ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · STOUGHTON, MA · 2022
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/2022-annual-report
Yearly Traffic Safety Analysis
805 CRASHES IN
STOUGHTON, MA
2022
In 2022, Stoughton recorded 805 total traffic crashes, a 7.5% increase from the 749 crashes documented in 2021. While overall crashes rose, there were notable decreases in specific incident types. The most significant year-over-year shift was a 54.2% reduction in hit-and-run crashes, which fell from 24 in 2021 to 11 in 2022.
805
▲ 7.5%was 749
Total Crash Events
3
▼ -25.0%was 4
Persons Killed
50
▼ -7.4%was 54
Persons Injured
11
▼ -54.2%was 24
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 699 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend shows an increase in crash volume, with total incidents rising by 7.5% from 749 in 2021 to 805 in 2022. Despite the higher number of crashes, key severity metrics improved. Total fatalities declined from 4 to 3, and the number of persons injured decreased from 54 to 50 year-over-year.
11
Hit-and-Run Crashes — 2022
▼ -54.2% vs prior (24)
Hit-and-run incidents saw a substantial downward trend. The number of hit-and-run crashes fell by 54.2%, from 24 in 2021 to 11 in 2022. As a result, the hit-and-run rate, as a percentage of all crashes, dropped from 3.2% in 2021 to 1.4% in 2022.
Vulnerable Road User Casualties
1
Pedestrians Killed
2
Motorists Killed
0
Pedestrians Injured
50
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In 2022, the peak day for crashes was Friday with 140 incidents, a change from Thursday in 2021, which saw 123 crashes. The daily peak hour also moved earlier in the day, from the 5 p.m. hour in 2021 (68 crashes) to the 2 p.m. hour in 2022 (67 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The number of fatal crashes remained stable at 3 incidents in both 2021 and 2022, leading to a slight decrease in the fatal crash rate from 0.40% to 0.37% due to the overall increase in crashes. The number of crashes resulting in serious injuries was also unchanged at 2 incidents. The proportion of crashes involving any level of injury remained consistent, accounting for 4.7% of all crashes in 2022 compared to 4.9% in 2021.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The top four contributing factors were identical in rank and order for both years, led by 'Failed to yield right of way' and 'Followed too closely.' However, the count of crashes attributed to 'Followed too closely' increased by 20%, from 55 incidents in 2021 to 66 in 2022. Similarly, crashes citing 'Distracted' as a factor grew in count from 11 to 16, a 45.5% increase from the prior year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crash conditions shifted toward clearer weather and drier roads in 2022 compared to the previous year. Crashes occurring in clear weather constituted 74.5% of the total in 2022, an increase from a 68.2% share in 2021. Correspondingly, the proportion of crashes on wet road surfaces decreased from 18.6% in 2021 to 15.2% in 2022.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The five most frequently involved vehicle makes—Toyota, Honda, Ford, Chevrolet, and Nissan—remained the same across both years, with minor changes in their rankings. An analysis of persons involved in crashes shows a demographic shift, with the share of individuals aged 65 and older increasing from 10.6% of the total in 2021 to 12.0% in 2022. The representation of other age groups remained relatively stable.
Top Vehicle Makes (1,456 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
106 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,654 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes shifted into different speed zones year-over-year, with notable increases in 30 mph zones (from 269 to 301 crashes) and 65 mph zones (from 69 to 93). Fatal crashes in 2022 were recorded in 35, 40, and 65 mph zones. This compares to 2021, when fatal crashes occurred in 35, 45, and 65 mph zones.
Fatal crashes by zone: 35 mph: 1 of 181 (0.552%) · 40 mph: 1 of 117 (0.855%) · 65 mph: 1 of 93 (1.075%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: STOUGHTON, MA
- Total crash records analyzed: 805
- Total persons involved: 1,785
- Total vehicles involved: 1,456
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/2022-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: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved