ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · 2024
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/2024-annual-report
Yearly Traffic Safety Analysis
1,641 CRASHES IN
CHICOPEE, MA
2024
In 2024, Chicopee recorded 1,641 total crashes, a 9.7% decrease from the 1,818 crashes reported in 2023. This year-over-year comparison shows a notable reduction in total collisions and related outcomes. The most significant change was a 37.5% decrease in total fatalities, which fell from 8 in 2023 to 5 in 2024.
1,641
▼ -9.7%was 1,818
Total Crash Events
5
▼ -37.5%was 8
Persons Killed
500
▼ -10.9%was 561
Persons Injured
250
▼ -17.8%was 304
Hit-and-Run Crashes
Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 73 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends in Chicopee show a decrease between 2023 and 2024. Total crashes fell by 9.7%, from 1,818 to 1,641. Similarly, total injuries decreased by 10.9% from 561 to 500, and total fatalities dropped by 37.5% from 8 to 5.
250
Hit-and-Run Crashes — 2024
▼ -17.8% vs prior (304)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The number of hit-and-run crashes fell by 17.8% from 304 in 2023 to 250 in 2024. The hit-and-run rate also trended downward, declining from 16.7% of all crashes in the prior year to 15.2% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
0
Other Killed
15
Pedestrians Injured
5
Cyclists Injured
477
Motorists Injured
3
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes remained largely consistent year-over-year. Friday was the peak day for crashes in both 2024 (266 crashes) and 2023 (308 crashes). The peak hour for collisions also remained the same, occurring at 4 p.m. in both periods, with 173 crashes in 2024 and 165 in 2023. While the overall number of crashes decreased, the daily and hourly peaks did not shift.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes shifted slightly towards less severe outcomes in 2024. The rate of fatal crashes remained stable at 0.3% of all crashes in both 2023 and 2024. However, the proportion of crashes resulting in any level of injury decreased from 23.0% in 2023 to 21.7% in 2024. Correspondingly, the share of crashes with no reported injuries increased from 71.9% to 73.6%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes remained consistent between the two periods, though their counts changed. 'Inattention' remained the most cited driver-related factor, but its count decreased by 21.2% from 273 incidents in 2023 to 215 in 2024. Crashes attributed to 'Followed too closely' also saw a 13.3% decrease in count, from 188 to 163. Conversely, crashes involving 'Failed to yield right of way' increased in count from 167 to 174, moving it from the fourth to the third most common factor.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The environmental conditions under which crashes occurred saw little change year-over-year. In both 2024 and 2023, the vast majority of crashes happened during daylight (69.3% and 69.5% of crashes, respectively) and on dry road surfaces (78.3% and 79.6%, respectively). The proportion of crashes occurring in adverse weather like rain or on wet roads also remained stable between the two periods, indicating no significant shift in condition-related crash patterns.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The makes of vehicles involved in crashes showed a stable pattern, with Honda, Toyota, and Ford remaining the top three most common makes in both 2023 and 2024. However, the age demographics of persons involved in crashes shifted. The proportion of individuals aged 35 and older involved in crashes increased, while the share for those under 35 decreased. For example, the 35-44 age group's share of persons involved rose from 14.4% to 15.2%, and the 65+ group's share grew from 9.3% to 10.2%.
Top Vehicle Makes (3,123 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
558 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (3,346 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained consistent, with approximately 60% of all collisions in both 2023 and 2024 occurring in 25 mph and 30 mph zones. However, the profile of fatal crashes by speed zone shifted. In 2023, fatal crashes were recorded in zones up to 65 mph. In contrast, all 5 fatal crashes in 2024 occurred in zones of 40 mph or less, with two of these occurring in a 40 mph zone.
Fatal crashes by zone: 25 mph: 1 of 532 (0.188%) · 30 mph: 1 of 439 (0.228%) · 35 mph: 1 of 176 (0.568%) · 40 mph: 2 of 76 (2.632%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 1,641
- Total persons involved: 3,965
- Total vehicles involved: 3,123
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved