ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · DECEMBER 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/december-2025-report
Monthly Traffic Safety Analysis
133 CRASHES IN
CHICOPEE, MA
DECEMBER 2025
In December 2025, CHICOPEE experienced 133 total crashes, an increase of 13.68% compared to the 117 crashes recorded in December 2024. A significant shift was observed in fatalities, which decreased from 1 in the prior period to 0 in the current period, representing a 100% reduction.
133
▲ 13.7%was 117
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
39
▲ 8.3%was 36
Persons Injured
22
▲ 15.8%was 19
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. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash incidents in CHICOPEE showed an upward trend, with total crashes increasing from 117 in December 2024 to 133 in December 2025. This represents a 13.68% rise in the number of crashes year-over-year. Despite the increase in total crashes, fatalities decreased from 1 to 0, while total injuries rose from 36 to 39, an 8.3% increase.
22
Hit-and-Run Crashes — December 2025
▲ 15.8% vs prior (19)
Hit-and-run crashes increased from 19 incidents in December 2024 to 22 incidents in December 2025. Concurrently, the hit-and-run rate saw a slight increase, rising from 16.2% to 16.5%. This indicates a minor upward trend in both the absolute number and the proportion of hit-and-run incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Pedestrians Injured
1
Cyclists Injured
35
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal patterns shifted year-over-year; while the peak crash hour remained 5 p.m. for both periods, the peak count slightly decreased from 17 to 16 crashes. The peak day of the week for crashes shifted from Thursday in December 2024 (25 crashes) to Monday and Saturday in December 2025, both recording 25 crashes. Notably, crashes on Monday increased from 21 to 25, and Saturday crashes increased from 16 to 25, while Thursday crashes decreased from 25 to 18.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution saw notable changes, with total fatalities decreasing by 100% from 1 in December 2024 to 0 in December 2025. Conversely, total injuries increased by 8.3%, from 36 to 39. Serious injuries (severity 'A') increased from 0 in the prior period to 3 in the current period, while minor injuries (severity 'B') rose from 15 to 20, and possible injuries (severity 'C') decreased from 10 to 6.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw significant count changes year-over-year. 'Driving too fast for conditions' increased from 3 crashes to 13 crashes, a 333.3% increase in count, and 'Inattention' increased from 13 crashes to 21 crashes, a 61.5% increase in count. Conversely, 'Failed to yield right of way' decreased from 17 crashes to 11 crashes, a 35.3% reduction in count, and 'No improper driving' decreased from 26 crashes to 22 crashes, a 15.4% reduction in count. The ranking of top factors shifted, with 'Inattention' moving to the second most frequent factor and 'Driving too fast for conditions' becoming the third most frequent.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Regarding crash conditions, incidents during 'Daylight' increased from 47 to 67, while those in 'Dark - lighted roadway' decreased from 56 to 49. 'Clear' weather crashes increased from 50 to 63, but 'Rain' conditions saw a reduction from 14 to 6 crashes, and 'Snow' conditions decreased from 10 to 3 crashes. On road surfaces, 'Dry' conditions accounted for more crashes, rising from 63 to 83, while 'Wet' conditions decreased from 38 to 21, and crashes on 'Snow' and 'Ice' surfaces increased from 10 to 16 and 5 to 9, respectively.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 227 to 238 year-over-year. The top five vehicle makes involved remained consistent, with HONDA, TOYOTA, FORD, NISSAN, and HYUNDAI showing slight increases in counts. In terms of persons involved, the 16-20 age group saw a substantial increase from 18 to 32, and the 35-44 age group increased from 44 to 51, while the 45-54 age group experienced a decrease from 38 to 26.
Top Vehicle Makes (238 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Vehicle unit records
52 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (257 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 mph speed zones increased from 43 to 50, and those in 30 mph zones rose from 28 to 35. Crashes in 55 mph zones also increased from 8 to 11, while crashes in 65 mph zones decreased from 9 to 6. Notably, the prior period recorded 1 fatal crash in a 40 mph zone, whereas the current period reported no fatal crashes in any speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-12-01 to 2025-12-31 · 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: 2025-12-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-12-01 through 2025-12-31 (31 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 133
- Total persons involved: 310
- Total vehicles involved: 238
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: December 2025." Published June 21, 2026. Reporting period: 2025-12-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/december-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: 2025-12-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved