ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RAYNHAM, 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/raynham/2025-annual-report
Yearly Traffic Safety Analysis
531 CRASHES IN
RAYNHAM, MA
2025
In 2025, Raynham recorded 531 total traffic crashes, a 14.8% decrease from the 623 crashes reported in 2024. This downward trend was reflected across most key metrics, with total fatalities decreasing from 2 to 1 and total injuries falling from 221 to 211. One of the most significant shifts was a 42% reduction in crashes involving a suspected DUI driver, which fell from 19 incidents to 11 year-over-year.
531
▼ -14.8%was 623
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
211
▼ -4.5%was 221
Persons Injured
24
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 Raynham showed improvement year-over-year. Total crashes fell by 14.8%, from 623 in 2024 to 531 in 2025. This was accompanied by a 4.5% decrease in persons injured (from 221 to 211) and a 50% reduction in fatalities (from 2 to 1).
24
Hit-and-Run Crashes — 2025
▼ 0.0% vs prior (24)
The absolute number of hit-and-run crashes in Raynham was unchanged, with 24 incidents recorded in both 2025 and 2024. However, due to the 14.8% decrease in total crashes in 2025, the hit-and-run rate as a percentage of all crashes increased. This rate rose from 3.9% in 2024 to 4.5% in 2025, making hit-and-runs a slightly larger proportion of total incidents.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
2
Pedestrians Injured
4
Cyclists Injured
205
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 remained largely consistent between the two years. Friday was the peak day for crashes in both 2025 (91 crashes) and 2024 (106 crashes). However, the peak hour for collisions shifted slightly earlier, moving from the 4 PM hour in 2024 (60 crashes) to the 3 PM hour in 2025 (47 crashes).
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
While the number of fatal crashes remained constant at one event in both years, the number of resulting fatalities decreased from 2 in 2024 to 1 in 2025. The overall proportion of crashes involving an injury was stable, accounting for 26.2% of crashes in 2025 compared to 25.2% in 2024. Notably, the count of serious injury crashes increased from 7 to 9, while crashes involving minor or possible injuries saw a combined decrease from 150 to 130.
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 primary contributing factors to crashes were consistent across both periods, with 'Inattention' ranking as the top cause in both 2024 and 2025. The count of crashes attributed to inattention decreased by 26.1%, from 157 incidents in 2024 to 116 in 2025. Similarly, crashes involving 'Failed to yield right of way' dropped from 99 to 81. In contrast, crashes where speeding was a factor saw a slight increase in count from 37 to 39 incidents.
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
Crash conditions were broadly similar year-over-year, with no significant shifts due to adverse weather or road surfaces. The majority of collisions in both 2025 and 2024 occurred in daylight (68.2% and 70.8%, respectively) and on dry roads (77.8% and 79.8%, respectively). There was a slight proportional increase in crashes occurring in dark but lighted roadway conditions, which grew from 14.6% of all crashes in 2024 to 18.3% in 2025.
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 vehicle makes most frequently involved in crashes remained unchanged, with Toyota, Honda, and Ford ranking as the top three in both years, though their raw counts decreased in line with the overall trend. The age distribution of persons involved in crashes also showed stability. For example, the 26-34 age group represented 18.1% of all persons in 2025, compared to 17.6% in 2024, indicating no significant demographic shift.
Top Vehicle Makes (1,008 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 (1,229 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
The distribution of crashes across posted speed zones did not change significantly between periods. The highest crash volumes in both years occurred in 65 mph, 40 mph, and 30 mph zones, with counts decreasing in each. For instance, crashes in 40 mph zones fell from 140 to 110. The single fatal crash recorded in both 2024 and 2025 occurred in a 30 mph zone.
Fatal crashes by zone: 30 mph: 1 of 86 (1.163%)
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: RAYNHAM, MA
- Total crash records analyzed: 531
- Total persons involved: 1,311
- Total vehicles involved: 1,008
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). "RAYNHAM, 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/raynham/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