Monthly Traffic Safety Analysis

14 CRASHES IN
LEICESTER, MA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, LEICESTER, MA experienced 14 total crashes, a 22.22% decrease from the 18 crashes reported in June 2024. Despite the reduction in total crashes, the number of injured persons increased by 120%, rising from 5 in the prior period to 11 in the current period. This indicates a notable shift towards more injury-involved incidents year-over-year.

14

-22.2%was 18

Total Crash Events

0

Persons Killed

11

120.0%was 5

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in LEICESTER, MA showed a downward trend, decreasing by 22.22% from 18 crashes in June 2024 to 14 crashes in June 2025. However, total injuries significantly increased by 120%, rising from 5 injured persons in June 2024 to 11 injured persons in June 2025. This suggests that while crash frequency decreased, the severity of outcomes for individuals involved in crashes intensified.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

10

Motorists Injured

Prior: 5100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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 Saturday, with 7 crashes in June 2024, to Sunday, with 5 crashes in June 2025. Similarly, the peak hour for crashes changed from 4 PM, with 4 crashes in the prior period, to 12 PM, with 3 crashes in the current period. This indicates a shift in the most frequent times for crashes, moving from late afternoon on Saturdays to midday on Sundays.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either June 2024 or June 2025. However, total injuries increased by 120%, from 5 injured persons in the prior period to 11 in the current period. In June 2025, 1 crash resulted in a serious injury and 5 crashes resulted in minor injuries, whereas in June 2024, 3 crashes resulted in minor injuries and no serious injuries were reported.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes7.1%
Minor Injury5minor injury crashes35.7%
66.7%prior 3
Possible Injury2possible injury crashes14.3%
No Injury6no injury crashes42.9%
-60.0%prior 15

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor shifted from "Inattention," accounting for 6 crashes in June 2024, to "No improper driving," cited in 5 crashes in June 2025. Crashes attributed to "Inattention" decreased by 50% in count, from 6 in the prior period to 3 in the current period. Conversely, crashes where "No improper driving" was cited increased by 25% in count, from 4 to 5.

Officer-Reported Primary Contributing Cause

No improper driving5 (35.7%)
Inattention3 (21.4%)-50.0%prior 6
Fatigued/asleep1 (7.1%)
Followed too closely1 (7.1%)
Over-correcting/over-steering1 (7.1%)
Disregarded traffic signs, signals, road markings1 (7.1%)
Wrong side or wrong way1 (7.1%)
Failure to keep in proper lane or running off road1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring under adverse weather conditions decreased, with 3 such incidents (2 Clear/Cloudy, 1 Rain) in June 2024 compared to 1 (Cloudy/Rain) in June 2025. Similarly, crashes in low light conditions decreased from 2 (1 Dawn, 1 Dusk) in the prior period to 1 (Dark - roadway not lighted) in the current period. The number of crashes on wet road surfaces remained consistent at 1 for both periods.

Weather

Clear13 (92.9%)
-13.3%prior 15
Cloudy/Rain1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight13 (92.9%)
-18.8%prior 16
Dark - roadway not lighted1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry13 (92.9%)
-23.5%prior 17
Wet1 (7.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (25 vehicles)

1
TOYOTA5 (20%)
2
HONDA4 (16%)
3
SUBARU3 (12%)
4
NISSAN2 (8%)
5
JEEP2 (8%)
6
FORD2 (8%)
-71.4%prior 7
7
SUZI1 (4%)
8
MITS1 (4%)
9
CHEVROLET1 (4%)
10
LEXUS1 (4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

Sex Distribution (36 persons with recorded sex)

Female19 (52.8%)
-20.8%prior 24
Male17 (47.2%)
21.4%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones shifted year-over-year. In June 2025, crashes were recorded in 15 mph and 20 mph zones, which were not present in June 2024. Conversely, crashes in 25 mph and 45 mph zones, present in June 2024, were absent in June 2025. The highest number of crashes in both periods occurred in the 30-35 mph range, with 8 crashes at 35 mph in June 2025 and 7 crashes at 35 mph and 6 crashes at 30 mph in June 2024.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: LEICESTER, MA
  • Total crash records analyzed: 14
  • Total persons involved: 37
  • Total vehicles involved: 25

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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leicester/june-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 — June 2025 | ThatCarHitMe.com