Monthly Traffic Safety Analysis

91 CRASHES IN
LEOMINSTER, MA
APRIL 2023

All metrics benchmarked againstApril 2022

Total crashes in Leominster for April 2023 increased by 30% to 91, up from 70 crashes in April 2022. This period saw no fatalities, a decrease from one fatality recorded in the prior year. The most notable shift was the overall increase in total crashes.

91

30.0%was 70

Total Crash Events

0

-100.0%was 1

Persons Killed

28

Persons Injured

1

-50.0%was 2

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 · 2023-04-01 to 2023-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in Leominster shows an increase year-over-year, with total crashes rising from 70 in April 2022 to 91 in April 2023. This represents a 30% increase in crash incidents.

1

Hit-and-Run Crashes — April 2023

-50.0% vs prior (2)

Hit-and-run crashes decreased year-over-year, dropping from 2 incidents in April 2022 to 1 incident in April 2023. The hit-and-run rate also fell from 2.9% to 1.1% over the same period.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

28

Motorists Injured

Prior: 273.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted year-over-year. In April 2023, the peak day for crashes was Wednesday with 16 incidents, whereas in April 2022, Friday and Wednesday shared the peak with 13 incidents each. The peak hour for crashes also changed, moving from 2 PM with 10 incidents in April 2022 to 7 AM with 9 incidents in April 2023.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution of crashes saw a notable change with no fatalities in April 2023, compared to one fatality in April 2022. While total injuries remained stable at 28 for both periods, minor injuries decreased from 12 (17.1% share) to 5 (5.5% share). Conversely, possible injuries increased from 3 (4.3% share) to 13 (14.3% share) year-over-year.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.2%
0.0%prior 2
Minor Injury5minor injury crashes5.5%
-58.3%prior 12
Possible Injury13possible injury crashes14.3%
333.3%prior 3
No Injury71no injury crashes78%
36.5%prior 52

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Most severe injury per crash record

Top Contributing Factors

Inattention remained the leading contributing factor, increasing from 24 incidents in April 2022 to 33 in April 2023, a 37.5% increase in count. Crashes attributed to "No improper driving" saw a significant rise from 4 to 9, a 125% increase in count. Conversely, "Followed too closely" incidents decreased from 11 to 9, an 18.2% reduction in count.

Officer-Reported Primary Contributing Cause

Inattention33 (36.3%)37.5%prior 24
Failed to yield right of way10 (11%)0.0%prior 10
No improper driving9 (9.9%)
Followed too closely9 (9.9%)-18.2%prior 11
Failure to keep in proper lane or running off road5 (5.5%)
Distracted4 (4.4%)
Other improper action4 (4.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (3.3%)
Visibility obstructed3 (3.3%)
Disregarded traffic signs, signals, road markings2 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 54 in April 2022 to 69 in April 2023. Similarly, incidents during daylight hours rose from 62 to 74 year-over-year. Crashes on dry road surfaces also increased from 66 to 85, reflecting the overall increase in total crash volume.

Weather

Clear69 (75.8%)
27.8%prior 54
Cloudy16 (17.6%)
23.1%prior 13
Rain3 (3.3%)
Clear/Cloudy1 (1.1%)
Cloudy/Rain1 (1.1%)
Fog, smog, smoke1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Weather condition at time of crash

Lighting

Daylight74 (81.3%)
19.4%prior 62
Dark - lighted roadway12 (13.2%)
50.0%prior 8
Dusk4 (4.4%)
Dark - roadway not lighted1 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Lighting condition field

Road Surface

Dry85 (93.4%)
28.8%prior 66
Wet6 (6.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased by 27.6%, from 134 in April 2022 to 171 in April 2023. Among vehicle makes, Chevrolet incidents increased from 13 to 19, while Mazda and Hyundai incidents both rose from 4 to 10. The 65+ age group was the only one to show a decrease in persons involved, from 23 to 21.

Top Vehicle Makes (171 vehicles)

1
TOYOTA26 (15.2%)
0.0%prior 26
2
HONDA22 (12.9%)
4.8%prior 21
3
CHEVROLET19 (11.1%)
46.2%prior 13
4
FORD12 (7%)
33.3%prior 9
5
MAZDA10 (5.8%)
6
HYUNDAI10 (5.8%)
7
SUBARU9 (5.3%)
80.0%prior 5
8
JEEP8 (4.7%)
60.0%prior 5
9
NISSAN8 (4.7%)
14.3%prior 7
10
DODGE6 (3.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Vehicle unit records

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

Sex Distribution (216 persons with recorded sex)

Male109 (50.5%)
25.3%prior 87
Female107 (49.5%)
39.0%prior 77

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones saw a substantial increase, rising from 26 incidents in April 2022 to 49 in April 2023. Conversely, crashes in 35 mph zones decreased from 18 to 14, and in 55 mph zones from 7 to 3. There were no fatalities recorded in any speed zone in April 2023, compared to one fatality in a 10 mph zone in April 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-04-01 to 2023-04-30 · 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: 2023-04-01 through 2023-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-04-01 through 2023-04-30 (30 days)
  • Geographic scope: LEOMINSTER, MA
  • Total crash records analyzed: 91
  • Total persons involved: 229
  • Total vehicles involved: 171

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: April 2023." Published June 21, 2026. Reporting period: 2023-04-01 to 2023-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/april-2023-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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Leominster, MA Crash Report — April 2023 | ThatCarHitMe.com