Monthly Traffic Safety Analysis

15 CRASHES IN
LEICESTER, MA
FEBRUARY 2024

All metrics benchmarked againstFebruary 2023

In February 2024, LEICESTER recorded 15 total crashes, an increase of 15.4% compared to the 13 crashes reported in February 2023. The most notable shift was a 100% increase in crashes attributed to 'Inattention' as a contributing factor, rising from 3 to 6 incidents.

15

15.4%was 13

Total Crash Events

0

Persons Killed

2

-33.3%was 3

Persons Injured

0

Fatal Crash Events

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. 2 crashes with unreported severity are 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, crash incidents in LEICESTER showed an upward trend, with total crashes increasing from 13 in February 2023 to 15 in February 2024, representing a 15.4% rise. Conversely, total injuries decreased by 33.3%, from 3 injuries in the prior period to 2 injuries in the current period, while total fatalities remained at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 3-33.3%

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 temporal distribution of crashes shifted year-over-year. In February 2023, Thursday was the peak day with 7 crashes, and the peak hour was 4p with 3 crashes. In February 2024, the peak days were Tuesday, Thursday, and Friday, each with 3 crashes, and the peak hour shifted to 8a with 3 crashes.

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 0 in both periods. Total injuries decreased from 3 in February 2023 to 2 in February 2024. The current period saw 1 serious injury crash (Severity A), which was not present in the prior period, while minor injury crashes (Severity B) decreased from 2 (15.4% share) to 1 (6.7% share).

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.7%
Minor Injury1minor injury crashes6.7%
-50.0%prior 2
No Injury11no injury crashes73.3%
10.0%prior 10

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

The contributing factor 'Inattention' saw a 100% increase in count, rising from 3 crashes in February 2023 to 6 crashes in February 2024, and became the most frequent factor in the current period with a 40% share. 'No improper driving' decreased by 33.3% in count, from 3 crashes to 2 crashes. Factors like 'Followed too closely' (2 crashes) and 'Driving too fast for conditions' (1 crash) appeared in the current period but not in the prior, while factors such as 'Glare' (1 crash) and 'Failure to keep in proper lane or running off road' (1 crash) were present only in the prior period.

Officer-Reported Primary Contributing Cause

Inattention6 (40%)
Followed too closely2 (13.3%)
No improper driving2 (13.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (6.7%)
Driving too fast for conditions1 (6.7%)

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

Crashes occurring in 'Clear' weather conditions increased from 6 in February 2023 to 12 in February 2024. Crashes on 'Dry' road surfaces also increased from 10 to 13 year-over-year. Crashes in 'Dark - lighted roadway' conditions decreased from 4 to 2, while 'Dark - roadway not lighted' and 'Dusk' conditions, each accounting for 2 and 1 crash respectively, were observed in the current period but not in the prior.

Weather

Clear12 (80.0%)
100.0%prior 6
Snow2 (13.3%)
Cloudy1 (6.7%)
-80.0%prior 5

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

Lighting

Daylight10 (66.7%)
25.0%prior 8
Dark - lighted roadway2 (13.3%)
Dark - roadway not lighted2 (13.3%)
Dusk1 (6.7%)

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

Road Surface

Dry13 (86.7%)
30.0%prior 10
Sand, mud, dirt, oil, gravel1 (6.7%)
Snow1 (6.7%)

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

Vehicles & Demographics

Top Vehicle Makes (25 vehicles)

1
TOYOTA4 (16%)
-33.3%prior 6
2
NISSAN4 (16%)
3
CHEVROLET4 (16%)
4
KIA2 (8%)
5
HONDA1 (4%)
6
HYUNDAI1 (4%)
7
JEEP1 (4%)
8
STRN1 (4%)
9
SUBARU1 (4%)
10
VOLKSWAGEN1 (4%)

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

Sex Distribution (27 persons with recorded sex)

Female14 (51.9%)
40.0%prior 10
Male13 (48.1%)
8.3%prior 12

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 30 mph speed zones increased from 5 in February 2023 to 6 in February 2024, while crashes in 40 mph zones decreased from 4 to 3. The current period also reported crashes in 20 mph (1 crash) and 25 mph (1 crash) speed zones, which were not present in the prior period. Fatal crash rates remained at 0 for 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: LEICESTER, MA
  • Total crash records analyzed: 15
  • Total persons involved: 28
  • Total vehicles involved: 25

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). "LEICESTER, 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/leicester/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

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