Monthly Traffic Safety Analysis

37 CRASHES IN
WRENTHAM, MA
JANUARY 2026

All metrics benchmarked againstJanuary 2025

Total crashes in Wrentham increased by 60.87% year-over-year, rising from 23 crashes in January 2025 to 37 crashes in January 2026. This period also saw a significant increase in total injuries, which grew from 3 to 21. The most notable shift was the substantial increase in crashes resulting in injuries.

37

60.9%was 23

Total Crash Events

0

Persons Killed

21

600.0%was 3

Persons Injured

2

-33.3%was 3

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 · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant increase in crash activity in Wrentham, with total crashes rising from 23 to 37, representing a 60.87% increase. Concurrently, total injuries surged from 3 in January 2025 to 21 in January 2026, marking a 600% increase. These figures suggest a notable worsening of crash outcomes and frequency.

2

Hit-and-Run Crashes — January 2026

-33.3% vs prior (3)

Hit-and-run crashes decreased from 3 in January 2025 to 2 in January 2026. Consequently, the hit-and-run rate also saw a decline, dropping from 13% in the prior period to 5.4% in the current period. This indicates a downward trend in the proportion of crashes involving a hit-and-run.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

21

Motorists Injured

Prior: 3600.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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 Friday in January 2025 (6 crashes) to Thursday in January 2026 (11 crashes), indicating a change in the busiest day for incidents. The peak hour also changed from 6 PM (4 crashes) in the prior period to 2 PM (5 crashes) in the current period. Notably, crashes occurring on Thursday more than doubled, increasing from 4 to 11.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes reported in either January 2025 or January 2026. However, total injuries increased substantially from 3 to 21 year-over-year. The proportion of crashes involving any injury (Minor or Possible) rose from 13% in January 2025 to 35.1% in January 2026.

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes16.2%
Possible Injury7possible injury crashes18.9%
133.3%prior 3
No Injury24no injury crashes64.9%
20.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from 'Followed too closely' (6 crashes) in January 2025 to 'Failed to yield right of way' (6 crashes) in January 2026. Crashes attributed to 'Failed to yield right of way' saw a count increase from 1 to 6, while 'Driving too fast for conditions' increased from 0 to 4 crashes. Conversely, 'Followed too closely' incidents decreased slightly from 6 to 5 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way6 (16.2%)
Failure to keep in proper lane or running off road5 (13.5%)
No improper driving5 (13.5%)0.0%prior 5
Followed too closely5 (13.5%)-16.7%prior 6
Driving too fast for conditions4 (10.8%)
Made an improper turn3 (8.1%)
Disregarded traffic signs, signals, road markings2 (5.4%)
Other improper action1 (2.7%)
Physical impairment1 (2.7%)
Inattention1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in adverse road surface conditions, such as wet, snow, ice, or slush, increased significantly from 3 in January 2025 to 18 in January 2026. Specifically, wet road crashes increased from 1 to 7, and snow-related road surface crashes rose from 1 to 6. Crashes during daylight hours increased from 12 to 22, while crashes in dark, unlighted conditions rose from 3 to 8.

Weather

Clear17 (45.9%)
6.3%prior 16
Clear/Clear10 (27.0%)
Snow3 (8.1%)
Snow/Sleet, hail (freezing rain or drizzle)2 (5.4%)
Cloudy/Cloudy2 (5.4%)
Snow/Blowing sand, snow2 (5.4%)
Rain1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash

Lighting

Daylight22 (59.5%)
83.3%prior 12
Dark - roadway not lighted8 (21.6%)
Dark - lighted roadway7 (18.9%)
0.0%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field

Road Surface

Dry19 (51.4%)
0.0%prior 19
Wet7 (18.9%)
Snow6 (16.2%)
Ice3 (8.1%)
Slush2 (5.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (71 vehicles)

1
TOYOTA13 (18.3%)
85.7%prior 7
2
FORD9 (12.7%)
12.5%prior 8
3
HONDA7 (9.9%)
4
NISSAN5 (7%)
5
HYUNDAI4 (5.6%)
6
SUBARU4 (5.6%)
7
LEXUS3 (4.2%)
8
JEEP3 (4.2%)
9
CHEVROLET3 (4.2%)
10
VOLKSWAGEN2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records

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

Sex Distribution (81 persons with recorded sex)

Male46 (56.8%)
70.4%prior 27
Female35 (43.2%)
66.7%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph zones saw the largest increase, rising from 1 crash in January 2025 to 5 crashes in January 2026. Crashes in 55 mph zones also increased, from 4 to 6. Conversely, crashes in 40 mph zones decreased from 5 to 4, and 35 mph zones decreased from 2 to 1.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2026-01-01 through 2026-01-31 (31 days)
  • Geographic scope: WRENTHAM, MA
  • Total crash records analyzed: 37
  • Total persons involved: 86
  • 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). "WRENTHAM, MA Crash Intelligence Report: January 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wrentham/january-2026-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 — January 2026 | ThatCarHitMe.com