ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · CHICOPEE, MA · NOVEMBER 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/november-2024-report
Monthly Traffic Safety Analysis
102 CRASHES IN
CHICOPEE, MA
NOVEMBER 2024
In November 2024, Chicopee experienced 102 total crashes, a decrease of 38.18% compared to 165 crashes in November 2023. Total fatalities increased from 0 in November 2023 to 1 in November 2024, marking a significant year-over-year shift in crash outcomes. Total injuries also decreased from 52 to 37, representing a 28.85% reduction.
102
▼ -38.2%was 165
Total Crash Events
1
Persons Killed
37
▼ -28.8%was 52
Persons Injured
13
▼ -27.8%was 18
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a substantial decrease in crash incidents year-over-year, with total crashes falling by 63, or 38.18%, from 165 in November 2023 to 102 in November 2024. Despite this reduction in overall crashes, there was an increase in total fatalities from 0 to 1 during the same period.
13
Hit-and-Run Crashes — November 2024
▼ -27.8% vs prior (18)
The number of hit-and-run crashes decreased from 18 in November 2023 to 13 in November 2024. However, the hit-and-run crash rate increased from 10.9% to 12.7% year-over-year. This indicates that while the absolute number of hit-and-run incidents fell, they constituted a larger proportion of total crashes in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
0
Other Killed
0
Pedestrians Injured
36
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns for crashes shifted between the two periods. In November 2024, the peak day for crashes was Sunday with 18 incidents, whereas in November 2023, Wednesday saw the highest count with 31 crashes. The peak crash hour also changed from 2 PM with 17 crashes in the prior period to 5 PM with 14 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes increased from 0 in November 2023 to 1 in November 2024, resulting in a fatal crash rate of 0.98% in the current period. Crashes involving serious injuries (code 'A') increased from 1 (0.6% share) to 2 (2% share) year-over-year. Minor injury crashes (code 'B') decreased in count from 27 to 16, though their share remained relatively stable at 16.4% and 15.7% respectively.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Most severe injury per crash record
Top Contributing Factors
Among contributing factors, 'No improper driving' decreased by 18 crashes (a 40% reduction in count) from 45 to 27. 'Inattention' crashes saw a 56% reduction in count, dropping from 25 to 11. Conversely, 'Distracted' driving incidents increased significantly by 400% in count, rising from 1 crash in November 2023 to 5 crashes in November 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions decreased from 113 to 63, while crashes during rain conditions increased from 1 to 5. The proportion of crashes on dry road surfaces decreased from 86.67% (143 of 165) in the prior period to 84.31% (86 of 102) in the current period. Daylight crashes decreased from 90 to 56, while crashes in dark-lighted roadway conditions decreased from 60 to 38.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 311 to 189 year-over-year. The top vehicle make involved in crashes shifted, with Honda becoming the most frequent in November 2024 (28 incidents), surpassing Toyota and Ford, which were tied for the top spot in November 2023 with 38 incidents each. In terms of persons involved, most age groups saw a decrease in representation, with the 35-44 age group experiencing the largest drop from 73 to 35 persons.
Top Vehicle Makes (189 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
25 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (214 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 25 MPH speed zones decreased from 51 to 33, a 35.3% reduction, while those in 30 MPH zones decreased from 51 to 22, a 56.9% reduction. The single fatal crash in November 2024 occurred in a 30 MPH zone, where no fatal crashes were recorded in the prior period. Crashes in 65 MPH zones slightly increased from 9 to 11, though no fatalities were recorded in this zone for either period.
Fatal crashes by zone: 30 mph: 1 of 22 (4.545%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · 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: 2024-11-01 through 2024-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-11-01 through 2024-11-30 (30 days)
- Geographic scope: CHICOPEE, MA
- Total crash records analyzed: 102
- Total persons involved: 241
- Total vehicles involved: 189
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: November 2024." Published June 21, 2026. Reporting period: 2024-11-01 to 2024-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/chicopee/november-2024-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: 2024-11-01 – 2024-11-30
Generated: June 21, 2026 · All rights reserved