ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · SEPTEMBER 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/chicopee/september-2025-report
Monthly Traffic Safety Analysis
141 CRASHES IN
CHICOPEE, MA
SEPTEMBER 2025
In September 2025, Chicopee experienced 141 total crashes, a 2.9% increase from the 137 crashes recorded in September 2024. While total crashes saw a slight rise, total injuries decreased by 18.75%, from 48 to 39. Notably, hit-and-run crashes increased by 46.7%, rising from 15 to 22 incidents year-over-year.
141
▲ 2.9%was 137
Total Crash Events
0
Persons Killed
39
▼ -18.8%was 48
Persons Injured
22
▲ 46.7%was 15
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash frequency saw a slight upward trend, with total crashes increasing by 2.9% from 137 in September 2024 to 141 in September 2025. However, total injuries decreased by 18.75%, falling from 48 to 39 over the same period, indicating a positive trend in injury outcomes despite more crashes.
22
Hit-and-Run Crashes — September 2025
▲ 46.7% vs prior (15)
Hit-and-run crashes increased by 46.7% year-over-year, rising from 15 incidents in September 2024 to 22 in September 2025. The hit-and-run rate also climbed from 10.9% to 15.6% of all crashes, indicating an upward trend.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
37
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak day for crashes shifted from Thursday (24 crashes) in September 2024 to both Tuesday and Wednesday (24 crashes each) in September 2025. The peak hour for crashes moved from 2 p.m. (19 crashes) in September 2024 to 4 p.m. (16 crashes) in September 2025. Monday saw the largest increase in crashes, rising by 8 from 15 to 23.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
No fatal crashes were reported in either September 2024 or September 2025. Total injuries decreased by 18.75%, from 48 to 39, year-over-year. Specifically, serious injuries decreased by 40%, from 5 to 3, and possible injuries decreased by 50%, from 8 to 4.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Most severe injury per crash record
Top Contributing Factors
The number of crashes attributed to 'Inattention' rose significantly by 85.7%, from 14 in September 2024 to 26 in September 2025, becoming the second most frequent contributing factor. Conversely, crashes due to 'Other improper action' decreased by 53.3%, from 15 to 7. Crashes involving 'Exceeded authorized speed limit' and 'Distracted' both increased by 200%, from 1 to 3 incidents each.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring on wet road surfaces increased substantially by 185.7%, from 7 incidents in September 2024 to 20 in September 2025. The number of crashes in 'Clear' weather decreased by 20 incidents, from 97 to 77, while crashes during 'Rain' increased by 100%, from 3 to 6. The proportion of crashes occurring in daylight also increased, rising from 101 to 109 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased slightly from 264 to 269. The top vehicle make involved shifted, with Toyota rising to the most frequent (35 vehicles) from 30, while Honda decreased from 39 to 29. Notably, persons in the 0-15 age group involved in crashes increased by 65.2%, from 23 to 38, and those 65+ increased by 43.6%, from 39 to 56.
Top Vehicle Makes (269 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Vehicle unit records
41 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (318 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 65 mph speed zones saw a 150% increase, rising from 4 incidents in September 2024 to 10 in September 2025. Crashes in 35 mph zones also increased by 60%, from 15 to 24. There were no fatal crashes reported in any speed limit zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-09-01 to 2025-09-30 · Posted speed limit at crash location
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Massachusetts Crash Data (MassDOT CDV), accessed programmatically via the Arcgis_yearly Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.
Data Retrieval
- Access method: Arcgis_yearly Open Data API (SoQL queries)
- Data format: Structured JSON via REST API
- Record types queried: Crash events, person records, and vehicle unit records
- Date filter applied: 2025-09-01 through 2025-09-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-09-01 through 2025-09-30 (30 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 141
- Total persons involved: 361
- Total vehicles involved: 269
Analytical Methodology
- Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
- Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
- Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
- Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
- Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
- Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
- AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.
Limitations & Disclaimers
- Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
- Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
- Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
- AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
- Percentages are calculated from reported data and are subject to rounding.
Non-Affiliation Disclosure
This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.
Data License
The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.
Corrections & Feedback
If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.
Suggested Citation
ThatCarHitMe.com (Injuria.ai). "CHICOPEE, MA Crash Intelligence Report: September 2025." Published June 21, 2026. Reporting period: 2025-09-01 to 2025-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/september-2025-report
About the Publisher
ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.
Questions about this report's data or methodology: data@injuria.ai
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-09-01 – 2025-09-30
Generated: June 21, 2026 · All rights reserved