Yearly Traffic Safety Analysis

6 CRASHES IN
LEVERETT, MA
2025

All metrics benchmarked against2024

In Leverett, total traffic crashes decreased by 50% from 12 in the prior year to 6 in the current year. The number of injuries remained unchanged at 2, and no fatalities were reported in either period. The most significant year-over-year change was the substantial reduction in overall crash volume.

6

-50.0%was 12

Total Crash Events

0

Persons Killed

2

Persons Injured

0

-100.0%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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Leverett indicates a significant downward trend, with total collisions falling by half from 12 to 6 year-over-year. While the number of crashes decreased, the number of resulting injuries held steady at 2 for both periods. Fatalities remained at zero.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

2

Motorists Injured

Prior: 20.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal pattern of crashes shifted between the two periods. In the prior year, crashes peaked on Wednesday with 5 incidents and had a clear afternoon peak hour at 5 p.m. In the current year, the peak day moved to Thursday with 2 crashes, and collisions were more scattered throughout the day, with a notable cluster of incidents occurring in dark, early morning, or late-night hours.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity remained relatively stable year-over-year, with zero fatalities or fatal crashes reported in either period. The total number of injuries was unchanged at 2. However, because the total number of crashes fell, the proportion of crashes involving an injury increased from 16.7% (2 of 12 crashes) in the prior year to 33.3% (2 of 6 crashes) in the current year.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes16.7%
-50.0%prior 2
Possible Injury1possible injury crashes16.7%
No Injury4no injury crashes66.7%
-50.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The profile of contributing factors changed year-over-year. In the prior period, "No improper driving" was the most cited factor with 4 crashes. In the current period, this factor's count dropped to 1. Crashes attributed to being "Fatigued/asleep" also decreased from 2 to 1. Factors such as "Exceeded authorized speed limit" and "Inattention," each linked to one crash in the prior year, were not cited in the current year's data.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road1 (16.7%)
Fatigued/asleep1 (16.7%)
No improper driving1 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a notable shift in the conditions under which crashes occurred. The proportion of crashes happening in dark or dawn conditions increased from 41.7% (5 of 12 crashes) to 83.3% (5 of 6 crashes). Concurrently, the share of crashes on wet road surfaces rose from 8.3% (1 crash) to 50% (3 crashes). Crashes in adverse weather (rain, snow, sleet) decreased as a share of the total, from 41.7% in the prior year to 16.7% in the current year.

Weather

Clear4 (66.7%)
-33.3%prior 6
Clear/Clear1 (16.7%)
Rain/Cloudy1 (16.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted4 (66.7%)
Dawn1 (16.7%)
Daylight1 (16.7%)
-85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry3 (50.0%)
-66.7%prior 9
Wet3 (50.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (7 vehicles)

1
ACURA1 (14.3%)
2
CHEVROLET1 (14.3%)
3
FORD1 (14.3%)
4
HYUNDAI1 (14.3%)
5
KIA1 (14.3%)
6
SUBARU1 (14.3%)
7
TOYOTA1 (14.3%)
-80.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

Sex Distribution (7 persons with recorded sex)

Male5 (71.4%)
0.0%prior 5
Female2 (28.6%)
-75.0%prior 8

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across different speed zones changed between periods. In the prior year, crashes were most concentrated in the 35 mph zone, which saw 4 incidents. In the current year, the 6 crashes with recorded speed limits were evenly distributed, with one crash each in the 25, 30, 35, 40, 45, and 50 mph zones. No fatal crashes occurred in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: LEVERETT, MA
  • Total crash records analyzed: 6
  • Total persons involved: 7
  • Total vehicles involved: 7

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). "LEVERETT, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/leverett/2025-annual-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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Leverett, MA Crash Report — 2025 | ThatCarHitMe.com