and Crimes Against Society instead of VIOLENCE, THEFT, and OTHER, respectively. We’ve decided to update our terminology to PERSONS, PROPERTY, and SOCIETY to be more consistent with the FBI’s UCR.  

Note - COERCION and ARSON were placed in PERSONS and PROPERTY respectively to be more consistent with the FBI's UCR.

We introduced a new dimension to our analysis, we geocoded or mapped crime locations using the values from HUNDRED BLOCK.  From there, we were able to place crimes in different neighborhoods throughout Albany.  The first thing we checked was the total number of crimes for each neighborhood. Below is the breakdown listing the total number of crimes, number of Larcenies (sum of LARCENY and MV LARCENY), CRIMINAL MISCHIEF, and assaults (sum of SIMPLE ASSAULT and AGGRAVATED ASSAULT). 

Note that we are using neighborhood boundaries derived from a dataset created by Zillow. This dataset was originally incomplete and did not cover the complete surface of Albany, so we added a few definitions for several missing neighborhoods. We also want to remind everyone that, while some neighborhoods may show more crimes than others, no other factor was considered, such as neighborhood size, population density, estimates on housing prices, property taxes, etc.

In our maps below we will focus on three areas of the city.  To avoid ambiguity we are calling these mapping areas:

"Central Albany" - the area around Washington Park and north

"Southern Albany" - the area around Lincoln Park and south

"Western Albany" - the area west of Main St

We also want to thank everyone who reached out and provided tips, hints, and constructive criticism via email, Reddit and other channels on Part 1 of our story.  

To elaborate on a few questions and comments we received: 

• We were informed that incidents marked as NO CRIME cover a broad range of things.  These can be anything from someone wanting to bring something to the attention of APD to capturing an event resulting in an injury to an officer.
• We received a question about what MISC includes.  MISC includes - Fraud (642), Rape (356), Sex Offence (286), Unauthorized Use (205), Controlled Substances (166), Stolen Property (139), Kidnapping (87), Murder (84), Forgery (78), Arson (68), Disorderly Conduct (37), GCO (35), Extortion (33), DWI (18), Offenses Against Public Order (8), Offenses Against Family (7), Embezzlement (3), Coercion (2), Prostitution (1), Poss of Burglary Tools (1), Gambling (1)
• We haven’t had time to pull in additional data, i.e., employment rate, active duty police officers, etc. These are items we are considering in future studies involving crime data. For now, we’re concentrating on mining the single source of data to showcase the value contained in the dataset. We are interested in bringing in additional datasets, but we want to be very selective in the ones we bring in and make sure that we capture as much detail as possible. For example, in addition to the total number of active duty police officers, we’d likely want to know the distribution of their years of service, the precinct they are assigned to.

We are still working with the same data Jan 1st, 2020 - March 2025, and have not had an opportunity to request data before 2020. This is something we are discussing.  Finally, we have included a link at the bottom of this article to the source data.  We’re excited to share this with you, and all we’re asking is that if you use the data, please provide a link back to Albany Data Stories.  If you’re interested in writing an article of your own using this and other data, please reach out at albanydatastories@gmail.com.