ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · GRAFTON, MA · 2023
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/2023-annual-report
Yearly Traffic Safety Analysis
324 CRASHES IN
GRAFTON, MA
2023
In 2023, Grafton recorded 324 total vehicle crashes, an increase from the 294 crashes reported in 2022, representing a 10.2% rise. The total number of injuries also increased from 73 to 84 over the same period. The most significant shift was the occurrence of one fatal crash in 2023, whereas no fatal crashes were recorded in the prior year.
324
▲ 10.2%was 294
Total Crash Events
1
Persons Killed
84
▲ 15.1%was 73
Persons Injured
17
▲ 466.7%was 3
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for Grafton indicates an upward trend in collisions year-over-year. Total crashes increased by 10.2%, from 294 in 2022 to 324 in 2023. This was accompanied by a 15.1% rise in total injuries, which grew from 73 to 84 over the same period.
17
Hit-and-Run Crashes — 2023
▲ 466.7% vs prior (3)
Hit-and-run incidents increased significantly in 2023 compared to the previous year. The number of hit-and-run crashes rose from 3 in 2022 to 17 in 2023. As a result, the hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, increased from 1.0% to 5.2% year-over-year.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
82
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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 showed some shifts between 2022 and 2023. The peak hour for crashes remained consistent, with the 4 p.m. hour having the highest volume in both years (30 crashes in 2022, 31 in 2023). However, the peak day for crashes shifted from Friday in 2022 (67 crashes) to Wednesday in 2023 (54 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes increased in 2023 compared to the previous year. Grafton recorded one fatal crash, accounting for 0.3% of all crashes, up from zero fatal crashes in 2022. The proportion of crashes resulting in minor injuries also rose, accounting for 14.2% (46 crashes) of all incidents in 2023, compared to 10.9% (32 crashes) in 2022. Consequently, the share of non-injury crashes decreased from 80.6% in 2022 to 76.9% in 2023.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record
Top Contributing Factors
In 2023, 'No improper driving' was the most cited factor with 67 instances, followed by 'Inattention' with 56. This is a change from 2022, when 'Inattention' was the top factor with 62 instances. The count of crashes attributed to 'Driving too fast for conditions' increased from 10 to 16, while crashes involving 'Failure to keep in proper lane' grew from 16 to 23. Conversely, crashes attributed to an 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased in count from 16 to 9.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
While most crashes in both years occurred in daylight on dry roads, 2023 saw a larger share of crashes in adverse conditions. The number of crashes on wet roads increased from 35 in 2022 to 63 in 2023, and crashes during rain rose from 17 to 30. Correspondingly, the proportion of crashes in clear weather conditions fell from 71.4% of the total in 2022 to 57.7% in 2023.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field
Vehicles & Demographics
Toyota (79 vehicles) and Honda (53 vehicles) were the top two makes involved in crashes in 2023, consistent with the prior year where they were also top makes. Ford's involvement decreased from 58 vehicles in 2022 to 41 in 2023. While the 26-34 age group remained the most frequently involved demographic in both years, their count decreased from 132 to 110. The number of persons aged 16-20 involved in crashes increased from 54 to 72, and those in the 55-64 age bracket also saw an increase from 57 to 86.
Top Vehicle Makes (562 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
35 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (629 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events
Speed Limit Zones
Analysis of crashes by posted speed limit shows an increase in incidents in 30 mph and 65 mph zones in 2023. Crashes in 30 mph zones rose from 115 in 2022 to 143 in 2023, the largest volume increase. Crashes in 65 mph zones also increased from 85 to 98. The single fatal crash in 2023 occurred in a 65 mph zone, which had no fatal crashes the prior year.
Fatal crashes by zone: 65 mph: 1 of 98 (1.02%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-12-31 (365 days)
- Geographic scope: GRAFTON, MA
- Total crash records analyzed: 324
- Total persons involved: 669
- Total vehicles involved: 562
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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/grafton/2023-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: 2023-01-01 – 2023-12-31
Generated: June 21, 2026 · All rights reserved