ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · RAYNHAM, MA · MARCH 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/march-2025-report
Monthly Traffic Safety Analysis
37 CRASHES IN
RAYNHAM, MA
MARCH 2025
In March 2025, RAYNHAM experienced 37 total crashes, marking a 15.9% decrease compared to the 44 crashes reported in March 2024. Despite the reduction in overall crashes, total injuries rose significantly from 8 in the prior period to 15 in the current period, an 87.5% increase. This suggests a notable shift towards more injurious outcomes per crash.
37
▼ -15.9%was 44
Total Crash Events
0
Persons Killed
15
▲ 87.5%was 8
Persons Injured
0
▼ -100.0%was 1
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the number of crashes in RAYNHAM decreased by 15.9% year-over-year, from 44 crashes in March 2024 to 37 crashes in March 2025. Fatalities remained at zero in both periods, indicating stability in the most severe outcomes. However, total injuries increased by 87.5%, rising from 8 to 15, which suggests a concerning trend of higher injury rates per crash.
Vulnerable Road User Casualties
0
Motorists Killed
15
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes showed some shifts year-over-year. While Friday remained the peak day for crashes in both periods, the count decreased from 10 crashes in March 2024 to 8 crashes in March 2025. The peak crash hour shifted from 2 p.m. in the prior period (7 crashes) to 5 p.m. in the current period (6 crashes), indicating a change in the busiest time for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero for both March 2024 and March 2025. However, the proportion of crashes resulting in injuries increased, with 9 crashes involving injuries (24.3% of total crashes) in the current period compared to 7 such crashes (15.9% of total crashes) in the prior period. Notably, serious injury crashes, categorized as 'A', were reported in March 2025 (1 crash) where none were present in March 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Most severe injury per crash record
Top Contributing Factors
Contributing factors saw notable shifts in their counts and rankings year-over-year. 'No improper driving' increased by 50% in count, from 6 to 9, becoming the most frequent factor in the current period. Conversely, 'Followed too closely' decreased by 60% in count, from 10 to 4, and 'Inattention' decreased by 20% in count, from 10 to 8. 'Failed to yield right of way' increased by 60% in count, from 5 to 8, rising in prominence.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions remained largely consistent, with 'Daylight' being the predominant lighting condition for crashes in both periods, accounting for 35 crashes in the prior period and 29 in the current. 'Dry' road surfaces were most common, though crashes on 'Wet' surfaces decreased from 13 in March 2024 to 9 in March 2025. The proportion of crashes occurring under adverse road conditions (wet or icy) saw a slight decrease from 29.5% to 27%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased by 17.4%, from 86 in March 2024 to 71 in March 2025. Toyota remained the top vehicle make involved, though its count decreased from 16 to 14 year-over-year. There was a 50% increase in persons aged 0-15 involved in crashes (from 6 to 9), while involvement for ages 21-25 decreased by 30.8% (from 13 to 9).
Top Vehicle Makes (71 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Vehicle unit records
Sex Distribution (92 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes with recorded speed limits decreased from 44 in March 2024 to 34 in March 2025. A significant decrease was observed in crashes occurring in 65 mph zones, dropping from 17 to 7. Conversely, crashes in 30 mph zones increased from 2 to 6, and in 50 mph zones from 4 to 7, indicating a shift in crash distribution towards lower speed limit areas.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-03-01 to 2025-03-31 · 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: 2025-03-01 through 2025-03-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-03-01 through 2025-03-31 (31 days)
- Geographic scope: RAYNHAM, MA
- Total crash records analyzed: 37
- Total persons involved: 92
- Total vehicles involved: 71
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: March 2025." Published June 21, 2026. Reporting period: 2025-03-01 to 2025-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/raynham/march-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: 2025-03-01 – 2025-03-31
Generated: June 21, 2026 · All rights reserved