ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LEOMINSTER, MA · AUGUST 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/leominster/august-2025-report
Monthly Traffic Safety Analysis
83 CRASHES IN
LEOMINSTER, MA
AUGUST 2025
Total crashes in Leominster decreased by 19.4% year-over-year, from 103 crashes in August 2024 to 83 crashes in August 2025. This period also saw a significant reduction in serious injuries, which fell by 83.3% from 6 to 1. Overall, the data indicates a notable decrease in crash frequency and severity.
83
▼ -19.4%was 103
Total Crash Events
0
Persons Killed
29
▼ -9.4%was 32
Persons Injured
6
▲ 50.0%was 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. 1 crash with unreported severity is not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Leominster show a downward trend year-over-year, with total crashes decreasing from 103 in August 2024 to 83 in August 2025. This represents a 19.4% reduction in the total number of crashes. The number of injured persons also decreased by 9.4%, from 32 to 29.
6
Hit-and-Run Crashes — August 2025
▲ 50.0% vs prior (4)
Hit-and-run crashes increased year-over-year, rising from 4 in August 2024 to 6 in August 2025. This represents a 50% increase in the count of hit-and-run incidents. The hit-and-run rate also increased from 3.9% of total crashes to 7.2%.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
27
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · 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, though the count decreased from 20 in August 2024 to 16 in August 2025. The peak hour for crashes shifted from 3 p.m. in August 2024 (20 crashes) to 4 p.m. in August 2025 (9 crashes), indicating a change in the highest-frequency hour and a reduction in crash volume during that peak.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatalities reported in either August 2024 or August 2025. Total injuries decreased by 9.4%, from 32 to 29. Notably, serious injuries (Severity A) saw an 83.3% reduction, decreasing from 6 in August 2024 to 1 in August 2025, while possible injuries (Severity C) increased from 5 to 8.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Most severe injury per crash record
Top Contributing Factors
The top contributing factor shifted from 'Failed to yield right of way' in August 2024 to 'Inattention' in August 2025. Crashes attributed to 'Failed to yield right of way' decreased by 15, from 25 to 10, while 'Inattention' increased by 10 crashes, from 19 to 29. 'Followed too closely' also saw a decrease of 5 crashes, from 13 to 8.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions saw a decrease in count from 77 to 68, but the proportion of crashes in clear weather increased from 74.8% to 81.9%. Similarly, the proportion of crashes on dry road surfaces increased from 85.4% to 94.0%, despite a decrease in count from 88 to 78. Crashes occurring in daylight decreased from 88 to 61, and their proportion dropped from 85.4% to 73.5%.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes decreased from 201 to 160 year-over-year. Honda became the most frequently involved vehicle make, with its count increasing from 19 to 29, while Toyota, previously first, saw its count decrease from 37 to 20. Nissan also saw a decrease in involvement from 18 to 13.
Top Vehicle Makes (160 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (183 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Person-level records linked to crash events
Speed Limit Zones
There was a notable shift in crashes occurring at higher speed limits, with crashes at 35 mph decreasing by 16 (from 33 to 17) and crashes at 55 mph decreasing by 10 (from 17 to 7). Conversely, crashes at 25 mph increased by 3, from 15 to 18. No fatal crashes were reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · 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: 2025-08-01 through 2025-08-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-08-01 through 2025-08-31 (31 days)
- Geographic scope: LEOMINSTER, MA
- Total crash records analyzed: 83
- Total persons involved: 205
- Total vehicles involved: 160
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: August 2025." Published June 21, 2026. Reporting period: 2025-08-01 to 2025-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/august-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-08-01 – 2025-08-31
Generated: June 21, 2026 · All rights reserved