ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LEOMINSTER, MA · 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/2024-annual-report
Yearly Traffic Safety Analysis
1,168 CRASHES IN
LEOMINSTER, MA
2024
In Leominster, total vehicle crashes remained relatively stable, increasing by 1.1% from 1,155 in 2023 to 1,168 in 2024. The total number of injuries also saw a slight increase from 325 to 328. The most significant year-over-year change was the recording of one fatality in 2024, following a year with zero fatalities.
1,168
▲ 1.1%was 1,155
Total Crash Events
1
Persons Killed
328
▲ 0.9%was 325
Persons Injured
45
▼ -22.4%was 58
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 11 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic crash trends in Leominster show a slight increase between 2023 and 2024. Total collisions rose from 1,155 to 1,168, and injuries increased from 325 to 328. The emergence of a fatal crash in 2024 marks a notable departure from the prior year, which had none.
45
Hit-and-Run Crashes — 2024
▼ -22.4% vs prior (58)
Hit-and-run crashes decreased from 2023 to 2024. The total count of such incidents fell from 58 to 45. This decline is also reflected in the hit-and-run rate, which dropped from 5.0% of all crashes in 2023 to 3.9% in 2024.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
0
Other Killed
4
Pedestrians Injured
12
Cyclists Injured
307
Motorists Injured
5
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes remained consistent year-over-year. The afternoon commute hour of 3 PM was the peak time for collisions in both 2024 and 2023, with 105 and 107 crashes respectively. Wednesday was the most frequent day for crashes in 2024 with 197 incidents, closely mirroring the prior year where Wednesday and Thursday were tied as the peak days with 193 crashes each.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity saw a notable shift with one fatal crash occurring in 2024, whereas none were recorded in 2023. The number of crashes involving serious injuries decreased from 33 to 28. However, there was a significant increase in crashes resulting in minor injuries, which rose from 104 in 2023 to 159 in 2024.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors to crashes were identical in both periods: "Inattention," "Failed to yield right of way," and "Followed too closely." The count of crashes attributed to inattention increased slightly from 303 to 309. Notably, crashes linked to a driver being "Distracted" saw a 39.6% decrease in count from 53 to 32, while crashes involving an "Improper turn" more than doubled in count from 7 to 16.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
A larger proportion of crashes in 2024 occurred under favorable conditions compared to 2023. Collisions on dry roads increased from 77.2% to 81.2% of the total, while crashes in daylight grew from 71.3% to 74.9% of all incidents. Correspondingly, the share of crashes on wet roads and on dark, lighted roadways both decreased from the prior year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes were Toyota, Ford, and Honda in both years, with only a minor shuffle in rank between Ford and Honda. An analysis of persons involved in crashes reveals an increase in the 35-44 and 65+ age groups from 2023 to 2024. The number of people aged 35-44 involved in crashes grew from 422 to 480, and for the 65+ group, the count rose from 286 to 355.
Top Vehicle Makes (2,221 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
136 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (2,776 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
Most crashes in both years occurred in 30 mph zones, although the count in this zone declined from 526 to 507. Crashes increased in 25 mph zones (from 159 to 179) and 35 mph zones (from 251 to 273). The single fatal crash recorded in 2024 took place in a 25 mph zone, a zone which had no fatalities in the previous year.
Fatal crashes by zone: 25 mph: 1 of 179 (0.559%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: LEOMINSTER, MA
- Total crash records analyzed: 1,168
- Total persons involved: 2,946
- Total vehicles involved: 2,221
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/2024-annual-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: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved