Monthly Traffic Safety Analysis

23 CRASHES IN
MANSFIELD, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

In February 2025, MANSFIELD recorded 23 crashes, a 14.8% decrease from the 27 crashes reported in February 2024. A significant change observed was the absence of DUI-related crashes in the current period, down from 2 in the prior year.

23

-14.8%was 27

Total Crash Events

0

Persons Killed

7

16.7%was 6

Persons Injured

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 · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in MANSFIELD decreased year-over-year, falling by 14.8% from 27 crashes in February 2024 to 23 crashes in February 2025. Despite this reduction in total crashes, the number of injured persons increased by 16.7%, from 6 to 7.

1

Hit-and-Run Crashes — February 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained stable at 1 incident in both February 2025 and February 2024. However, due to a decrease in total crashes, the hit-and-run rate slightly increased from 3.7% in the prior period to 4.3% in the current period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 616.7%

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 temporal distribution of crashes showed shifts year-over-year. In February 2025, the peak day for crashes was Sunday with 7 incidents, a notable increase from the 1 crash on Sunday in February 2024, when Thursday was the peak day with 6 crashes. The peak hour for crashes also shifted, with 4 PM having 3 crashes in the current period, compared to 3 PM with 6 crashes in the prior period.

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

Fatal crashes remained at zero in both February 2025 and February 2024. The distribution of injury severity changed, with serious injuries remaining stable at 1 crash in both periods. Minor injury crashes decreased from 4 (14.8% share) in the prior period to 2 (8.7% share) in the current period, while possible injury crashes increased from 1 (3.7% share) to 4 (17.4% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes4.3%
0.0%prior 1
Minor Injury2minor injury crashes8.7%
-50.0%prior 4
Possible Injury4possible injury crashes17.4%
300.0%prior 1
No Injury16no injury crashes69.6%
-15.8%prior 19

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 leading contributing factors shifted significantly year-over-year. 'Followed too closely' decreased substantially from 9 crashes in February 2024 to 2 crashes in February 2025. Conversely, 'Inattention' increased from 1 crash to 4 crashes, and 'No improper driving' also rose from 1 crash to 4 crashes. 'Failure to keep in proper lane or running off road,' which accounted for 6 crashes in the prior period, was not among the top factors in the current period.

Officer-Reported Primary Contributing Cause

Inattention4 (17.4%)
No improper driving4 (17.4%)
Operating defective equipment2 (8.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (8.7%)
Driving too fast for conditions2 (8.7%)
Followed too closely2 (8.7%)-77.8%prior 9
Disregarded traffic signs, signals, road markings1 (4.3%)
Fatigued/asleep1 (4.3%)
Distracted1 (4.3%)

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

Crash conditions showed some changes year-over-year. While 'Clear' weather remained the most common condition, its associated crash count decreased from 22 in February 2024 to 11 in February 2025. Crashes occurring in 'Snow' conditions increased from 2 to 3. Similarly, 'Dry' road surface conditions saw a decrease in associated crashes from 24 to 16, while crashes on 'Snow' surfaces increased from 2 to 4.

Weather

Clear11 (47.8%)
-50.0%prior 22
Clear/Clear3 (13.0%)
Cloudy3 (13.0%)
Snow3 (13.0%)
Snow/Sleet, hail (freezing rain or drizzle)2 (8.7%)
Snow/Snow1 (4.3%)

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

Lighting

Daylight12 (52.2%)
-33.3%prior 18
Dark - lighted roadway5 (21.7%)
Dark - roadway not lighted3 (13.0%)
Dusk2 (8.7%)
Dawn1 (4.3%)

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

Road Surface

Dry16 (69.6%)
-33.3%prior 24
Snow4 (17.4%)
Wet2 (8.7%)
Slush1 (4.3%)

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

Vehicles & Demographics

Top Vehicle Makes (43 vehicles)

1
TOYOTA8 (18.6%)
-46.7%prior 15
2
FORD8 (18.6%)
3
HONDA6 (14%)
0.0%prior 6
4
CHEVROLET4 (9.3%)
5
VOLKSWAGEN3 (7%)
6
HYUNDAI3 (7%)
-50.0%prior 6
7
BMW2 (4.7%)
8
JEEP2 (4.7%)
9
NISSAN2 (4.7%)
-66.7%prior 6
10
FREIGHTLINER1 (2.3%)

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

2 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (45 persons with recorded sex)

Male28 (62.2%)
-9.7%prior 31
Female17 (37.8%)
-19.0%prior 21

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

The distribution of crashes across speed zones saw some shifts. Crashes in 65 mph zones decreased from 13 in February 2024 to 9 in February 2025. Conversely, crashes in 40 mph zones increased from 2 to 4, and in 45 mph zones from 1 to 2. All reported speed zones maintained a fatal crash rate of 0% in both periods.

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: MANSFIELD, MA
  • Total crash records analyzed: 23
  • Total persons involved: 47
  • Total vehicles involved: 43

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). "MANSFIELD, 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/mansfield/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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Mansfield, MA Crash Report — February 2025 | ThatCarHitMe.com