ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, 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/statewide/november-2024-report
Monthly Traffic Safety Analysis
12,108 CRASHES IN
MASSACHUSETTS, MA
NOVEMBER 2024
In November 2024, there were 12,108 total crashes, a 1.7% decrease from the 12,315 crashes recorded in November 2023. Despite the slight drop in overall collisions, the number of fatalities doubled, increasing from 19 to 38 year-over-year. This sharp rise in fatalities represents the most significant change in the data between the two periods.
12,108
▼ -1.7%was 12,315
Total Crash Events
38
▲ 100.0%was 19
Persons Killed
3,770
▲ 6.0%was 3,557
Persons Injured
1,101
▼ -0.9%was 1,111
Hit-and-Run Crashes
Note: "Persons Killed" (38) counts individual fatalities across all crash events. "Fatal" in the severity table below (37) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 478 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
Overall crash volume showed a slight decline in November 2024 compared to the previous year, with total incidents decreasing by 1.7% from 12,315 to 12,108. However, this small reduction in total crashes was accompanied by a 6.0% increase in total injuries, which rose from 3,557 to 3,770. Fatalities also saw a significant increase, doubling from 19 to 38.
1,101
Hit-and-Run Crashes — November 2024
▼ -0.9% vs prior (1,111)
The number of hit-and-run incidents remained relatively stable, with a slight decrease from 1,111 in November 2023 to 1,101 in November 2024. However, because the total number of crashes also decreased, the hit-and-run rate saw a marginal increase from 9.0% to 9.1% of all crashes. This indicates that hit-and-run incidents made up a slightly larger proportion of all crashes in the current period.
Vulnerable Road User Casualties
11
Pedestrians Killed
0
Cyclists Killed
25
Motorists Killed
2
Other Killed
191
Pedestrians Injured
105
Cyclists Injured
3,439
Motorists Injured
35
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 of crashes showed some shifts between the two periods. While the peak hour for collisions remained consistent at 5 p.m. in both November 2023 (1,232 crashes) and November 2024 (1,202 crashes), the peak day changed. The highest volume of crashes shifted from Wednesday (2,398) in the prior year to Friday (2,306) in the current year.
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
Crash severity worsened in November 2024 compared to the prior year, with the number of fatal crashes more than doubling from 18 to 37. Consequently, the fatal crash rate increased from 0.15 to 0.31 per 100 crashes. The number of crashes resulting in serious injuries also rose from 213 to 237, and minor injury crashes increased from 1,546 to 1,721. The proportion of non-injury crashes decreased slightly from 73.1% to 72.6% of all incidents.
Severity is per crash event (most severe injury). 37 fatal crash events resulted in 38 persons killed.
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
The top three contributing factors remained consistent in rank year-over-year: 'No improper driving,' 'Inattention,' and 'Failed to yield right of way.' However, the count for crashes attributed to 'No improper driving' decreased by 8.5% from 3,461 to 3,168. Notably, crashes involving 'Driving too fast for conditions' increased by 31.5% from 181 to 238 incidents, and those where a driver 'Disregarded traffic signs, signals, road markings' rose by 16.6% from 307 to 358.
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 in November 2024 occurred under more adverse road and weather conditions compared to the previous year. The number of crashes on wet roads increased from 1,420 to 1,870, and incidents on icy roads more than tripled from 38 to 125. This corresponds with an increase in crashes during rain, which rose from 564 to 906. Crashes in 'Dark - lighted roadway' conditions also saw a slight increase from 3,503 to 3,584 incidents.
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 distribution of top vehicle makes involved in crashes remained largely unchanged, with Toyota, Honda, and Ford consistently being the three most common makes in both periods. An analysis of person demographics shows a notable 5.8% increase in the number of individuals aged 65 and older involved in crashes, rising from 3,040 to 3,217. Conversely, the involvement of persons in the 21-25 age group decreased by 4.4% from 2,880 to 2,754.
Top Vehicle Makes (22,463 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-11-01 to 2024-11-30 · Vehicle unit records
3,030 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (25,057 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
There was a shift in crash locations, with a 12.2% increase in incidents occurring in 25 mph zones, from 2,351 to 2,638. Conversely, crashes in 65 mph zones decreased by 13.6% from 899 to 777. Despite this shift, the number of fatal crashes increased across multiple zones; fatalities in 25 mph zones quadrupled from 2 to 8, while fatalities in 65 mph zones doubled from 4 to 8. The fatal crash rate for 65 mph zones increased from 0.445% to 1.03%.
Fatal crashes by zone: 5 mph: 1 of 137 (0.73%) · 20 mph: 1 of 317 (0.315%) · 25 mph: 8 of 2,638 (0.303%) · 30 mph: 6 of 3,037 (0.198%) · 35 mph: 4 of 1,607 (0.249%) · 40 mph: 3 of 937 (0.32%) · 45 mph: 3 of 458 (0.655%) · 55 mph: 1 of 513 (0.195%) · 65 mph: 8 of 777 (1.03%)
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: massachusetts, MA
- Total crash records analyzed: 12,108
- Total persons involved: 28,225
- Total vehicles involved: 22,463
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 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/statewide/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