ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WILLIAMSTOWN, 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/williamstown/2023-annual-report
Yearly Traffic Safety Analysis
140 CRASHES IN
WILLIAMSTOWN, MA
2023
In 2023, Williamstown recorded 140 total crashes, a decrease from the 158 crashes in 2022, representing an 11.4% year-over-year decline. Despite the reduction in total incidents, the number of people injured rose significantly. Total injuries increased from 24 in 2022 to 39 in 2023, a 62.5% rise.
140
▼ -11.4%was 158
Total Crash Events
0
Persons Killed
39
▲ 62.5%was 24
Persons Injured
8
▲ 60.0%was 5
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. 3 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 trend in Williamstown shows a decrease in the total number of crashes, falling by 11.4% from 158 in 2022 to 140 in 2023. However, this downward trend in crash volume was accompanied by a notable 62.5% increase in the number of reported injuries, which rose from 24 to 39. There were no fatalities reported in either period.
8
Hit-and-Run Crashes — 2023
▲ 60.0% vs prior (5)
Hit-and-run incidents increased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes rose from 5 in 2022 to 8 in 2023, a 60% increase. Consequently, the hit-and-run rate trended upward, increasing from 3.2% of all crashes in 2022 to 5.7% in 2023.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
0
Motorists Killed
2
Pedestrians Injured
1
Cyclists Injured
36
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 shifted between the two years. In 2023, the peak day for crashes was Friday with 28 incidents, moving from Wednesday which saw the most crashes (30) in 2022. The peak hour for crashes also shifted earlier in the day, from 5 p.m. (16 crashes) in 2022 to a tie between 1 p.m. and 2 p.m. (14 crashes each) in 2023.
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
No fatal crashes were recorded in either 2022 or 2023. The proportion of crashes resulting in any injury increased from 14.5% in 2022 to 20.7% in 2023. This was driven by a substantial rise in the share of "Possible Injury" crashes, which grew from 1.9% of all crashes in 2022 to 11.4% in 2023. Conversely, the share of crashes involving "Serious Injury" or "Minor Injury" decreased year-over-year.
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 improper driving factors remained consistent, though their counts generally decreased. Crashes attributed to "Inattention" fell from 30 in 2022 to 28 in 2023. The count of crashes involving "Other improper action" decreased from 23 to 12, and "Followed too closely" incidents dropped from 14 to 11. The share of crashes where "No improper driving" was cited remained stable at 28.5% in 2022 and 27.9% 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
In both periods, most crashes occurred in clear weather and daylight on dry roads. The share of crashes in daylight was stable, at 71.5% in 2022 and 73.6% in 2023. Crashes on dry roads decreased as a proportion of the total, from 76.6% in 2022 to 72.1% in 2023. The count of crashes in adverse weather increased, with rain-related incidents rising from 7 to 12 and snow-related incidents from 5 to 9.
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 Toyota, Honda, and Subaru in both years, with only minor shifts in their counts. Regarding persons involved, the 65+ age group was the largest demographic in both periods, with 53 individuals in 2022 and 50 in 2023. The number of persons in the 16-20 age group involved in crashes saw a notable decrease from 34 in 2022 to 23 in 2023.
Top Vehicle Makes (219 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
33 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (231 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
The distribution of crashes across speed zones shifted year-over-year. In 2022, the 30 mph zone had the most crashes (44), but in 2023, crashes in this zone decreased to 29. The 35 mph zone saw a significant increase, from 22 crashes in 2022 to 38 in 2023, becoming the most common speed zone for incidents. No fatal crashes were recorded in any speed zone in either period.
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: WILLIAMSTOWN, MA
- Total crash records analyzed: 140
- Total persons involved: 264
- Total vehicles involved: 219
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). "WILLIAMSTOWN, 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/williamstown/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