ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LEOMINSTER, MA · JUNE 2024
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/june-2024-report
Monthly Traffic Safety Analysis
101 CRASHES IN
LEOMINSTER, MA
JUNE 2024
In June 2024, LEOMINSTER, MA experienced 101 crashes, an increase from the 89 crashes recorded in June 2023. This represents a 13.48% rise in total crashes year-over-year. A notable change was the 100% decrease in speeding-related crashes, falling from 5 in the prior period to 0 in the current period.
101
▲ 13.5%was 89
Total Crash Events
0
Persons Killed
35
▲ 25.0%was 28
Persons Injured
7
▼ -12.5%was 8
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 · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crash activity in LEOMINSTER, MA showed an upward trend year-over-year. Total crashes increased by 12, rising from 89 in June 2023 to 101 in June 2024, a 13.48% increase. Concurrently, total injuries also saw an increase, climbing by 7 from 28 to 35, marking a 25% rise.
7
Hit-and-Run Crashes — June 2024
▼ -12.5% vs prior (8)
Hit-and-run crashes decreased from 8 in June 2023 to 7 in June 2024. The hit-and-run rate also saw a decline, falling from 9% of total crashes in the prior period to 6.9% in the current period. This indicates a downward trend in hit-and-run incidents year-over-year.
Vulnerable Road User Casualties
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
1
Cyclists Injured
32
Motorists Injured
2
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal distribution of crashes shifted year-over-year. In June 2023, Friday was the peak day with 21 crashes, while in June 2024, Tuesday became the peak day with 17 crashes. The peak hour for crashes also changed, moving from 3 p.m. with 12 crashes in the prior period to 1 p.m. with 13 crashes in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both June 2023 and June 2024. However, there was an increase in serious injury crashes, rising from 0 in the prior period to 2 in the current period. Minor injury crashes saw a slight decrease in their proportion of total crashes, from 13.5% in June 2023 to 12.9% in June 2024, while possible injury crashes increased from 5.6% to 8.9%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record
Top Contributing Factors
Inattention remained the leading contributing factor, increasing significantly from 19 crashes in June 2023 to 34 crashes in June 2024, a 78.9% increase. Conversely, crashes attributed to 'Failed to yield right of way' decreased from 18 to 11, a 38.9% reduction. 'Followed too closely' crashes increased from 8 to 11, a 37.5% rise, while 'No improper driving' crashes slightly decreased from 13 to 12.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring under clear weather conditions increased from 56 in June 2023 to 87 in June 2024. Correspondingly, crashes during rainy conditions decreased from 8 to 2, and cloudy/rainy conditions decreased from 5 to 3. The number of crashes on dry road surfaces increased from 74 to 93, while crashes on wet surfaces decreased from 15 to 8.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 25, from 170 in June 2023 to 195 in June 2024. Toyota remained the most common vehicle make involved, increasing from 22 to 25. Notably, Ford-involved crashes rose by 8 (from 16 to 24), and Nissan-involved crashes increased by 9 (from 10 to 19), while Hyundai-involved crashes decreased by 9 (from 17 to 8).
Top Vehicle Makes (195 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records
12 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (243 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · Person-level records linked to crash events
Speed Limit Zones
Crashes in 30 mph zones slightly decreased from 42 in June 2023 to 40 in June 2024. Conversely, crashes in 35 mph zones saw a significant increase, rising from 17 to 29. Crashes in 25 mph zones also increased from 11 to 12, while those in 55 mph zones decreased from 11 to 10. Fatal crashes remained at zero across all speed zones in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-06-01 through 2024-06-30 (30 days)
- Geographic scope: LEOMINSTER, MA
- Total crash records analyzed: 101
- Total persons involved: 259
- Total vehicles involved: 195
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: June 2024." Published June 21, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/june-2024-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: 2024-06-01 – 2024-06-30
Generated: June 21, 2026 · All rights reserved