Monthly Traffic Safety Analysis

89 CRASHES IN
LEOMINSTER, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, LEOMINSTER, MA experienced 89 total crashes, a decrease from 111 crashes in November 2024, representing a 19.8% reduction. Total injuries also saw a significant decline, falling by 34.2% from 41 in the prior period to 27 in the current period. Fatalities remained at zero in both comparative periods.

89

▼ -19.8%was 111

Total Crash Events

0

Persons Killed

27

▼ -34.1%was 41

Persons Injured

4

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. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a decrease in crash incidents year-over-year, with total crashes falling from 111 in November 2024 to 89 in November 2025. This represents a reduction of 22 crashes, or a 19.8% decline in total crashes.

4

Hit-and-Run Crashes — November 2025

▼ 0.0% vs prior (4)

The number of hit-and-run crashes remained constant at 4 in both November 2024 and November 2025. However, the hit-and-run crash rate increased from 3.6% in the prior period to 4.5% in the current period, due to a decrease in the overall number of crashes.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

27

Motorists Injured

Prior: 41↓-34.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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 Tuesday, with 21 crashes in November 2024, to Saturday, with 18 crashes in November 2025. Similarly, the peak hour for crashes moved from 5 PM, which recorded 14 crashes in the prior period, to 12 PM, with 13 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at zero in both November 2024 and November 2025. Serious injury crashes (severity A) decreased from 3 crashes (2.7% of total) in the prior period to 1 crash (1.1% of total) in the current period. Minor injury crashes (severity B) also saw a reduction from 20 crashes (18% of total) to 13 crashes (14.6% of total) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes1.1%
↓-66.7%prior 3
Minor Injury13minor injury crashes14.6%
↓-35.0%prior 20
Possible Injury3possible injury crashes3.4%
↓-62.5%prior 8
No Injury69no injury crashes77.5%
↓-11.5%prior 78

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, "Inattention," decreased from 27 crashes in November 2024 to 24 crashes in November 2025. "Failed to yield right of way" also saw a reduction from 21 crashes to 16 crashes. Conversely, crashes attributed to "Disregarded traffic signs, signals, road markings" increased from 5 crashes in the prior period to 7 crashes in the current period.

Officer-Reported Primary Contributing Cause

Inattention24 (27%)↓-11.1%prior 27
Failed to yield right of way16 (18%)↓-23.8%prior 21
Followed too closely11 (12.4%)↓-15.4%prior 13
No improper driving9 (10.1%)↑12.5%prior 8
Disregarded traffic signs, signals, road markings7 (7.9%)↑40.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway4 (4.5%)
Failure to keep in proper lane or running off road3 (3.4%)↓-57.1%prior 7
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (3.4%)
Visibility obstructed2 (2.2%)
Driving too fast for conditions1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 80 in November 2024 to 66 in November 2025. Crashes on dry road surfaces also saw a reduction, from 94 to 78. A notable shift was observed in crashes occurring in "Dark - roadway not lighted" conditions, which decreased from 12 in the prior period to 3 in the current period.

Weather

Clear66 (75.0%)
↓-17.5%prior 80
Cloudy9 (10.2%)
↓-18.2%prior 11
Clear/Clear5 (5.7%)
→0.0%prior 5
Rain3 (3.4%)
↓-57.1%prior 7
Snow2 (2.3%)
Clear/Rain1 (1.1%)
Cloudy/Rain1 (1.1%)
Rain/Severe crosswinds1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight52 (59.8%)
↓-22.4%prior 67
Dark - lighted roadway27 (31.0%)
↓-10.0%prior 30
Dark - roadway not lighted3 (3.4%)
↓-75.0%prior 12
Dusk3 (3.4%)
Dawn2 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry78 (87.6%)
↓-17.0%prior 94
Wet7 (7.9%)
↓-53.3%prior 15
Ice3 (3.4%)
Snow1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

The total number of persons involved in crashes decreased from 275 in November 2024 to 228 in November 2025. The 35-44 age group saw a reduction in involvement, from 52 persons in the prior period to 31 persons in the current period. Toyota became the top vehicle make involved in crashes, with 41 vehicles in November 2025, compared to 23 in the prior year when Honda was the top make.

Top Vehicle Makes (167 vehicles)

1
TOYOTA41 (24.6%)
↑78.3%prior 23
2
HONDA17 (10.2%)
↓-39.3%prior 28
3
NISSAN14 (8.4%)
→0.0%prior 14
4
FORD12 (7.2%)
↓-42.9%prior 21
5
SUBARU11 (6.6%)
↓-26.7%prior 15
6
CHEVROLET11 (6.6%)
↓-26.7%prior 15
7
JEEP8 (4.8%)
↓-27.3%prior 11
8
VOLKSWAGEN7 (4.2%)
↑16.7%prior 6
9
HYUNDAI5 (3%)
↓-61.5%prior 13
10
KIA5 (3%)
→0.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (218 persons with recorded sex)

Male119 (54.6%)
↓-15.6%prior 141
Female99 (45.4%)
↓-14.7%prior 116

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

No fatal crashes were recorded in any speed zone during either period. Crashes in 30 mph zones increased from 37 in November 2024 to 44 in November 2025. Conversely, crashes in 35 mph zones decreased from 39 to 22, and crashes in 55 mph zones decreased from 10 to 6 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: LEOMINSTER, MA
  • Total crash records analyzed: 89
  • Total persons involved: 228
  • Total vehicles involved: 167

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). "LEOMINSTER, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/november-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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Leominster, MA Crash Report — November 2025 | ThatCarHitMe.com