Monthly Traffic Safety Analysis

45 CRASHES IN
RAYNHAM, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

In February 2025, RAYNHAM experienced 45 total crashes, an increase from 42 crashes reported in February 2024, representing a 7.14% rise. Total injuries also increased significantly, from 12 in the prior period to 17 in the current period, a 41.67% increase. Fatalities remained at zero in both comparative periods.

45

7.1%was 42

Total Crash Events

0

Persons Killed

17

41.7%was 12

Persons Injured

0

-100.0%was 2

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight increase in crash incidents year-over-year, with total crashes rising by 7.14% from 42 to 45. A more pronounced upward trend is observed in injuries, which increased by 41.67% from 12 to 17. Fatalities remained stable at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

17

Motorists Injured

Prior: 1241.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Wednesday, with 10 incidents in February 2024, to Sunday, with 15 incidents in February 2025. Similarly, the peak hour for crashes moved from 5 PM, which had 8 incidents in the prior year, to 11 PM, which recorded 4 incidents in the current period. This indicates a notable change in the temporal distribution of crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The proportion of crashes resulting in injury increased from 21.4% in February 2024 to 28.9% in February 2025. Specifically, serious injuries rose from 0 to 1, and minor injuries increased from 6 to 11. Possible injuries decreased from 3 to 1, while fatal crash rates remained at 0% for both periods.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.2%
Minor Injury11minor injury crashes24.4%
83.3%prior 6
Possible Injury1possible injury crashes2.2%
-66.7%prior 3
No Injury31no injury crashes68.9%
-3.1%prior 32

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, "Inattention," decreased from 18 crashes in February 2024 to 7 crashes in February 2025. Conversely, "Followed too closely" more than doubled, increasing from 4 crashes to 8 crashes. "Failed to yield right of way" also saw an increase from 6 crashes to 7 crashes.

Officer-Reported Primary Contributing Cause

Followed too closely8 (17.8%)
Inattention7 (15.6%)-61.1%prior 18
Failed to yield right of way7 (15.6%)16.7%prior 6
No improper driving7 (15.6%)
Failure to keep in proper lane or running off road3 (6.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (6.7%)
Driving too fast for conditions2 (4.4%)
Other improper action2 (4.4%)
Made an improper turn1 (2.2%)
Distracted1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse weather conditions (snow, rain, sleet) increased from 6 (14.3% of total crashes) in February 2024 to 13 (28.9%) in February 2025. Crashes on adverse road surfaces (snow, wet, slush) also rose significantly from 8 (19.0%) to 19 (42.2%). Incidents during dark or low-light conditions increased from 12 (28.6%) to 19 (42.2%), suggesting a shift towards less favorable environmental conditions at the time of crashes.

Weather

Clear21 (47.7%)
-36.4%prior 33
Clear/Clear8 (18.2%)
Snow6 (13.6%)
Snow/Snow4 (9.1%)
Cloudy2 (4.5%)
Rain1 (2.3%)
Rain/Sleet, hail (freezing rain or drizzle)1 (2.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight26 (57.8%)
-13.3%prior 30
Dark - lighted roadway14 (31.1%)
75.0%prior 8
Dark - roadway not lighted4 (8.9%)
Dusk1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry26 (57.8%)
-23.5%prior 34
Snow12 (26.7%)
140.0%prior 5
Wet6 (13.3%)
Slush1 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

Toyota became the most frequently involved vehicle make in February 2025 with 16 vehicles, up from 11 in the prior year, while Chevrolet decreased from 12 to 5. The 45-54 age group saw an increase in persons involved from 12 to 19, whereas the 26-34 age group experienced a decrease from 20 to 16 persons. Honda maintained a consistent involvement with 8 vehicles in both periods.

Top Vehicle Makes (79 vehicles)

1
TOYOTA16 (20.3%)
45.5%prior 11
2
FORD11 (13.9%)
-8.3%prior 12
3
HONDA8 (10.1%)
0.0%prior 8
4
JEEP7 (8.9%)
5
NISSAN5 (6.3%)
-16.7%prior 6
6
CHEVROLET5 (6.3%)
-58.3%prior 12
7
SUBARU3 (3.8%)
8
LEXUS3 (3.8%)
9
MAZDA3 (3.8%)
10
VOLKSWAGEN2 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

Sex Distribution (94 persons with recorded sex)

Male61 (64.9%)
24.5%prior 49
Female33 (35.1%)
-26.7%prior 45

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 mph speed zone increased from 13 in February 2024 to 18 in February 2025. Conversely, crashes in the 45 mph speed zone decreased from 8 to 4, and the 30 mph zone saw a reduction from 3 to 2 crashes. There were no fatal crashes recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: RAYNHAM, MA
  • Total crash records analyzed: 45
  • Total persons involved: 96
  • Total vehicles involved: 79

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: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/raynham/february-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

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Raynham, MA Crash Report — February 2025 | ThatCarHitMe.com