ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · ATHOL, 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/athol/2023-annual-report
Yearly Traffic Safety Analysis
208 CRASHES IN
ATHOL, MA
2023
In 2023, Athol recorded 208 total traffic crashes, a 17.8% decrease from the 253 crashes in 2022. While overall collisions and injuries declined, the most notable year-over-year shift was a significant increase in hit-and-run incidents, which more than doubled from 6 to 14. Total fatalities decreased from two in the prior year to one in the current year.
208
▼ -17.8%was 253
Total Crash Events
1
▼ -50.0%was 2
Persons Killed
54
▼ -27.0%was 74
Persons Injured
14
▲ 133.3%was 6
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. 12 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
Traffic safety trends in Athol showed improvement year-over-year, with total crashes falling by 17.8% from 253 to 208. This downward trend was also reflected in the number of people injured, which decreased by 27% from 74 to 54. The number of fatalities also declined from two in 2022 to one in 2023.
14
Hit-and-Run Crashes — 2023
▲ 133.3% vs prior (6)
Hit-and-run incidents showed a significant upward trend year-over-year. The absolute number of hit-and-run crashes more than doubled, increasing from 6 in 2022 to 14 in 2023. As a result, the hit-and-run rate, representing the share of all crashes that were hit-and-runs, rose sharply from 2.4% to 6.7%.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Motorists Killed
6
Pedestrians Injured
48
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 saw a minor shift between the two periods. The peak day for crashes moved from Friday (42 crashes) in 2022 to Thursday (38 crashes) in 2023. However, the afternoon rush remained the most dangerous time, as 3 PM was the peak hour for crashes in both years, accounting for 27 and 22 crashes, respectively.
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
While the number of fatal crashes remained constant at one in both 2023 and 2022, the total number of fatalities decreased from two to one. The overall proportion of crashes resulting in an injury was unchanged at 20.6% year-over-year. Within injury crashes, the share of 'Minor Injury' incidents increased from 12.3% to 14.4% of all crashes, while 'Possible Injury' crashes decreased from 7.1% to 4.8%.
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
The top contributing factors shifted between the two years. While 'Inattention' was cited in a constant 37 crashes in both periods, its share of all crashes grew from 14.6% to 17.8%. Crashes attributed to 'Failed to yield right of way' saw a 62.5% increase in count, rising from 8 to 13 incidents. Conversely, crashes due to 'Followed too closely' decreased by 47%, from 17 incidents in 2022 to 9 in 2023.
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
There was a notable shift in lighting conditions for crashes year-over-year. The proportion of collisions occurring in daylight decreased from 71.5% in 2022 to 62.5% in 2023, while the share of crashes in darkness (both lighted and unlighted roads) increased from 22.9% to 29.3%. The distribution of crashes across road surface conditions remained relatively stable, with incidents on non-dry surfaces accounting for 23.3% of crashes in 2022 and 20.7% 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
The top three vehicle makes involved in crashes remained consistent but shifted in rank; Ford, the most common make in 2022 with 57 vehicles, dropped to third in 2023 with 31, while Toyota became the most frequent with 49 vehicles. The 26-34 age group was the most represented demographic involved in crashes in both years. This group's share of total persons involved increased from 14.6% in 2022 to 18.4% in 2023.
Top Vehicle Makes (346 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
43 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (354 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
Crashes appeared to shift towards lower-speed zones in 2023 compared to the prior year. The number of collisions in 30 mph zones increased from 91 to 96, while crashes in 45 mph and 55 mph zones collectively fell from 41 to 28. The location of the year's fatal crash also shifted from a 55 mph zone in 2022 to a 30 mph zone in 2023.
Fatal crashes by zone: 30 mph: 1 of 96 (1.042%)
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: ATHOL, MA
- Total crash records analyzed: 208
- Total persons involved: 403
- Total vehicles involved: 346
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). "ATHOL, 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/athol/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