ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · STOUGHTON, 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/stoughton/2023-annual-report
Yearly Traffic Safety Analysis
770 CRASHES IN
STOUGHTON, MA
2023
In 2023, Stoughton recorded 770 total vehicle crashes, a 4.3% decrease from the 805 crashes reported in 2022. Despite the overall reduction in incidents, the most notable year-over-year shift was a 176% increase in the number of people injured, which rose from 50 in 2022 to 138 in 2023.
770
▼ -4.3%was 805
Total Crash Events
2
▼ -33.3%was 3
Persons Killed
138
▲ 176.0%was 50
Persons Injured
38
▲ 245.5%was 11
Hit-and-Run Crashes
Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 433 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 shows a decrease in total crashes, which fell by 4.3% from 805 in 2022 to 770 in 2023. However, this decline in crash volume was contrasted by a sharp increase in crash severity, as the number of persons injured grew by 176% year-over-year. The number of fatalities saw a slight decrease from 3 in the prior year to 2 in the current year.
38
Hit-and-Run Crashes — 2023
▲ 245.5% vs prior (11)
Hit-and-run incidents showed a significant upward trend. The number of hit-and-run crashes increased by 245.5%, from 11 in 2022 to 38 in 2023. The hit-and-run rate, which measures these incidents as a percentage of total crashes, rose from 1.4% in the prior year to 4.9% in the current year.
Vulnerable Road User Casualties
0
Pedestrians Killed
2
Motorists Killed
0
Other Killed
4
Pedestrians Injured
133
Motorists Injured
1
Other 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 periods. In 2023, Monday was the most frequent day for crashes with 126 incidents, a change from 2022 when Friday was the peak day with 140 crashes. The peak hour for collisions also moved from 2 p.m. in 2022 (67 crashes) to the 5 p.m. hour in 2023 (64 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
While total crashes declined, the severity of outcomes increased notably from 2022 to 2023. The total number of people injured rose from 50 to 138, a 176% increase. Crashes resulting in minor injuries increased from 27 to 50, and those with possible injuries rose from 9 to 44. Consequently, the proportion of all crashes that resulted in an injury increased from 4.7% in 2022 to 12.9% 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
The leading contributing factors remained consistent, but their counts shifted year-over-year. Crashes attributed to "Inattention" saw a significant 50.9% increase in count, rising from 53 incidents in 2022 to 80 in 2023. Similarly, crashes where a driver "Failed to yield right of way" grew by 11.1% in count, from 90 to 100. In contrast, crashes with "No improper driving" recorded decreased from 281 to 240.
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 crashes occurring in adverse conditions. The number of crashes on wet road surfaces increased from 122 in 2022 to 159 in 2023, raising its share of total crashes from 15.2% to 20.6%. In line with this, crashes reported during rain increased from 45 to 66. The majority of crashes in both years occurred in clear weather and daylight, though the proportion of daylight crashes fell slightly from 69.6% to 66.6%.
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 five most common vehicle makes involved in crashes were identical in both years: Toyota, Honda, Ford, Nissan, and Chevrolet. Toyota remained the top make with 258 vehicles in 2023, a decrease from 281 in 2022. Regarding demographics, the share of persons aged 65 and older involved in crashes decreased from 12.0% of all persons in 2022 to 10.6% in 2023.
Top Vehicle Makes (1,428 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
103 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,596 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
Crash locations shifted between speed zones year-over-year. Incidents increased in 65 mph zones (from 93 to 113) and 30 mph zones (from 301 to 316). Conversely, crashes decreased in 35 mph zones (from 181 to 155) and 40 mph zones (from 117 to 90). Both of 2023's fatal crashes occurred in a 65 mph zone, whereas 2022's three fatalities were distributed across 35, 40, and 65 mph zones.
Fatal crashes by zone: 65 mph: 2 of 113 (1.77%)
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: STOUGHTON, MA
- Total crash records analyzed: 770
- Total persons involved: 1,735
- Total vehicles involved: 1,428
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). "STOUGHTON, 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/stoughton/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