ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MASSACHUSETTS, MA · JUNE 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/june-2025-report
Monthly Traffic Safety Analysis
11,181 CRASHES IN
MASSACHUSETTS, MA
JUNE 2025
In June 2025, there were 11,181 total crashes, a 4.1% decrease from the 11,660 crashes recorded in June 2024. While overall crashes declined, the number of fatalities rose from 31 to 33 year-over-year. One of the most notable shifts was in the daily pattern of collisions, with the peak day for crashes moving from Saturday in the prior year to Monday in the current period.
11,181
▼ -4.1%was 11,660
Total Crash Events
33
▲ 6.5%was 31
Persons Killed
3,775
▲ 0.1%was 3,770
Persons Injured
1,090
▼ -4.5%was 1,141
Hit-and-Run Crashes
Note: "Persons Killed" (33) counts individual fatalities across all crash events. "Fatal" in the severity table below (32) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 447 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Year-over-year, the total number of crashes in June decreased by 4.1%, falling from 11,660 in 2024 to 11,181 in 2025. Despite this overall decline in collisions, the human toll remained relatively consistent, with total injuries increasing slightly from 3,770 to 3,775 and fatalities rising from 31 to 33.
1,090
Hit-and-Run Crashes — June 2025
▼ -4.5% vs prior (1,141)
Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes fell from 1,141 in June 2024 to 1,090 in June 2025. Correspondingly, the hit-and-run rate saw a slight downward trend, decreasing from 9.8% to 9.7% of all crashes year-over-year.
Vulnerable Road User Casualties
4
Pedestrians Killed
3
Cyclists Killed
26
Motorists Killed
0
Other Killed
111
Pedestrians Injured
156
Cyclists Injured
3,440
Motorists Injured
68
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal pattern of crashes shifted between the two periods. In June 2024, the peak day for crashes was Saturday with 1,860 incidents, whereas in June 2025, the peak shifted to Monday with 1,920 incidents. The peak hour for collisions, however, remained stable at 3 p.m. in both years, with 939 crashes in the prior period and 952 in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes showed a slight increase year-over-year. The fatal crash rate rose from 0.26% in June 2024 to 0.29% in June 2025, corresponding to an increase from 30 to 32 fatal crashes. The proportion of crashes resulting in minor injuries also grew, from 15.1% of all crashes to 16.2%. Conversely, crashes categorized as having 'possible injury' or 'no injury' both saw a decrease in their share of the total.
Severity is per crash event (most severe injury). 32 fatal crash events resulted in 33 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors remained consistent year-over-year, with 'Inattention' and 'Failed to yield right of way' being the top improper driving actions cited in both periods. However, the count for several key factors decreased; crashes attributed to 'Followed too closely' fell by 9.2% from 1,127 to 1,023, and those linked to 'Inattention' dropped by 2.5% from 1,697 to 1,654. Crashes involving distraction also saw a notable 17% decrease in count, from 270 incidents in June 2024 to 224 in June 2025.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Comparing conditions, the proportion of crashes occurring on wet road surfaces increased from 8.4% in June 2024 to 9.2% in June 2025. Similarly, crashes during rain represented 6.7% of the total in the current period, up from 5.8% the prior year. The majority of crashes in both periods occurred in daylight (79.1% in prior, 80.1% in current) and on dry roads (90.0% in prior, 88.6% in current), with these proportions remaining relatively stable.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field
Vehicles & Demographics
The demographic profile of persons involved in crashes remained largely stable, though the share of individuals aged 65 and older increased slightly from 11.0% to 11.6% of all persons involved. The top five most common vehicle makes involved in crashes were identical in both periods, with Toyota, Honda, Ford, Chevrolet, and Nissan leading the list in the same order. Toyota was the most frequent make in both June 2024 (3,535 vehicles) and June 2025 (3,403 vehicles).
Top Vehicle Makes (20,916 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records
2,871 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (23,254 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events
Speed Limit Zones
Analysis of speed zones reveals a shift in crash locations. Crashes in 30 mph zones decreased from 3,084 to 2,717, while those in 25 mph zones increased from 2,433 to 2,782. While overall crashes declined, fatal incidents in higher speed zones saw a notable increase. In the 65 mph zone, fatal crashes rose from 1 in the prior year to 5 in the current year, despite a decrease in total crashes for that zone from 815 to 743.
Fatal crashes by zone: 15 mph: 1 of 208 (0.481%) · 25 mph: 7 of 2,782 (0.252%) · 30 mph: 6 of 2,717 (0.221%) · 35 mph: 4 of 1,322 (0.303%) · 40 mph: 3 of 817 (0.367%) · 45 mph: 3 of 336 (0.893%) · 55 mph: 1 of 462 (0.216%) · 65 mph: 5 of 743 (0.673%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-06-01 through 2025-06-30 (30 days)
- Geographic scope: massachusetts, MA
- Total crash records analyzed: 11,181
- Total persons involved: 26,307
- Total vehicles involved: 20,916
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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/statewide/june-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: 2025-06-01 – 2025-06-30
Generated: June 21, 2026 · All rights reserved