Yearly Traffic Safety Analysis

335 CRASHES IN
WRENTHAM, MA
2025

All metrics benchmarked against2024

In 2025, Wrentham recorded 335 total traffic crashes, a 15.4% decrease from the 396 crashes reported in 2024. Despite the overall decline in collisions, the number of fatalities increased from two in the prior year to three in the current year. This rise in fatalities occurred alongside a decrease in total injuries from 132 to 121.

335

-15.4%was 396

Total Crash Events

3

50.0%was 2

Persons Killed

121

-8.3%was 132

Persons Injured

19

-5.0%was 20

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 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

The overall trend in traffic collisions shows a year-over-year decrease, with total crashes falling by 15.4% from 396 in 2024 to 335 in 2025. Similarly, the number of people injured in these incidents declined by 8.3%, from 132 to 121. In contrast to this downward trend, the number of fatalities rose from two to three over the same period.

19

Hit-and-Run Crashes — 2025

-5.0% vs prior (20)

The total number of hit-and-run incidents remained relatively stable, decreasing by one from 20 in 2024 to 19 in 2025. However, due to the overall reduction in total crashes, the hit-and-run rate as a proportion of all collisions increased from 5.1% to 5.7% year-over-year. This indicates that hit-and-run events constituted a slightly larger share of total collisions in the more recent period.

Vulnerable Road User Casualties

3

Motorists Killed

Prior: 1200.0%

121

Motorists Injured

Prior: 130-6.9%

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

Temporal analysis reveals a shift in crash patterns between the two periods. The peak day for crashes moved from Saturday (73 crashes) in 2024 to Friday (65 crashes) in 2025. The peak hour also shifted from 2 p.m. in the prior year to 5 p.m. in the current year, aligning more closely with the evening commute.

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 overall number of crashes decreased, the number of fatal crashes increased from two in 2024 to three in 2025, raising the fatal crash rate from 0.5% to 0.9% of all crashes. The proportion of crashes resulting in serious injury decreased from 2.5% to 1.2%. The overall share of crashes involving any level of injury remained stable at 23% in both periods.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.9%
50.0%prior 2
Serious Injury4serious injury crashes1.2%
-60.0%prior 10
Minor Injury30minor injury crashes9%
-33.3%prior 45
Possible Injury43possible injury crashes12.8%
19.4%prior 36
No Injury252no injury crashes75.2%
-16.3%prior 301

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, with 'Followed too closely' becoming the most frequent factor in 2025 after its count increased from 59 to 66. Conversely, crashes involving 'Inattention' saw a significant drop in count from 67 to 41, moving it from the second-ranked factor to the fourth. The count for 'Failed to yield right of way' also decreased from 66 to 58.

Officer-Reported Primary Contributing Cause

Followed too closely66 (19.7%)11.9%prior 59
No improper driving60 (17.9%)-21.1%prior 76
Failed to yield right of way58 (17.3%)-12.1%prior 66
Inattention41 (12.2%)-38.8%prior 67
Failure to keep in proper lane or running off road20 (6%)-33.3%prior 30
Made an improper turn11 (3.3%)-8.3%prior 12
Disregarded traffic signs, signals, road markings10 (3%)-9.1%prior 11
Other improper action9 (2.7%)12.5%prior 8
Driving too fast for conditions7 (2.1%)-53.3%prior 15
Visibility obstructed6 (1.8%)

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

Crashes occurred under broadly similar environmental conditions across both years, with the proportion of crashes in adverse weather (not clear) stable at 26.3% for both periods. There was a slight decrease in the share of crashes occurring on non-dry road surfaces, which fell from 24.0% in 2024 to 20.3% in 2025. Similarly, crashes in non-daylight conditions decreased proportionally from 33.6% to 31.6%.

Weather

Clear157 (49.4%)
-20.3%prior 197
Clear/Clear90 (28.3%)
-5.3%prior 95
Rain22 (6.9%)
46.7%prior 15
Cloudy18 (5.7%)
20.0%prior 15
Cloudy/Cloudy5 (1.6%)
-16.7%prior 6
Snow5 (1.6%)
-37.5%prior 8
Cloudy/Rain4 (1.3%)
-33.3%prior 6
Snow/Snow3 (0.9%)
-50.0%prior 6
Rain/Rain3 (0.9%)
-62.5%prior 8
Sleet, hail (freezing rain or drizzle)/Rain2 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight229 (68.4%)
-12.9%prior 263
Dark - lighted roadway66 (19.7%)
4.8%prior 63
Dark - roadway not lighted25 (7.5%)
-47.9%prior 48
Dusk9 (2.7%)
-35.7%prior 14
Dawn4 (1.2%)
-42.9%prior 7
Dark - unknown roadway lighting2 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry267 (83.2%)
-11.3%prior 301
Wet39 (12.1%)
-35.0%prior 60
Snow9 (2.8%)
-40.0%prior 15
Slush3 (0.9%)
-50.0%prior 6
Ice2 (0.6%)
-71.4%prior 7
Sand, mud, dirt, oil, gravel1 (0.3%)

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 three vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford leading in both years, although the total number of vehicles from these makes decreased in 2025. The 26-34 age group represented the largest cohort of individuals involved in crashes for both periods, with its count dropping from 172 in 2024 to 127 in 2025. The number of persons in the 16-20 age group remained nearly unchanged, with 120 in 2025 compared to 119 in the prior year.

Top Vehicle Makes (643 vehicles)

1
TOYOTA107 (16.6%)
-4.5%prior 112
2
FORD68 (10.6%)
-11.7%prior 77
3
HONDA67 (10.4%)
-23.9%prior 88
4
NISSAN46 (7.2%)
-9.8%prior 51
5
CHEVROLET39 (6.1%)
-2.5%prior 40
6
HYUNDAI36 (5.6%)
-7.7%prior 39
7
JEEP33 (5.1%)
3.1%prior 32
8
GMC23 (3.6%)
-4.2%prior 24
9
SUBARU19 (3%)
-32.1%prior 28
10
VOLKSWAGEN18 (2.8%)
-18.2%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (772 persons with recorded sex)

Male453 (58.7%)
-7.7%prior 491
Female318 (41.2%)
-17.0%prior 383
X / Unspecified1 (0.1%)
0.0%prior 1

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 65 mph speed zone accounted for the highest number of crashes in both periods, though the count decreased from 60 in 2024 to 52 in 2025. In 2024, both fatal crashes with a recorded speed limit occurred in the 55 mph zone. In 2025, fatal crashes shifted to other zones, with one occurring in a 45 mph zone and another in a 65 mph zone.

Fatal crashes by zone: 45 mph: 1 of 20 (5%) · 65 mph: 1 of 52 (1.923%)

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: WRENTHAM, MA
  • Total crash records analyzed: 335
  • Total persons involved: 833
  • Total vehicles involved: 643

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). "WRENTHAM, 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/wrentham/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

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Wrentham, MA Crash Report — 2025 | ThatCarHitMe.com