Monthly Traffic Safety Analysis

26 CRASHES IN
GRAFTON, MA
AUGUST 2025

All metrics benchmarked againstAugust 2024

Total crashes in GRAFTON increased from 23 in August 2024 to 26 in August 2025, representing a 13.04% rise year-over-year. The most notable shift was a significant increase in hit-and-run crashes, which quadrupled from 1 to 5 incidents. Despite the increase in total crashes, total injuries decreased during this period.

26

13.0%was 23

Total Crash Events

0

Persons Killed

5

-28.6%was 7

Persons Injured

5

400.0%was 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. 1 crash with unreported severity is not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a slight increase in total crashes, rising from 23 to 26 incidents, a 13.04% increase year-over-year. Conversely, total injuries saw a downward trend, decreasing from 7 to 5, a 28.57% reduction. Fatalities remained stable at 0 in both periods.

5

Hit-and-Run Crashes — August 2025

400.0% vs prior (1)

Hit-and-run crashes increased significantly from 1 incident in August 2024 to 5 incidents in August 2025. Consequently, the hit-and-run rate rose from 4.3% to 19.2% of total crashes year-over-year, indicating an upward trend in these types of incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 6-16.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Saturday, with 5 crashes in August 2024, to Friday, with 9 crashes in August 2025. The peak hour also changed from 12 p.m. in the prior period to 10 p.m. in the current period, with both peak hours recording 3 crashes. Crashes on Fridays notably increased from 3 to 9 year-over-year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both August 2024 and August 2025. Total injuries decreased from 7 to 5, a 28.57% reduction year-over-year. The proportion of crashes resulting in minor injury increased from 13% to 15.4%, while possible injury crashes decreased from 13% to 3.8% of total crashes.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes15.4%
33.3%prior 3
Possible Injury1possible injury crashes3.8%
-66.7%prior 3
No Injury20no injury crashes76.9%
17.6%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor shifted from 'Followed too closely' (6 crashes) in August 2024 to 'Inattention' (6 crashes) in August 2025. Crashes attributed to 'Followed too closely' decreased by 66.7%, from 6 to 2 incidents, while 'Inattention' crashes increased by 20%, from 5 to 6 incidents. 'No improper driving' remained constant with 4 crashes in both periods.

Officer-Reported Primary Contributing Cause

Inattention6 (23.1%)20.0%prior 5
No improper driving4 (15.4%)
Followed too closely2 (7.7%)-66.7%prior 6
Fatigued/asleep2 (7.7%)
Failed to yield right of way2 (7.7%)
Other improper action1 (3.8%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (3.8%)
Visibility obstructed1 (3.8%)
Disregarded traffic signs, signals, road markings1 (3.8%)
Driving too fast for conditions1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Clear' weather conditions remained consistent at 19 incidents in both August 2024 and August 2025. However, crashes during 'Rain' increased from 1 to 3, and crashes on 'Wet' road surfaces doubled from 2 to 4. Crashes occurring in 'Daylight' increased slightly from 16 to 17, while crashes in 'Dark - lighted roadway' increased from 3 to 4.

Weather

Clear16 (61.5%)
0.0%prior 16
Clear/Clear3 (11.5%)
Rain3 (11.5%)
Cloudy2 (7.7%)
Clear/Cloudy1 (3.8%)
Cloudy/Rain1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Weather condition at time of crash

Lighting

Daylight17 (65.4%)
6.3%prior 16
Dark - lighted roadway4 (15.4%)
Dark - roadway not lighted4 (15.4%)
Dusk1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Lighting condition field

Road Surface

Dry22 (84.6%)
4.8%prior 21
Wet4 (15.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (47 vehicles)

1
HONDA6 (12.8%)
2
CHEVROLET4 (8.5%)
3
TOYOTA4 (8.5%)
4
NISSAN3 (6.4%)
5
JEEP3 (6.4%)
6
FORD3 (6.4%)
-40.0%prior 5
7
SUBARU2 (4.3%)
8
MERCEDES-BENZ2 (4.3%)
9
VOLVO2 (4.3%)
10
GMC2 (4.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Vehicle unit records

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

Sex Distribution (47 persons with recorded sex)

Male25 (53.2%)
0.0%prior 25
Female22 (46.8%)
0.0%prior 22

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes occurring in 30 mph speed zones remained constant at 11 incidents in both periods. Crashes in 65 mph speed zones decreased from 7 to 6, while those in 35 mph speed zones increased from 1 to 4. The 10 mph and 40 mph speed zones, present in the prior period, did not record any crashes in the current period, and the 25 mph speed zone appeared with 2 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-08-01 to 2025-08-31 · 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: 2025-08-01 through 2025-08-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-08-01 through 2025-08-31 (31 days)
  • Geographic scope: GRAFTON, MA
  • Total crash records analyzed: 26
  • Total persons involved: 59
  • Total vehicles involved: 47

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). "GRAFTON, MA Crash Intelligence Report: August 2025." Published June 21, 2026. Reporting period: 2025-08-01 to 2025-08-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/grafton/august-2025-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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Grafton, MA Crash Report — August 2025 | ThatCarHitMe.com