Monthly Traffic Safety Analysis

84 CRASHES IN
LEOMINSTER, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

In February 2024, LEOMINSTER recorded 84 crashes, a 4.5% decrease from the 88 crashes reported in February 2023. Despite the overall reduction in crashes, total injuries rose by 50%, from 10 to 15, marking a significant year-over-year increase in injury outcomes.

84

-4.5%was 88

Total Crash Events

0

Persons Killed

15

50.0%was 10

Persons Injured

4

-33.3%was 6

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 · 2024-02-01 to 2024-02-29 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, LEOMINSTER experienced a slight decrease in total crashes, falling by 4.5% from 88 crashes in February 2023 to 84 crashes in February 2024. However, total injuries increased by 50%, rising from 10 to 15 during the same period, indicating a shift towards more injurious outcomes despite fewer overall incidents.

4

Hit-and-Run Crashes — February 2024

-33.3% vs prior (6)

Hit-and-run crashes decreased from 6 incidents in February 2023 to 4 incidents in February 2024. The hit-and-run rate also saw a decline, moving from 6.8% of all crashes in the prior period to 4.8% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Cyclists Injured

Prior: 0%

14

Motorists Injured

Prior: 1040.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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 Wednesday in both periods, with 19 crashes in February 2024 compared to 17 in February 2023. The peak hour shifted from 6 PM in February 2023 (7 crashes) to 4 PM in February 2024 (9 crashes). Overall, the temporal distribution shows similar patterns, with a slight increase in crashes during late afternoon hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both February 2023 and February 2024. However, total injuries increased by 50%, rising from 10 to 15. The proportion of crashes resulting in minor injuries more than doubled, from 5.7% (5 crashes) in February 2023 to 11.9% (10 crashes) in February 2024, while serious injuries decreased from 1 crash to 0.

Outcome by Severity (Crash Events)

Minor Injury10minor injury crashes11.9%
100.0%prior 5
Possible Injury2possible injury crashes2.4%
-33.3%prior 3
No Injury71no injury crashes84.5%
-7.8%prior 77

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor, though its count decreased from 26 crashes in February 2023 to 17 crashes in February 2024. Crashes attributed to 'Followed too closely' saw a substantial increase, rising from 5 to 12 incidents, making it the third most common factor in the current period. Conversely, 'Driving too fast for conditions' was cited in 6 crashes in the prior period but was not a factor in any crashes in the current period.

Officer-Reported Primary Contributing Cause

Inattention17 (20.2%)-34.6%prior 26
Failed to yield right of way16 (19%)6.7%prior 15
Followed too closely12 (14.3%)140.0%prior 5
No improper driving11 (13.1%)10.0%prior 10
Failure to keep in proper lane or running off road8 (9.5%)
Glare4 (4.8%)
Disregarded traffic signs, signals, road markings3 (3.6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (2.4%)
Made an improper turn2 (2.4%)
Visibility obstructed2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather increased, with 74 crashes in February 2024 compared to 63 in February 2023. Notably, crashes occurring in snowy or icy conditions significantly decreased, with only 1 crash reported in snow in February 2024, down from a combined 16 crashes involving snow or ice in February 2023. Crashes on wet road surfaces also decreased from 12 to 5.

Weather

Clear74 (89.2%)
17.5%prior 63
Cloudy6 (7.2%)
Clear/Rain1 (1.2%)
Rain1 (1.2%)
Snow1 (1.2%)
-87.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Weather condition at time of crash

Lighting

Daylight56 (67.5%)
-5.1%prior 59
Dark - lighted roadway16 (19.3%)
-23.8%prior 21
Dusk5 (6.0%)
Dark - roadway not lighted4 (4.8%)
-20.0%prior 5
Dawn2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Lighting condition field

Road Surface

Dry79 (94.0%)
31.7%prior 60
Wet5 (6.0%)
-58.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased slightly from 165 to 161 year-over-year. Honda became the top vehicle make involved, with 24 incidents in February 2024, surpassing Toyota which was the top make in February 2023. The total number of persons involved in crashes increased from 195 to 231, with a notable increase in the 0-15 age group from 9 to 47 individuals, and the 35-44 age group from 29 to 40 individuals.

Top Vehicle Makes (161 vehicles)

1
HONDA24 (14.9%)
50.0%prior 16
2
FORD19 (11.8%)
18.8%prior 16
3
TOYOTA19 (11.8%)
-20.8%prior 24
4
CHEVROLET13 (8.1%)
18.2%prior 11
5
SUBARU13 (8.1%)
30.0%prior 10
6
NISSAN10 (6.2%)
-33.3%prior 15
7
KIA9 (5.6%)
8
GMC7 (4.3%)
9
HYUNDAI6 (3.7%)
-25.0%prior 8
10
JEEP6 (3.7%)
-33.3%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Vehicle unit records

19 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (206 persons with recorded sex)

Male112 (54.4%)
6.7%prior 105
Female94 (45.6%)
28.8%prior 73

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 44 in February 2023 to 36 in February 2024. Conversely, crashes in the 35 mph zone increased from 15 to 18, and crashes in the 40 mph zone, which had no incidents in the prior period, recorded 6 crashes in the current period. Fatalities remained at zero across all speed zones in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-02-01 to 2024-02-29 · 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: 2024-02-01 through 2024-02-29
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-02-01 through 2024-02-29 (29 days)
  • Geographic scope: LEOMINSTER, MA
  • Total crash records analyzed: 84
  • Total persons involved: 231
  • Total vehicles involved: 161

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 2024." Published June 21, 2026. Reporting period: 2024-02-01 to 2024-02-29. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/february-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

Leominster, MA Crash Report — February 2024 | ThatCarHitMe.com