ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · NOVEMBER 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/statewide/november-2025-report
Monthly Traffic Safety Analysis
10,491 CRASHES IN
MASSACHUSETTS, MA
NOVEMBER 2025
In November 2025, there were 10,491 total crashes, representing a 13.4% decrease from the 12,108 crashes recorded in November 2024. This overall reduction in crash volume was the most notable year-over-year shift. Concurrently, total reported injuries fell by 18.6% from 3,770 to 3,070, and fatalities decreased from 38 to 32.
10,491
▼ -13.4%was 12,108
Total Crash Events
32
▼ -15.8%was 38
Persons Killed
3,070
▼ -18.6%was 3,770
Persons Injured
1,003
▼ -8.9%was 1,101
Hit-and-Run Crashes
Note: "Persons Killed" (32) counts individual fatalities across all crash events. "Fatal" in the severity table below (29) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 396 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year data indicates a significant downward trend in traffic incidents for November. Total crashes decreased by 13.4%, falling from 12,108 in November 2024 to 10,491 in November 2025. This decline was also reflected in crash outcomes, with total injuries decreasing by 18.6% and total fatalities falling from 38 to 32.
1,003
Hit-and-Run Crashes — November 2025
▼ -8.9% vs prior (1,101)
While the total number of hit-and-run crashes decreased from 1,101 to 1,003 year-over-year, the hit-and-run rate as a percentage of all crashes trended upward. In November 2025, hit-and-runs constituted 9.6% of all crashes, an increase from the 9.1% rate observed in November 2024. This indicates that although overall crashes declined, hit-and-run incidents declined at a slower pace, making them a larger proportion of the remaining crashes.
Vulnerable Road User Casualties
5
Pedestrians Killed
2
Cyclists Killed
25
Motorists Killed
0
Other Killed
159
Pedestrians Injured
67
Cyclists Injured
2,819
Motorists Injured
25
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts between the two periods. The peak day for crashes moved from Friday (2,306 crashes) in November 2024 to Saturday (1,773 crashes) in November 2025. The peak hour for collisions remained the 5 p.m. hour in both periods, though the volume of crashes during this hour decreased from 1,202 to 1,092.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The overall severity of crashes lessened year-over-year. The proportion of crashes resulting in any injury fell from 23.2% in November 2024 to 21.3% in November 2025, with the share of serious injury crashes declining from 2.0% to 1.6%. The absolute number of fatal crashes also decreased from 37 to 29, although their share of total crashes remained constant at 0.3%.
Severity is per crash event (most severe injury). 29 fatal crash events resulted in 32 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with 'No improper driving,' 'Inattention,' and 'Failed to yield right of way' as the top three in both periods. The count of crashes for these top factors decreased in line with the overall trend; for example, crashes involving inattention fell by 14.5% from 1,543 to 1,319. The rankings of the top five contributing factors did not change year-over-year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The proportion of crashes occurring under different conditions showed some changes year-over-year. Crashes in daylight conditions decreased as a share of the total, from 53.6% in November 2024 to 51.1% in November 2025. Correspondingly, the share of crashes in dark conditions (both lighted and unlighted roadways) increased from 38.8% to 41.8% of all incidents. Road surface conditions for crashes remained stable, with about 82% occurring on dry roads in both periods.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field
Vehicles & Demographics
Vehicle and person demographics involved in crashes remained largely consistent compared to the previous year. The top three vehicle makes involved in collisions were Toyota, Honda, and Ford in both November 2024 and November 2025, with their rankings unchanged. Similarly, the age distribution of all persons involved in crashes saw no significant shifts, with all major age cohorts representing a nearly identical percentage of the total in both periods.
Top Vehicle Makes (19,331 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records
2,754 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (21,124 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across different speed zones remained broadly similar, with a slight proportional shift toward higher speed zones. Crashes in zones with speed limits of 55 mph or higher accounted for 12.0% of all crashes in November 2025, up from 11.0% in the prior year. Conversely, the proportion of crashes in zones with limits of 30 mph or less was stable at approximately 54%.
Fatal crashes by zone: 25 mph: 4 of 2,353 (0.17%) · 30 mph: 6 of 2,542 (0.236%) · 35 mph: 4 of 1,290 (0.31%) · 40 mph: 2 of 878 (0.228%) · 45 mph: 3 of 415 (0.723%) · 65 mph: 7 of 701 (0.999%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-11-01 through 2025-11-30 (30 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 10,491
- Total persons involved: 24,056
- Total vehicles involved: 19,331
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). "massachusetts, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/november-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: 2025-11-01 – 2025-11-30
Generated: June 21, 2026 · All rights reserved