Yearly Traffic Safety Analysis

4 CRASHES IN
WORTHINGTON, MA
2023

All metrics benchmarked against2022

In Worthington, total vehicle crashes decreased by 33.3% year-over-year, falling from 6 incidents in 2022 to 4 in 2023. Throughout both periods, there were no recorded fatalities or injuries resulting from these crashes. The most notable shift was the overall reduction in crash volume, accompanied by a change in the daily and hourly patterns of when these incidents occurred.

4

-33.3%was 6

Total Crash Events

0

Persons Killed

0

Persons Injured

0

Fatal Crash Events

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. 4 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

The overall crash trend in Worthington is downward. Total reported crashes decreased from 6 in the prior year to 4 in the current year, representing a 33.3% reduction. Importantly, both periods recorded zero fatalities and zero injuries, indicating that while crash frequency declined, the severity of outcomes remained consistently at the lowest level.

When Crashes Happen

The timing of crashes shifted between the two years. In 2022, the peak days for crashes were Monday and Tuesday, each with 2 incidents. In 2023, the peak shifted to Wednesday, which also saw 2 crashes. The hourly pattern also changed, with 2022 showing distinct peaks at midday (2 crashes at 12 p.m.) and in the evening (2 crashes at 8 p.m.), while 2023's crashes were more evenly distributed across four separate afternoon and evening hours.

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)

Top Contributing Factors

A comparison of contributing factors shows that while speed-related issues remained stable, other driver behaviors changed. The number of crashes attributed to "No improper driving" decreased from 2 in 2022 to 1 in 2023. Crashes involving "Driving too fast for conditions" and "Exceeded authorized speed limit" held steady at 1 incident each for both years. Notably, "Inattention" was a factor in one 2022 crash but was not among the top factors in 2023, whereas "Fatigued/asleep" appeared as a factor in one 2023 crash after not being a top factor in the prior year.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions1 (25%)
Exceeded authorized speed limit1 (25%)
Fatigued/asleep1 (25%)
No improper driving1 (25%)

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

Crash conditions varied year-over-year, particularly regarding lighting and road surface. The proportion of crashes occurring in dark conditions increased, accounting for 75% of incidents (3 of 4) in 2023 compared to 50% (3 of 6) in 2022. Conversely, crashes on non-dry road surfaces became less frequent, dropping from 67% of all crashes in 2022 (4 involving ice, snow, or other materials) to 25% in 2023 (1 involving snow).

Weather

Clear3 (75.0%)
Snow1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Dark - roadway not lighted2 (50.0%)
Dark - lighted roadway1 (25.0%)
Daylight1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry3 (75.0%)
Snow1 (25.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (4 vehicles)

1
CHEVROLET2 (50%)
2
BMW1 (25%)
3
SUBARU1 (25%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

The distribution of crashes across different speed zones changed between the two periods. In 2022, the majority of crashes (4 of 6) occurred in 35 mph zones. In 2023, crashes in 35 mph zones decreased to 2. A crash was recorded in a 30 mph zone in 2023, a speed limit not present in the 2022 data, while a crash in a 40 mph zone from 2022 was not repeated in 2023. There were no fatalities in any speed zone during either year.

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: WORTHINGTON, MA
  • Total crash records analyzed: 4
  • Total persons involved: 4
  • Total vehicles involved: 4

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). "WORTHINGTON, 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/worthington/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

Worthington, MA Crash Report — 2023 | ThatCarHitMe.com