Monthly Traffic Safety Analysis

53 CRASHES IN
WILMINGTON, MA
JANUARY 2025

All metrics benchmarked againstJanuary 2024

In January 2025, Wilmington experienced 53 total crashes, a slight decrease from the 54 crashes recorded in January 2024, representing a 1.85% reduction. Total injuries also decreased by 25%, from 12 to 9. The most notable year-over-year shift was the absence of hit-and-run crashes in January 2025, compared to 7 in the prior year.

53

-1.9%was 54

Total Crash Events

0

Persons Killed

9

-25.0%was 12

Persons Injured

0

-100.0%was 7

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 · 2025-01-01 to 2025-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in January 2025 showed a slight decrease compared to January 2024. Total crashes decreased by 1.85%, from 54 to 53. This reduction was accompanied by a 25% decrease in total injuries, falling from 12 to 9.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 12-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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 Wednesday, with 13 crashes in January 2024, to Saturday, with 14 crashes in January 2025. Similarly, the peak hour for crashes changed from 2 PM (9 crashes) in January 2024 to 8 AM (8 crashes) in January 2025. This indicates a shift in the most common times and days for crash occurrences.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both January 2024 and January 2025 recorded zero traffic fatalities. Total injuries decreased by 25%, from 12 in January 2024 to 9 in January 2025. The proportion of minor injuries decreased from 16.7% (9 crashes) to 15.1% (8 crashes), while possible injuries decreased from 3.7% (2 crashes) to 1.9% (1 crash).

Outcome by Severity (Crash Events)

Minor Injury8minor injury crashes15.1%
-11.1%prior 9
Possible Injury1possible injury crashes1.9%
-50.0%prior 2
No Injury44no injury crashes83%
2.3%prior 43

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Most severe injury per crash record

Top Contributing Factors

Inattention became the leading contributing factor in January 2025 with 10 crashes, up from 8 crashes in January 2024, a 25% increase in count. Failed to yield right of way also saw a significant increase, rising from 6 crashes to 9 crashes, a 50% increase in count. Conversely, crashes attributed to 'No improper driving' decreased from 11 to 9, an 18.2% decrease in count, and 'Distracted' crashes decreased from 4 to 1, a 75% decrease in count.

Officer-Reported Primary Contributing Cause

Inattention10 (18.9%)25.0%prior 8
No improper driving9 (17%)-18.2%prior 11
Failed to yield right of way9 (17%)50.0%prior 6
Driving too fast for conditions5 (9.4%)0.0%prior 5
Followed too closely4 (7.5%)
Failure to keep in proper lane or running off road3 (5.7%)
Visibility obstructed2 (3.8%)
Fatigued/asleep2 (3.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.8%)
Exceeded authorized speed limit1 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on dry road surfaces increased from 27 in January 2024 to 36 in January 2025. Conversely, crashes on wet road surfaces saw a substantial decrease, falling from 19 to 5. While clear weather conditions remained the most common factor (30 vs 29 crashes), crashes during 'Dark - roadway not lighted' conditions decreased from 9 to 4.

Weather

Clear29 (54.7%)
-3.3%prior 30
Snow/Cloudy4 (7.5%)
Snow/Sleet, hail (freezing rain or drizzle)3 (5.7%)
Snow3 (5.7%)
-50.0%prior 6
Cloudy/Cloudy3 (5.7%)
Cloudy3 (5.7%)
-50.0%prior 6
Clear/Clear3 (5.7%)
Cloudy/Snow2 (3.8%)
Rain1 (1.9%)
-83.3%prior 6
Clear/Cloudy1 (1.9%)

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

Lighting

Daylight29 (54.7%)
7.4%prior 27
Dark - lighted roadway14 (26.4%)
-6.7%prior 15
Dark - roadway not lighted4 (7.5%)
-55.6%prior 9
Dawn4 (7.5%)
Dusk2 (3.8%)

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

Road Surface

Dry36 (67.9%)
33.3%prior 27
Snow10 (18.9%)
100.0%prior 5
Wet5 (9.4%)
-73.7%prior 19
Ice2 (3.8%)

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

Vehicles & Demographics

Toyota remained the most common vehicle make involved in crashes, with 18 vehicles in January 2025 compared to 17 in January 2024. Honda vehicles involved in crashes nearly doubled, increasing from 9 to 17, moving it to the second most common make. The number of persons aged 65 and older involved in crashes decreased from 15 to 9, while those aged 21-25 increased from 18 to 23.

Top Vehicle Makes (96 vehicles)

1
TOYOTA18 (18.8%)
5.9%prior 17
2
HONDA17 (17.7%)
88.9%prior 9
3
FORD14 (14.6%)
-6.7%prior 15
4
CHEVROLET7 (7.3%)
-30.0%prior 10
5
JEEP5 (5.2%)
6
FRHT4 (4.2%)
7
NISSAN4 (4.2%)
-42.9%prior 7
8
SUBARU3 (3.1%)
9
GMC3 (3.1%)
10
STRN2 (2.1%)

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

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

Sex Distribution (115 persons with recorded sex)

Male73 (63.5%)
4.3%prior 70
Female42 (36.5%)
7.7%prior 39

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · Person-level records linked to crash events

Speed Limit Zones

The number of crashes occurring in 35 MPH speed zones slightly increased from 16 in January 2024 to 17 in January 2025. Crashes in 65 MPH zones remained consistent at 17 for both periods. A notable decrease was observed in 30 MPH zones, which went from 9 crashes to 4 crashes. No fatalities were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-01-31 · 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: 2025-01-01 through 2025-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-01-31 (31 days)
  • Geographic scope: WILMINGTON, MA
  • Total crash records analyzed: 53
  • Total persons involved: 115
  • Total vehicles involved: 96

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). "WILMINGTON, MA Crash Intelligence Report: January 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/wilmington/january-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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Wilmington, MA Crash Report — January 2025 | ThatCarHitMe.com