ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · STOUGHTON, MA · 2025
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/2025-annual-report
Yearly Traffic Safety Analysis
729 CRASHES IN
STOUGHTON, MA
2025
In 2025, Stoughton recorded 729 total traffic crashes, a 5.8% decrease from the 774 crashes reported in 2024. This downward trend was accompanied by a significant reduction in crash severity, with total fatalities decreasing from 3 to 1 and total injuries falling by 31.6% from 376 to 257 year-over-year.
729
▼ -5.8%was 774
Total Crash Events
1
▼ -66.7%was 3
Persons Killed
257
▼ -31.6%was 376
Persons Injured
75
▲ 15.4%was 65
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 23 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall traffic safety trends in Stoughton improved from 2024 to 2025. Total crashes decreased by 5.8%, from 774 to 729. This was mirrored by a substantial decline in negative outcomes, as total injuries dropped by 31.6% and the number of fatalities fell from 3 to 1.
75
Hit-and-Run Crashes — 2025
▲ 15.4% vs prior (65)
Hit-and-run incidents trended upwards in 2025 compared to the previous year. The total number of hit-and-run crashes increased from 65 in 2024 to 75 in 2025. Correspondingly, the hit-and-run rate, which measures the proportion of all crashes that were hit-and-runs, rose from 8.4% in 2024 to 10.3% in 2025.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
0
Other Killed
2
Pedestrians Injured
1
Cyclists Injured
253
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The temporal patterns of crashes in Stoughton remained broadly consistent year-over-year. Friday was the peak day for crashes in both 2025 (113 crashes) and 2024 (135 crashes). The peak hour for collisions shifted slightly later, from 4 PM in 2024 (65 crashes) to 5 PM in 2025 (68 crashes), aligning with the evening commuter rush in both periods.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity decreased notably from 2024 to 2025. The number of fatal crashes fell from 3 to 1, and serious injury crashes were halved from 22 to 11. Crashes resulting in 'Possible Injury' also saw a significant reduction, dropping from 99 to 56. Consequently, the proportion of crashes with no reported injuries increased from 66.1% in 2024 to 70.8% in 2025.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
While 'No improper driving' was the most frequently cited factor in both years, its count decreased from 251 to 230. The most significant shift was in crashes attributed to 'Failed to yield right of way,' which increased in count by 64.5% from 79 in 2024 to 130 in 2025, remaining the second-ranked factor. Another notable increase was seen in 'Failure to keep in proper lane or running off road,' with the count increasing from 22 to 41.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in both periods predominantly occurred in clear weather and on dry roads, with no significant year-over-year change in these conditions. However, there was a noticeable shift in lighting conditions. The proportion of crashes happening during daylight hours increased from 63.4% of all crashes in 2024 to 71.7% in 2025. Correspondingly, crashes in darkness on lighted roadways decreased as a share of the total, from 23.0% in 2024 to 18.7% in 2025.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in crashes remained consistent, with Toyota, Honda, and Ford ranking as the top three in both 2024 and 2025. While the total number of persons involved in crashes decreased, the representation of certain age groups shifted. The proportion of persons aged 65 and older involved in crashes increased from 9.5% of the total in 2024 to 12.3% in 2025. Similarly, the 35-44 age group's involvement grew from 16.2% to 17.9% of all persons involved.
Top Vehicle Makes (1,375 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
143 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,521 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones showed some changes year-over-year. Crashes in 30 mph zones remained stable with 284 incidents in 2025 compared to 283 in 2024. However, there were fewer crashes in some higher speed zones, with incidents in 35 mph zones decreasing from 179 to 150. The single fatality in 2025 occurred in a 35 mph zone, whereas all three fatalities in 2024 occurred in a 40 mph zone.
Fatal crashes by zone: 35 mph: 1 of 150 (0.667%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: STOUGHTON, MA
- Total crash records analyzed: 729
- Total persons involved: 1,686
- Total vehicles involved: 1,375
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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/2025-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: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved