Monthly Traffic Safety Analysis

106 CRASHES IN
LEOMINSTER, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, LEOMINSTER experienced 106 total crashes, marking a 23.26% increase from the 86 crashes recorded in March 2022. Total injuries also saw a substantial rise, from 21 in the prior year to 34 in the current period, representing a 61.9% increase. Fatalities remained at zero for both periods, indicating no change in the most severe crash outcome.

106

23.3%was 86

Total Crash Events

0

Persons Killed

34

61.9%was 21

Persons Injured

8

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. 4 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for March 2023 indicates an upward trend in LEOMINSTER compared to March 2022. Total crashes increased by 20, rising from 86 to 106, which is a 23.26% increase year-over-year. Concurrently, total injuries increased by 13, from 21 to 34, marking a 61.9% rise.

8

Hit-and-Run Crashes — March 2023

33.3% vs prior (6)

Hit-and-run incidents increased in March 2023, with 8 crashes reported compared to 6 in March 2022. This represents an increase of 2 hit-and-run crashes year-over-year. The hit-and-run rate also slightly increased from 7% in the prior period to 7.5% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 2-50.0%

33

Motorists Injured

Prior: 1973.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes in March 2023 showed some shifts compared to the prior year. The peak day for crashes moved from Thursday with 18 crashes in March 2022 to Wednesday with 21 crashes in March 2023. While 3 PM remained the peak hour for crashes in both periods, the count increased slightly from 13 to 14. Notably, Monday, Wednesday, and Friday experienced increases in crash counts, with Monday rising from 10 to 17 crashes, Wednesday from 15 to 21 crashes, and Friday from 11 to 17 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at zero in both March 2022 and March 2023, resulting in a consistent fatal crash rate of 0%. The number of serious injury crashes increased from 1 to 2, and minor injury crashes rose from 6 to 9 year-over-year. While possible injury crashes remained constant at 9, their proportion of total crashes decreased from 10.5% to 8.5%.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes1.9%
100.0%prior 1
Minor Injury9minor injury crashes8.5%
50.0%prior 6
Possible Injury9possible injury crashes8.5%
0.0%prior 9
No Injury82no injury crashes77.4%
18.8%prior 69

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

Comparing contributing factors, 'Inattention' remained the leading factor, increasing from 25 crashes in March 2022 to 28 crashes in March 2023. 'Failed to yield right of way' also saw an increase, from 18 to 22 crashes. 'Distracted' driving incidents more than doubled, rising from 2 to 5 crashes year-over-year. Conversely, 'Failure to keep in proper lane or running off road' decreased from 8 to 6 crashes, and 'Disregarded traffic signs, signals, road markings' decreased from 3 to 2 crashes.

Officer-Reported Primary Contributing Cause

Inattention28 (26.4%)12.0%prior 25
Failed to yield right of way22 (20.8%)22.2%prior 18
Followed too closely9 (8.5%)0.0%prior 9
No improper driving9 (8.5%)50.0%prior 6
Failure to keep in proper lane or running off road6 (5.7%)-25.0%prior 8
Distracted5 (4.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner5 (4.7%)
Driving too fast for conditions4 (3.8%)
Disregarded traffic signs, signals, road markings2 (1.9%)
Exceeded authorized speed limit2 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In March 2023, crashes under 'Clear' weather conditions increased from 59 to 78, while crashes on 'Dry' road surfaces rose from 66 to 79 compared to March 2022. Notably, crashes occurring on 'Snow' covered roads saw a significant increase, from 1 in the prior year to 11 in the current period. Crashes during 'Daylight' conditions increased from 59 to 77, whereas those in 'Dark - lighted roadway' conditions decreased from 23 to 18.

Weather

Clear78 (75.7%)
32.2%prior 59
Snow7 (6.8%)
Cloudy7 (6.8%)
16.7%prior 6
Rain3 (2.9%)
-40.0%prior 5
Cloudy/Rain2 (1.9%)
-66.7%prior 6
Clear/Cloudy2 (1.9%)
Clear/Other1 (1.0%)
Clear/Rain1 (1.0%)
Cloudy/Snow1 (1.0%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight77 (72.6%)
30.5%prior 59
Dark - lighted roadway18 (17.0%)
-21.7%prior 23
Dark - roadway not lighted5 (4.7%)
Dusk5 (4.7%)
Dawn1 (0.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry79 (75.2%)
19.7%prior 66
Wet13 (12.4%)
-23.5%prior 17
Snow11 (10.5%)
Ice2 (1.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 172 in March 2022 to 203 in March 2023. Toyota remained the most frequently involved make, increasing from 25 to 32 vehicles. Chevrolet moved up in ranking, with its involvement rising from 18 to 22 vehicles, while Honda saw a slight decrease from 23 to 21 vehicles. Subaru experienced a notable decrease in involvement, dropping from 17 to 8 vehicles year-over-year.

Top Vehicle Makes (203 vehicles)

1
TOYOTA32 (15.8%)
28.0%prior 25
2
CHEVROLET22 (10.8%)
22.2%prior 18
3
HONDA21 (10.3%)
-8.7%prior 23
4
FORD20 (9.9%)
53.8%prior 13
5
JEEP10 (4.9%)
-16.7%prior 12
6
NISSAN9 (4.4%)
12.5%prior 8
7
SUBARU8 (3.9%)
-52.9%prior 17
8
HYUNDAI7 (3.4%)
-12.5%prior 8
9
MAZDA6 (3%)
10
BMW5 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (252 persons with recorded sex)

Male148 (58.7%)
46.5%prior 101
Female104 (41.3%)
7.2%prior 97

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones saw the largest increase, rising from 35 in March 2022 to 51 in March 2023. Crashes in 20 mph zones also increased, from 2 to 6. Conversely, crashes in 35 mph zones decreased from 17 to 13, and in 40 mph zones from 2 to 1. There were no fatal crashes reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: LEOMINSTER, MA
  • Total crash records analyzed: 106
  • Total persons involved: 277
  • Total vehicles involved: 203

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leominster/march-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

ThatCarHitMe.com · An Injuria.ai Company

Leominster, MA Crash Report — March 2023 | ThatCarHitMe.com