ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · MARCH 2026
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/march-2026-report
Monthly Traffic Safety Analysis
114 CRASHES IN
CHICOPEE, MA
MARCH 2026
In March 2026, CHICOPEE recorded 114 total crashes, a 5% decrease from the 120 crashes reported in March 2025. Total injuries also saw a slight decrease, falling from 31 to 29. The most notable shift was a 100% increase in speeding-related crashes, rising from 4 in March 2025 to 8 in March 2026.
114
▼ -5.0%was 120
Total Crash Events
0
Persons Killed
29
▼ -6.5%was 31
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. 8 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in CHICOPEE decreased by 5% year-over-year, from 120 crashes in March 2025 to 114 crashes in March 2026. This indicates a slight downward trend in the total number of crash incidents. Total injuries also declined by 6.5%, from 31 to 29.
22
Hit-and-Run Crashes — March 2026
▲ 15.8% vs prior (19)
Hit-and-run crashes increased from 19 in March 2025 to 22 in March 2026, a rise of 3 incidents. The hit-and-run rate also increased, from 15.8% of all crashes in March 2025 to 19.3% in March 2026, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
1
Pedestrians Injured
28
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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 in March 2025 (20 crashes) to Monday in March 2026 (26 crashes). The peak crash hour also changed, moving from 4 PM in March 2025 (10 crashes) to 3 PM in March 2026 (16 crashes). This suggests a shift in the timing of peak crash activity.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes or fatalities in either March 2025 or March 2026. Minor injury crashes increased from 15 (12.5% of total) in March 2025 to 20 (17.5% of total) in March 2026. Conversely, serious injury crashes decreased from 1 (0.8% of total) to 0, and possible injury crashes decreased from 5 (4.2% of total) to 3 (2.6% of total).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to 'No improper driving' increased by 8, from 22 in March 2025 to 30 in March 2026, representing a 36.4% rise. 'Driving too fast for conditions' crashes increased by 3, from 2 to 5, a 150% increase. Crashes due to 'Failed to yield right of way' decreased by 3, from 15 to 12, a 20% reduction.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring in 'Clear' weather decreased slightly, from 70 in March 2025 to 64 in March 2026, while crashes in 'Rain' conditions increased from 9 to 10. Crashes on 'Dry' road surfaces decreased from 94 to 78, while those on 'Wet' surfaces saw a minor increase from 23 to 24. Crashes occurring during 'Daylight' hours remained the most common, decreasing slightly from 75 to 78, while those in 'Dark - lighted roadway' conditions decreased from 33 to 27.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 233 in March 2025 to 217 in March 2026. Honda remained the top vehicle make involved, though its count decreased from 38 to 33. Toyota saw an increase in involvement from 23 to 28, while Chevrolet decreased from 21 to 13. Among persons involved, the 0-15 age group saw a decrease from 15 to 6, and the 35-44 age group decreased from 52 to 43.
Top Vehicle Makes (217 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
55 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (225 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes in the 30 mph speed zone decreased by 13, from 37 in March 2025 to 24 in March 2026. Conversely, crashes in the 5 mph zone increased by 3, from 2 to 5, and in the 15 mph zone increased by 4, from 3 to 7. There were no fatal crashes recorded in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 114
- Total persons involved: 284
- Total vehicles involved: 217
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: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/march-2026-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: 2026-03-01 – 2026-03-31
Generated: June 21, 2026 · All rights reserved