ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · MARCH 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/statewide/march-2026-report
Monthly Traffic Safety Analysis
8,871 CRASHES IN
MASSACHUSETTS, MA
MARCH 2026
In March 2026, there were 8,871 total crashes recorded in Massachusetts, a slight decrease of 0.4% from the 8,905 crashes in March 2025. While overall crash numbers were stable, the number of fatalities rose from 21 to 26 year-over-year. The most notable shift was in crashes attributed to speeding, which increased by 93.7% from 252 incidents in the prior year to 488 in the current period.
8,871
▼ -0.4%was 8,905
Total Crash Events
26
▲ 23.8%was 21
Persons Killed
2,569
▼ -7.1%was 2,766
Persons Injured
870
▼ -6.5%was 930
Hit-and-Run Crashes
Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (26) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 304 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume remained relatively stable, with total crashes decreasing by just 0.4% from 8,905 in March 2025 to 8,871 in March 2026. However, while total injuries fell by 7.1% (from 2,766 to 2,569), the number of fatalities increased by 23.8%, rising from 21 to 26 year-over-year.
870
Hit-and-Run Crashes — March 2026
▼ -6.5% vs prior (930)
The number and rate of hit-and-run crashes both decreased in March 2026 compared to the same month in 2025. The total count of hit-and-run incidents fell by 6.5%, from 930 to 870. This resulted in a lower hit-and-run rate, which dropped from 10.4% of all crashes in the prior period to 9.8% in the current period.
Vulnerable Road User Casualties
4
Pedestrians Killed
0
Cyclists Killed
22
Motorists Killed
0
Other Killed
87
Pedestrians Injured
46
Cyclists Injured
2,422
Motorists Injured
14
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak time for crashes remained consistent year-over-year, occurring during the 3 p.m. hour in both March 2025 (782 crashes) and March 2026 (796 crashes). However, the peak day of the week shifted from Monday (1,536 crashes) in the prior period to Tuesday (1,827 crashes) in the current period. This represents a 47.6% increase in crashes occurring on Tuesdays compared to the previous year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased in March 2026 compared to the previous year, with the number of fatal crashes rising by 36.8% from 19 to 26. This pushed the fatal crash rate up from 0.21% to 0.29%. While fatal crashes rose, crashes resulting in injuries saw a decline across all categories: serious injuries fell by 9.8% (from 143 to 129), minor injuries by 6.4% (from 1,263 to 1,182), and possible injuries by 5.8% (from 599 to 564).
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent, with "Inattention" and "Failed to yield right of way" being the top improper driving behaviors in both periods. However, there were significant shifts in the counts of specific factors. Crashes attributed to "Driving too fast for conditions" surged by 211% in count, from 99 incidents in March 2025 to 308 in March 2026. Similarly, the count of crashes involving "Swerving or avoiding" increased by 143%, from 81 to 197 incidents. Conversely, crashes linked to "Inattention" decreased by 12.1% in count (from 1,230 to 1,081 incidents).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Road surface conditions were significantly different between the two periods, suggesting more inclement weather in March 2026. Crashes on non-dry surfaces (Wet, Ice, Snow, or Slush) accounted for 30.5% of all incidents in the current period, a substantial increase from 15.3% in March 2025. The number of crashes on roads with ice or snow rose from a combined 46 incidents in the prior year to 949 in the current year. Lighting conditions remained stable, with approximately 70% of crashes in both periods occurring during daylight.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Road surface condition field
Vehicles & Demographics
The profile of vehicles and persons involved in crashes remained largely unchanged year-over-year. The top five vehicle makes involved in collisions were identical in both March 2025 and March 2026: Toyota, Honda, Ford, Chevrolet, and Nissan. The age distribution of all persons involved also showed little variation, with all age groups representing a similar proportion of the total in both periods. For instance, the 65+ age group accounted for 11.6% of persons in the current period, compared to 10.9% in the prior year.
Top Vehicle Makes (16,674 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Vehicle unit records
2,301 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (18,011 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crash distribution by speed limit shows a shift towards higher-speed roadways year-over-year. The number of crashes in the 65 mph zone increased by 31.8% from 450 to 593 incidents, while crashes in 25 mph and 30 mph zones decreased. The lethality of crashes on these high-speed roads also increased; in both the 55 mph and 65 mph zones, fatalities rose from 1 in the prior year to 5 in the current year.
Fatal crashes by zone: 20 mph: 1 of 251 (0.398%) · 25 mph: 2 of 2,144 (0.093%) · 30 mph: 1 of 2,128 (0.047%) · 35 mph: 2 of 1,054 (0.19%) · 40 mph: 4 of 620 (0.645%) · 45 mph: 4 of 317 (1.262%) · 50 mph: 2 of 186 (1.075%) · 55 mph: 5 of 389 (1.285%) · 65 mph: 5 of 593 (0.843%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-03-01 to 2026-03-31 · 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: 2026-03-01 through 2026-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-03-01 through 2026-03-31 (31 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 8,871
- Total persons involved: 20,458
- Total vehicles involved: 16,674
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: March 2026." Published June 21, 2026. Reporting period: 2026-03-01 to 2026-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/march-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: 2026-03-01 – 2026-03-31
Generated: June 21, 2026 · All rights reserved