Yearly Traffic Safety Analysis

4 CRASHES IN
GRANVILLE, MA
2025

All metrics benchmarked against2024

In 2025, Granville recorded 4 total crashes, a 43% decrease from the 7 crashes reported in 2024. No fatalities or injuries were reported in 2025, a notable improvement from the 3 injuries recorded in the prior year. The most significant year-over-year change was this complete reduction of crash-related injuries.

4

-42.9%was 7

Total Crash Events

0

Persons Killed

0

-100.0%was 3

Persons Injured

1

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

Trend Summary

The overall trend in traffic crashes in Granville shows a significant year-over-year decrease. Total crashes fell by 43%, from 7 in 2024 to 4 in 2025. This downward trend is also reflected in crash outcomes, with total injuries dropping from 3 to 0 while fatalities remained at zero in both periods.

1

Hit-and-Run Crashes — 2025

25.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

When Crashes Happen

The timing of crashes shifted between the two periods. In 2025, the peak day for crashes was Sunday with 2 incidents, a change from 2024 when Thursday was the peak day with 3 crashes. The peak hour for crashes in 2024 was 11 p.m. with 2 crashes, while in 2025, crashes were more distributed across the day, with single incidents occurring at 8 a.m., 9 a.m., 4 p.m., and 10 p.m.

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)

Top Contributing Factors

The primary contributing factors for crashes changed significantly year-over-year. In 2024, the leading factor was 'Driving too fast for conditions' with 3 crashes, but this factor's count decreased by 67% to just 1 crash in 2025. The top factor in 2025 was 'Failure to keep in proper lane or running off road,' which was cited in 2 crashes (a 50% share of all crashes), a factor not listed in the prior year's data. The count for crashes involving erratic or reckless operation remained steady at one incident in both years.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road2 (50%)
Driving too fast for conditions1 (25%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (25%)

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

In 2025, a larger proportion of crashes occurred during daylight hours, with 75% of incidents happening in daylight compared to just 14% in 2024. Conversely, crashes in dark conditions dropped from 5 incidents in 2024 to 1 in 2025. The share of crashes on dry road surfaces remained relatively stable, accounting for 50% of crashes in 2025 versus 57% in 2024. Crashes involving adverse road surfaces like snow, slush, or ice decreased from 3 incidents in 2024 to 1 in 2025.

Weather

Clear/Clear2 (50.0%)
Fog, smog, smoke1 (25.0%)
Snow1 (25.0%)

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

Lighting

Daylight3 (75.0%)
Dark - roadway not lighted1 (25.0%)

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

Road Surface

Dry2 (50.0%)
Slush1 (25.0%)
Wet1 (25.0%)

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 (5 vehicles)

1
BUIC1 (20%)
2
CHEVROLET1 (20%)
3
DODGE1 (20%)
4
RAM1 (20%)

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

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

Sex Distribution (5 persons with recorded sex)

Male3 (60.0%)
-57.1%prior 7
Female2 (40.0%)
0.0%prior 2

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

Fewer crashes had speed limit data available in 2025 (2 crashes) compared to 2024 (7 crashes). In 2024, all reported crashes occurred in speed zones of 40 mph or less, with the highest concentration (3 crashes) in 30 mph zones. In 2025, one of the two crashes with speed data occurred in a 45 mph zone, a speed zone not represented in the previous year's crash data. No fatal crashes were recorded 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: GRANVILLE, MA
  • Total crash records analyzed: 4
  • Total persons involved: 7
  • Total vehicles involved: 5

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). "GRANVILLE, 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/granville/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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Granville, MA Crash Report — 2025 | ThatCarHitMe.com