Monthly Traffic Safety Analysis

22 CRASHES IN
LEICESTER, MA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, LEICESTER experienced 22 crashes, a 29.41% increase compared to the 17 crashes reported in May 2024. Despite the rise in total crashes, total injuries saw a significant decrease, falling by 80% from 10 injuries in May 2024 to 2 injuries in May 2025. This indicates a shift towards less severe crash outcomes year-over-year.

22

▲ 29.4%was 17

Total Crash Events

0

Persons Killed

2

▼ -80.0%was 10

Persons Injured

0

Fatal Crash Events

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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in LEICESTER increased from 17 in May 2024 to 22 in May 2025, representing a 29.41% rise. Concurrently, total injuries decreased substantially by 80%, from 10 to 2, suggesting a trend towards crashes with fewer or less severe injuries. Fatalities remained at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

2

Motorists Injured

Prior: 10↓-80.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Friday in both periods, with 6 crashes reported on this day. However, the peak hour shifted from 9 p.m. with 2 crashes in May 2024 to 5 p.m. with 3 crashes in May 2025. Crashes on Mondays increased from 0 to 2, while crashes on Sundays decreased from 2 to 1.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both May 2024 and May 2025. Total injuries significantly decreased from 10 to 2, an 80% reduction year-over-year. Crashes resulting in serious injuries (A) fell from 1 to 0, and minor injuries (B) decreased from 5 to 1, while crashes with no injuries increased from 10 to 20.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes4.5%
↓-80.0%prior 5
No Injury20no injury crashes90.9%
↑100.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to 'No improper driving' increased from 3 in May 2024 to 7 in May 2025, a 133.3% increase. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' crashes also rose, from 1 to 3, a 200% increase. Conversely, 'Inattention' crashes decreased from 3 to 2, a 33.3% reduction, and 'Failed to yield right of way' was a factor in 2 crashes in May 2024 but none in May 2025.

Officer-Reported Primary Contributing Cause

No improper driving7 (31.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (13.6%)
Glare2 (9.1%)
Inattention2 (9.1%)
Distracted1 (4.5%)
Followed too closely1 (4.5%)
Driving too fast for conditions1 (4.5%)
Other improper action1 (4.5%)
Over-correcting/over-steering1 (4.5%)
Illness1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions decreased from 15 to 13, while 'Cloudy' crashes increased from 1 to 3, and 'Rain' crashes increased from 0 to 2. The number of crashes on 'Wet' road surfaces increased from 1 to 6, whereas crashes on 'Dry' road surfaces remained at 16. Crashes during 'Dark - lighted roadway' conditions increased from 3 to 5, and 'Dawn' and 'Dusk' conditions, not present in May 2024, accounted for 2 and 1 crash respectively in May 2025.

Weather

Clear13 (59.1%)
↓-13.3%prior 15
Cloudy3 (13.6%)
Rain2 (9.1%)
Rain/Fog, smog, smoke1 (4.5%)
Fog, smog, smoke1 (4.5%)
Cloudy/Rain1 (4.5%)
Rain/Cloudy1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight14 (63.6%)
→0.0%prior 14
Dark - lighted roadway5 (22.7%)
Dawn2 (9.1%)
Dusk1 (4.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry16 (72.7%)
→0.0%prior 16
Wet6 (27.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (39 vehicles)

1
FORD11 (28.2%)
↑83.3%prior 6
2
CHEVROLET4 (10.3%)
3
NISSAN3 (7.7%)
4
JEEP3 (7.7%)
5
TOYOTA3 (7.7%)
6
SUBARU2 (5.1%)
7
HONDA2 (5.1%)
8
MAZDA1 (2.6%)
9
MERCEDES-BENZ1 (2.6%)
10
OTH1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (45 persons with recorded sex)

Male30 (66.7%)
↑36.4%prior 22
Female15 (33.3%)
→0.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 MPH zones increased from 6 in May 2024 to 10 in May 2025, a 66.7% rise. Conversely, crashes in 35 MPH zones decreased from 7 to 4, a 42.9% reduction. Crashes in 45 MPH zones increased from 1 to 2, while new crashes were recorded in 25 MPH (2 crashes) and 50 MPH (1 crash) zones in May 2025, which had no reported crashes in May 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: LEICESTER, MA
  • Total crash records analyzed: 22
  • Total persons involved: 49
  • Total vehicles involved: 39

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). "LEICESTER, MA Crash Intelligence Report: May 2025." Published June 21, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leicester/may-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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Leicester, MA Crash Report — May 2025 | ThatCarHitMe.com