ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · JUNE 2023
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/june-2023-report
Monthly Traffic Safety Analysis
138 CRASHES IN
CHICOPEE, MA
JUNE 2023
In June 2023, Chicopee experienced 138 total crashes, a decrease of 16.87% compared to the 166 crashes recorded in June 2022. Total injuries also saw a reduction, dropping from 50 to 44. Notably, hit-and-run crashes increased by 43.75%, rising from 16 incidents in June 2022 to 23 in June 2023.
138
▼ -16.9%was 166
Total Crash Events
0
Persons Killed
44
▼ -12.0%was 50
Persons Injured
23
▲ 43.8%was 16
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. 3 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash data for Chicopee indicates a downward trend year-over-year, with total crashes decreasing by 16.87% from 166 in June 2022 to 138 in June 2023. Similarly, total injuries declined by 12%, from 50 to 44. This suggests a general improvement in crash frequency and injury outcomes during the period.
23
Hit-and-Run Crashes — June 2023
▲ 43.8% vs prior (16)
Hit-and-run crashes increased significantly year-over-year, rising from 16 incidents in June 2022 to 23 incidents in June 2023, representing a 43.75% increase. The hit-and-run rate also increased from 9.6% of all crashes in June 2022 to 16.7% in June 2023, indicating an upward trend in these types of incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
4
Cyclists Injured
39
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes show some shifts year-over-year. While June 2022's peak day for crashes was Wednesday with 32 incidents, June 2023 saw Thursday as the peak day, also with 32 crashes. The peak hour remained consistent at 4 PM in both periods, with 17 crashes in June 2022 and 20 crashes in June 2023.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes and total fatalities remained at zero for both June 2022 and June 2023. Total injuries decreased from 50 in the prior period to 44 in the current period. The proportion of crashes resulting in minor injuries (Severity B) slightly decreased from 15.1% to 14.5%, while possible injury crashes (Severity C) increased from 6% to 10.1% of total crashes.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' remained the most frequently cited, increasing from 30 crashes to 34 crashes, a 13.3% rise. 'Inattention' decreased by 27.6%, from 29 crashes to 21 crashes, while 'Followed too closely' increased by 46.2%, from 13 crashes to 19 crashes. 'Failed to yield right of way' saw a significant decrease of 45%, dropping from 20 crashes to 11 crashes year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions saw some shifts, with crashes occurring in 'Clear' weather decreasing from 126 to 81, while 'Cloudy' weather crashes increased from 20 to 29. Crashes on 'Dry' road surfaces decreased from 155 to 122, whereas those on 'Wet' surfaces increased from 9 to 15. The number of crashes occurring in 'Daylight' conditions decreased from 136 to 112.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 16.2%, from 308 in June 2022 to 258 in June 2023. HONDA remained the top vehicle make involved, though its count decreased from 52 to 37. Crashes involving persons aged 65 and older saw the largest decrease, dropping from 48 to 29, while male persons involved decreased from 177 to 157 and female persons involved decreased from 171 to 143.
Top Vehicle Makes (258 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records
45 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (300 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes within a 25 mph speed limit saw a decrease from 55 to 49, while crashes in 30 mph zones also decreased from 54 to 35. No fatal crashes were recorded in any speed zone for either period. The distribution of crashes across speed zones largely maintained its pattern, with the majority occurring in 25 mph and 30 mph zones in both years.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-06-01 through 2023-06-30 (30 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 138
- Total persons involved: 347
- Total vehicles involved: 258
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: June 2023." Published June 21, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/june-2023-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: 2023-06-01 – 2023-06-30
Generated: June 21, 2026 · All rights reserved