ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GRAFTON, MA · 2024
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/grafton/2024-annual-report
Yearly Traffic Safety Analysis
330 CRASHES IN
GRAFTON, MA
2024
In 2024, Grafton recorded 330 total vehicle crashes, a 1.9% increase from the 324 crashes documented in 2023. While overall crash volume remained relatively stable, the most significant change was the reduction in fatalities, with zero deaths reported in 2024 compared to one in the previous year. The total number of injuries saw a slight increase from 84 in 2023 to 88 in 2024.
330
▲ 1.9%was 324
Total Crash Events
0
▼ -100.0%was 1
Persons Killed
88
▲ 4.8%was 84
Persons Injured
18
▲ 5.9%was 17
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash trends in Grafton show a slight increase year-over-year. The total number of crashes rose by 1.9%, from 324 in 2023 to 330 in 2024. Similarly, the number of people injured in these incidents increased by 4.8%, from 84 to 88.
18
Hit-and-Run Crashes — 2024
▲ 5.9% vs prior (17)
The number of hit-and-run incidents in Grafton remained relatively stable year-over-year, with a slight increase from 17 in 2023 to 18 in 2024. This corresponds to a minor rise in the hit-and-run rate, which edged up from 5.2% to 5.5% of all crashes. The trend indicates that the frequency of drivers leaving the scene of a crash has not significantly changed.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
86
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Grafton shifted between 2023 and 2024. The peak day for collisions moved from Wednesday (54 crashes) to Tuesday (64 crashes). A more pronounced change occurred in the peak hour, which shifted from the 4 p.m. hour in 2023 (31 crashes) to the 8 a.m. hour in 2024 (36 crashes), indicating a move from the evening commute to the morning commute as the most frequent time for incidents.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity improved in 2024, with fatal crashes decreasing from one in 2023 to zero. The proportion of crashes resulting in no injuries increased from 76.9% to 79.7% year-over-year. While there were no fatal crashes, the data shows an increase in crashes classified as 'Serious Injury,' rising from zero reported in 2023 to 4 in 2024, representing 1.2% of all crashes in the current period.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record
Top Contributing Factors
The top three contributing factors to crashes in Grafton remained consistent year-over-year: 'No improper driving,' 'Inattention,' and 'Followed too closely.' The count for crashes attributed to 'Followed too closely' increased by 14.3%, from 42 to 48 incidents. Crashes involving 'Failed to yield right of way' also saw a notable rise in count from 21 to 29 incidents. Conversely, crashes related to 'Driving too fast for conditions' decreased in count by 31.3%, from 16 in 2023 to 11 in 2024.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
In both periods, the majority of crashes occurred in daylight on dry roads. In 2024, crashes on dry road surfaces increased from 235 to 255, while those on wet surfaces decreased from 63 to 41. However, incidents during snowy conditions saw a significant increase, with crashes in snow weather rising from 8 to 18, and those on snow-covered road surfaces increasing from 12 to 31 year-over-year.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes remained Toyota, Honda, and Ford in both 2023 and 2024, with all three seeing an increase in total incidents. Toyota involvement rose from 79 to 93 vehicles, Honda from 53 to 61, and Ford from 41 to 58. Analysis of driver and passenger age demographics reveals shifts among different groups; the number of persons aged 45-54 involved in crashes increased from 73 to 96. Conversely, involvement for the 55-64 age group decreased from 86 to 70.
Top Vehicle Makes (589 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records
36 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (636 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones saw some changes between 2023 and 2024. Crashes in 35 mph zones increased from 43 to 59, while incidents in 65 mph zones decreased from 98 to 91. The number of crashes in 30 mph zones remained nearly constant, with 141 incidents in 2024 compared to 143 in the prior year. The single fatality in 2023 occurred in a 65 mph zone; in 2024, there were no fatalities recorded in any speed zone.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2024-01-01 through 2024-12-31 (366 days)
- Geographic scope: GRAFTON, MA
- Total crash records analyzed: 330
- Total persons involved: 677
- Total vehicles involved: 589
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: 2024." Published June 21, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/grafton/2024-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2024-01-01 – 2024-12-31
Generated: June 21, 2026 · All rights reserved