Monthly Traffic Safety Analysis

19 CRASHES IN
LEICESTER, MA
APRIL 2024

All metrics benchmarked againstApril 2023

In April 2024, LEICESTER, MA experienced 19 crashes, a 35.7% increase compared to the 14 crashes recorded in April 2023. The most notable shift was the occurrence of 1 fatality in April 2024, whereas no fatalities were reported in April 2023.

19

35.7%was 14

Total Crash Events

1

Persons Killed

12

50.0%was 8

Persons Injured

1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for April in LEICESTER, MA shows an upward trend year-over-year. Total crashes increased by 35.7%, rising from 14 in April 2023 to 19 in April 2024. Additionally, total injuries increased by 50%, from 8 to 12, and a fatal crash occurred in April 2024 after none were reported in April 2023.

1

Hit-and-Run Crashes — April 2024

5.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

1

Motorists Killed

Prior: 0%

12

Motorists Injured

Prior: 850.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted year-over-year, with the peak crash day moving from Saturday in April 2023 (3 crashes) to Monday in April 2024 (5 crashes). The peak crash hour also changed, occurring at 12p with 3 crashes in April 2023 and shifting to 3p with 4 crashes in April 2024. Notably, Monday crashes more than doubled from 2 to 5, and Thursday crashes quadrupled from 1 to 4.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity distributions changed significantly year-over-year, with one fatal crash occurring in April 2024, compared to zero in April 2023. While serious injury crashes decreased from 1 in April 2023 to 0 in April 2024, possible injury crashes doubled from 2 to 4, increasing their share from 14.3% to 21.1%. Overall, total injuries rose from 8 persons in April 2023 to 12 persons in April 2024.

Outcome by Severity (Crash Events)

Fatal1fatal crashes5.3%
Minor Injury3minor injury crashes15.8%
0.0%prior 3
Possible Injury4possible injury crashes21.1%
100.0%prior 2
No Injury11no injury crashes57.9%
37.5%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record

Top Contributing Factors

The distribution and frequency of contributing factors changed year-over-year. Crashes attributed to 'Inattention' decreased by 33.3% in count, from 6 in April 2023 to 4 in April 2024. Conversely, 'Failed to yield right of way' crashes doubled from 2 to 4, and 'Followed too closely' crashes tripled from 1 to 3. 'No improper driving' crashes saw a 300% increase in count, rising from 1 to 4, and its share increased from 7.1% to 21.1%.

Officer-Reported Primary Contributing Cause

No improper driving4 (21.1%)
Failed to yield right of way4 (21.1%)
Inattention4 (21.1%)-33.3%prior 6
Followed too closely3 (15.8%)
Visibility obstructed1 (5.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5.3%)
Distracted1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

While weather and road surface data were not consistently available for comparison, lighting conditions showed some shifts. Crashes occurring in 'Daylight' increased from 10 in April 2023 to 13 in April 2024. Crashes in 'Dark - lighted roadway' increased from 2 to 3, and crashes in 'Dark - roadway not lighted' also increased from 2 to 3. The proportion of crashes occurring in dark conditions slightly increased from 28.6% to 31.6%.

Weather

Clear13 (68.4%)
Cloudy2 (10.5%)
Rain/Fog, smog, smoke1 (5.3%)
Snow1 (5.3%)
Snow/Blowing sand, snow1 (5.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash

Lighting

Daylight13 (68.4%)
30.0%prior 10
Dark - lighted roadway3 (15.8%)
Dark - roadway not lighted3 (15.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field

Road Surface

Dry15 (78.9%)
Snow3 (15.8%)
Wet1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (35 vehicles)

1
TOYOTA5 (14.3%)
2
CHEVROLET4 (11.4%)
3
NISSAN4 (11.4%)
4
FORD3 (8.6%)
5
GMC2 (5.7%)
6
HONDA2 (5.7%)
7
MERCEDES-BENZ2 (5.7%)
8
KIA1 (2.9%)
9
PLSR1 (2.9%)
10
RAM1 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records

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

Sex Distribution (49 persons with recorded sex)

Male25 (51.0%)
47.1%prior 17
Female24 (49.0%)
20.0%prior 20

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones saw a substantial increase, rising from 1 crash in April 2023 to 5 crashes in April 2024. Crashes in 40 mph zones increased by 66.7%, from 3 to 5, and 45 mph zones increased by 50%, from 2 to 3. While 35 mph zones maintained 6 crashes in both periods, a fatal crash occurred in a 35 mph zone in April 2024, whereas no fatalities were reported in this zone in April 2023.

Fatal crashes by zone: 35 mph: 1 of 6 (16.667%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-04-01 through 2024-04-30 (30 days)
  • Geographic scope: LEICESTER, MA
  • Total crash records analyzed: 19
  • Total persons involved: 50
  • Total vehicles involved: 35

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: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leicester/april-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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