Monthly Traffic Safety Analysis

16 CRASHES IN
ATHOL, MA
MARCH 2023

All metrics benchmarked againstMarch 2022

In March 2023, Athol recorded 16 total crashes, a 5.9% decrease compared to the 17 crashes in March 2022. The most significant year-over-year change was an 88.9% reduction in total injuries, falling from 9 in the prior year to 1 in the current period.

16

-5.9%was 17

Total Crash Events

0

Persons Killed

1

-88.9%was 9

Persons Injured

2

100.0%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 · 2023-03-01 to 2023-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Athol show a slight decline year-over-year, with total crashes decreasing by 5.9% from 17 to 16. This period also saw a substantial reduction in total injuries, dropping from 9 to 1, indicating a positive trend in crash severity outcomes.

2

Hit-and-Run Crashes — March 2023

100.0% vs prior (1)

Hit-and-run incidents increased year-over-year, with 2 crashes reported in March 2023 compared to 1 in March 2022. Consequently, the hit-and-run rate rose from 5.9% of total crashes in the prior period to 12.5% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 8-87.5%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted slightly year-over-year. In March 2023, the peak day for crashes was Wednesday with 5 incidents, whereas in March 2022, Thursday and Wednesday both recorded 4 crashes. The peak crash hour also changed, moving from 1 PM with 4 crashes in the prior year to 3 PM with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity significantly decreased year-over-year, with total injuries falling from 9 in March 2022 to just 1 in March 2023. Both periods maintained zero fatal crashes. The proportion of crashes resulting in no injury increased from 58.8% in the prior year to 87.5% in the current period.

Outcome by Severity (Crash Events)

Minor Injury1minor injury crashes6.3%
-75.0%prior 4
No Injury14no injury crashes87.5%
40.0%prior 10

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors saw shifts year-over-year. Crashes attributed to 'Inattention' increased from 2 in March 2022 to 5 in March 2023. 'No improper driving' also saw a slight increase from 4 crashes to 5 crashes. Factors like 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway' and 'Driving too fast for conditions' were each present in 2 crashes in the prior year but were not reported in the current period.

Officer-Reported Primary Contributing Cause

Inattention5 (31.3%)
No improper driving5 (31.3%)
Distracted1 (6.3%)
Followed too closely1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions remained largely consistent, with 'Clear' conditions accounting for 11 crashes in March 2023, up from 10 in March 2022. Crashes occurring in 'Snow' conditions decreased from 4 to 3 year-over-year. Regarding lighting, 'Daylight' crashes decreased from 13 to 11, while crashes in 'Dark - lighted roadway' increased from 1 to 4. Road surface conditions saw a slight shift, with 'Dry' crashes decreasing from 12 to 11, and 1 crash occurring on 'Ice' in the current period where none were recorded in the prior year.

Weather

Clear11 (68.8%)
10.0%prior 10
Clear/Other2 (12.5%)
Snow2 (12.5%)
Snow/Blowing sand, snow1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Weather condition at time of crash

Lighting

Daylight11 (68.8%)
-15.4%prior 13
Dark - lighted roadway4 (25.0%)
Dusk1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Lighting condition field

Road Surface

Dry11 (68.8%)
-8.3%prior 12
Snow3 (18.8%)
Ice1 (6.3%)
Wet1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (27 vehicles)

1
TOYOTA4 (14.8%)
2
MERCEDES-BENZ3 (11.1%)
3
DODGE3 (11.1%)
4
FORD3 (11.1%)
5
CHEVROLET2 (7.4%)
-71.4%prior 7
6
JEEP1 (3.7%)
7
KIA1 (3.7%)
8
HYUNDAI1 (3.7%)
9
MITS1 (3.7%)
10
NISSAN1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Vehicle unit records

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

Sex Distribution (25 persons with recorded sex)

Male17 (68.0%)
30.8%prior 13
Female8 (32.0%)
-33.3%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph speed zones increased from 7 in March 2022 to 9 in March 2023. There was also an increase in crashes in 40 mph zones, from 1 to 2. Conversely, crashes in 20 mph zones decreased from 2 to 0, and crashes in 45 mph zones decreased from 1 to 0. No fatal crashes were reported across any speed limit zone in either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-03-01 to 2023-03-31 · 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: 2023-03-01 through 2023-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-03-01 through 2023-03-31 (31 days)
  • Geographic scope: ATHOL, MA
  • Total crash records analyzed: 16
  • Total persons involved: 29
  • Total vehicles involved: 27

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: March 2023." Published June 21, 2026. Reporting period: 2023-03-01 to 2023-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/athol/march-2023-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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Athol, MA Crash Report — March 2023 | ThatCarHitMe.com