ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · LEOMINSTER, MA · FEBRUARY 2022
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/february-2022-report
Monthly Traffic Safety Analysis
120 CRASHES IN
LEOMINSTER, MA
FEBRUARY 2022
In February 2022, LEOMINSTER recorded 120 crashes, a significant increase from the 86 crashes reported in February 2021. This represents a 39.5% rise in total crash incidents year-over-year. A notable change was the 400% increase in DUI-related crashes, rising from 1 to 5 incidents.
120
▲ 39.5%was 86
Total Crash Events
0
Persons Killed
37
▲ 76.2%was 21
Persons Injured
3
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 · 2022-02-01 to 2022-02-28 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash activity in LEOMINSTER shows an upward trend, with total crashes increasing by 39.5% from 86 in February 2021 to 120 in February 2022. Concurrently, total injuries rose by 76.2%, from 21 to 37, indicating a worsening safety trend year-over-year.
3
Hit-and-Run Crashes — February 2022
▼ 0.0% vs prior (3)
The number of hit-and-run crashes remained constant at 3 incidents in both February 2021 and February 2022. However, due to the overall increase in total crashes, the hit-and-run rate decreased from 3.5% in the prior period to 2.5% in the current period.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
35
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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 Thursday in February 2021 (22 crashes) to Saturday in February 2022 (28 crashes). While the peak hour count remained 13 crashes, the peak time moved from 3 PM in the prior period to 12 PM in the current period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Fatal crashes remained at zero in both February 2021 and February 2022. However, the proportion of crashes resulting in any injury (A, B, or C severity) increased from 16.3% (14 crashes) in the prior period to 26.7% (32 crashes) in the current period. Notably, serious injury crashes, which were absent in February 2021, accounted for 4 incidents in February 2022.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factor shifted from 'Failed to yield right of way' in February 2021 (17 crashes, 19.8% share) to 'Inattention' in February 2022 (25 crashes, 20.8% share), representing a 66.7% increase in inattention-related crash counts. 'No improper driving' saw the largest percentage increase, rising 185.7% from 7 crashes to 20 crashes, and its share of total crashes grew from 8.1% to 16.7%. Conversely, 'Failed to yield right of way' crashes decreased by 17.6% in count, from 17 to 14, and 'Followed too closely' crashes decreased by 8.3%, from 12 to 11.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather increased from 38 incidents (44.2% share) in February 2021 to 77 incidents (64.2% share) in February 2022. Similarly, dry road crashes rose from 44 (51.2% share) to 76 (63.3% share) year-over-year. Conversely, crashes on snowy roads decreased from 23 to 13, while crashes on icy roads saw a significant increase from 2 to 16 incidents.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford ranking among the highest in both periods, all showing an increase in incident counts. Toyota saw an increase from 24 to 35 vehicles, and Honda from 19 to 29. Regarding person demographics, the 16-20 age group experienced a substantial increase in involvement, rising from 21 persons in February 2021 to 41 persons in February 2022, while the 0-15 age group slightly decreased from 9 to 8.
Top Vehicle Makes (229 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Vehicle unit records
13 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (262 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · Person-level records linked to crash events
Speed Limit Zones
No fatal crashes were recorded in any speed zone during either period. Crashes in 25 mph zones increased from 20 in February 2021 to 34 in February 2022, and 35 mph zones saw a rise from 17 to 31 crashes. Conversely, crashes in 30 mph zones decreased from 37 to 31 incidents year-over-year, while 55 mph zones experienced an increase from 6 to 13 crashes.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-02-01 to 2022-02-28 · 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: 2022-02-01 through 2022-02-28
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-02-01 through 2022-02-28 (28 days)
- Geographic scope: LEOMINSTER, MA
- Total crash records analyzed: 120
- Total persons involved: 280
- Total vehicles involved: 229
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: February 2022." Published June 21, 2026. Reporting period: 2022-02-01 to 2022-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/february-2022-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: 2022-02-01 – 2022-02-28
Generated: June 21, 2026 · All rights reserved