ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · APRIL 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/april-2026-report
Monthly Traffic Safety Analysis
106 CRASHES IN
CHICOPEE, MA
APRIL 2026
Total crashes decreased from 130 in April 2025 to 106 in April 2026, representing an 18.5% reduction year-over-year. The most notable shift was a significant decrease in crashes attributed to "Inattention," which fell from 30 crashes to 11 crashes. Fatalities remained at zero in both periods.
106
▼ -18.5%was 130
Total Crash Events
0
Persons Killed
37
▲ 2.8%was 36
Persons Injured
12
▼ -36.8%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. 4 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash incidents in Chicopee decreased year-over-year, with total crashes falling by 18.5% from 130 in April 2025 to 106 in April 2026. While total injuries saw a slight increase from 36 to 37, fatalities remained at zero for both periods. This indicates a general downward trend in crash frequency.
12
Hit-and-Run Crashes — April 2026
▼ -36.8% vs prior (19)
Hit-and-run crashes decreased from 19 incidents in April 2025 to 12 incidents in April 2026, representing a reduction of 7 crashes. The hit-and-run rate also decreased by 3.3 percentage points, from 14.6% to 11.3% of total crashes. This indicates a downward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
2
Cyclists Injured
35
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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 Tuesday in April 2025, with 25 incidents, to Thursday in April 2026, with 24 incidents. The peak hour also changed, moving from 2 PM with 18 crashes in the prior period to 3 PM with 11 crashes in the current period. Overall, crash counts decreased across most days of the week and hours of the day.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatalities remained at zero for both April 2025 and April 2026. The distribution of injury severities saw a change, with serious injuries appearing in the current period with 1 crash (0.9% of total crashes) compared to zero in the prior period. Minor injury crashes decreased from 23 (17.7% of total crashes) to 15 (14.2% of total crashes), while possible injury crashes increased from 4 (3.1% of total crashes) to 7 (6.6% of total crashes).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Most severe injury per crash record
Top Contributing Factors
Crashes attributed to "Inattention" saw a substantial decrease, dropping from 30 crashes in April 2025 to 11 crashes in April 2026, a 63.3% reduction in count. Crashes attributed to "Exceeded authorized speed limit" also decreased by 75%, from 4 to 1 incident. Conversely, "Other improper action" crashes increased by 75%, from 4 to 7 incidents, and "Distracted" crashes rose by 66.7%, from 3 to 5 incidents.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in "Daylight" conditions decreased from 112 in April 2025 to 80 in April 2026. Conversely, crashes in "Dark - lighted roadway" conditions increased from 13 to 24 year-over-year. Incidents on "Dry" road surfaces decreased from 103 to 89, while those on "Wet" surfaces also decreased from 27 to 17.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 20%, from 250 in April 2025 to 200 in April 2026. Among top vehicle makes, Honda saw a significant decrease from 54 vehicles to 28, while Toyota increased from 23 to 35 vehicles. Ford also experienced a decrease in involvement, from 27 to 16 vehicles.
Top Vehicle Makes (200 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Vehicle unit records
36 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (229 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurring in 25 mph speed zones decreased from 51 in April 2025 to 42 in April 2026. Similarly, incidents in 30 mph zones decreased from 34 to 31, and 65 mph zones saw a reduction from 6 to 3 crashes. Fatalities remained at zero across all speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-04-01 to 2026-04-30 · 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: 2026-04-01 through 2026-04-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-04-01 through 2026-04-30 (30 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 106
- Total persons involved: 266
- Total vehicles involved: 200
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: April 2026." Published June 21, 2026. Reporting period: 2026-04-01 to 2026-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/april-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: 2026-04-01 – 2026-04-30
Generated: June 21, 2026 · All rights reserved