ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SOMERSET, MA · 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/somerset/2025-annual-report
Yearly Traffic Safety Analysis
366 CRASHES IN
SOMERSET, MA
2025
In 2025, Somerset recorded 366 total traffic crashes, a 15.7% decrease from the 434 crashes reported in 2024. This downward trend was accompanied by a reduction in fatalities, which fell from 5 in the prior year to 2 in the current year. The number of people injured also decreased from 133 to 113.
366
▼ -15.7%was 434
Total Crash Events
2
▼ -60.0%was 5
Persons Killed
113
▼ -15.0%was 133
Persons Injured
24
▼ -7.7%was 26
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Somerset showed improvement year-over-year. The total number of crashes decreased by 15.7%, from 434 in 2024 to 366 in 2025. This was mirrored by a 15.0% reduction in total injuries (from 133 to 113) and a 60% drop in fatalities (from 5 to 2).
24
Hit-and-Run Crashes — 2025
▼ -7.7% vs prior (26)
The total number of hit-and-run crashes saw a small decrease, from 26 incidents in 2024 to 24 in 2025. Despite this drop in volume, the hit-and-run rate as a percentage of all crashes trended slightly upward. In 2025, hit-and-runs constituted 6.6% of all crashes, compared to 6.0% in the prior year.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
3
Pedestrians Injured
110
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes shifted between the two periods. In 2025, the busiest days for crashes were Wednesday and Friday, each with 62 incidents, a change from 2024 when Saturday was the peak day with 76 crashes. The peak hour for collisions remained consistent at 4 p.m. in both years, though the volume of crashes during this hour fell from 47 in 2024 to 33 in 2025.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity improved, with the number of fatal crashes decreasing from 5 in 2024 to 2 in 2025, and the fatal crash rate dropping from 1.15% to 0.55%. While the total number of injury-related crashes fell from 98 to 91, their share of all crashes rose from 22.6% to 24.9%. Notably, the share of crashes classified as 'Serious Injury' more than doubled, increasing from 0.7% of total incidents in 2024 to 1.6% in 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of top contributing factors shifted year-over-year. In 2025, 'No improper driving' became the most cited factor with 73 incidents, followed by 'Followed too closely' (72). This contrasts with 2024, when 'Inattention' was the leading factor with 83 incidents. The count of crashes attributed to 'Inattention' decreased by 26.5% (from 83 to 61), while crashes due to 'Failed to yield right of way' saw a significant 38.4% drop in count (from 73 to 45). Conversely, crashes involving 'Followed too closely' increased in count by 12.5% (from 64 to 72).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
The distribution of crashes across different environmental conditions remained largely consistent between 2024 and 2025. In both years, the vast majority of crashes occurred in clear weather (79.2% in 2025 vs. 80.0% in 2024) and on dry road surfaces (81.7% in 2025 vs. 83.4% in 2024). Similarly, the proportion of crashes happening in daylight was stable, accounting for 71.6% of incidents in 2025 compared to 73.3% in the prior year. There were no significant shifts in the proportion of crashes occurring during adverse conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Toyota, Ford, and Honda being the most frequent in both years. Toyota led in both periods, though its involvement decreased from 137 vehicles in 2024 to 126 in 2025. The age demographics of persons involved in crashes showed minor shifts, with the 65+ age group's representation decreasing from 14.9% of all persons in 2024 to 12.8% in 2025. Other age groups maintained a relatively stable share of involvement year-over-year.
Top Vehicle Makes (684 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
73 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (752 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
There was a notable shift in crashes toward higher speed zones in 2025. The proportion of crashes occurring in zones with speed limits of 55 mph or higher increased from 7.0% of incidents in 2024 to 14.3% in 2025. In 2025, both of the year's two fatalities occurred in the 65 mph zone. This contrasts with 2024, where fatalities were spread across 30 mph, 45 mph, and 65 mph zones.
Fatal crashes by zone: 65 mph: 2 of 43 (4.651%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: SOMERSET, MA
- Total crash records analyzed: 366
- Total persons involved: 836
- Total vehicles involved: 684
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). "SOMERSET, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/somerset/2025-annual-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved