ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · STOUGHTON, MA · JULY 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.
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GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/stoughton/july-2025-report
Monthly Traffic Safety Analysis
65 CRASHES IN
STOUGHTON, MA
JULY 2025
In Stoughton, total crashes increased by 8.3% from 60 in July 2024 to 65 in July 2025. Despite this increase, total injuries decreased by 26.8%, from 41 to 30. The most notable shift was a 280% increase in crashes where 'Failed to yield right of way' was a contributing factor, rising from 5 to 19 crashes.
65
▲ 8.3%was 60
Total Crash Events
0
Persons Killed
30
▼ -26.8%was 41
Persons Injured
3
▼ -40.0%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. 2 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, crashes in Stoughton saw an increase of 5 incidents, rising from 60 in July 2024 to 65 in July 2025, an 8.3% year-over-year increase. Total fatalities remained at 0 in both periods, while total injuries decreased by 11, from 41 to 30, representing a 26.8% reduction.
3
Hit-and-Run Crashes — July 2025
▼ -40.0% vs prior (5)
The number of hit-and-run crashes decreased by 40%, from 5 in July 2024 to 3 in July 2025. The hit-and-run rate also decreased from 8.3% of all crashes in July 2024 to 4.6% in July 2025.
Vulnerable Road User Casualties
0
Motorists Killed
30
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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 year-over-year. In July 2025, Thursday became the peak day for crashes with 16 incidents, a change from Tuesday which was the peak day in July 2024 also with 16 crashes. The peak crash hour also moved from 9 PM in July 2024 (8 crashes) to 10 AM in July 2025 (8 crashes).
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, total injuries decreased from 41 in July 2024 to 30 in July 2025. Serious injuries (Severity A) saw an increase from 2 to 3, while possible injuries (Severity C) decreased from 12 to 7. The proportion of crashes resulting in no injury increased from 58.3% to 64.6% year-over-year.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record
Top Contributing Factors
The most significant change in contributing factors was a 280% increase in crashes attributed to 'Failed to yield right of way,' rising from 5 crashes in July 2024 to 19 crashes in July 2025. Conversely, crashes due to 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' decreased by 60%, from 5 to 2. 'No improper driving' remained a leading factor, increasing from 16 crashes to 19 crashes.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes occurring in clear weather conditions increased from 44 in July 2024 to 51 in July 2025, and those on dry road surfaces rose from 50 to 60. Conversely, crashes on wet road surfaces decreased by 50%, from 10 to 5. There was a notable shift in lighting conditions, with daylight crashes increasing by 15 (from 40 to 55), while crashes in dark-lighted roadway conditions decreased by 8 (from 14 to 6).
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased from 113 in July 2024 to 128 in July 2025. Toyota remained the most frequent vehicle make involved, increasing from 23 to 28. There was a notable increase in the number of persons aged 65 and over involved in crashes, rising from 10 to 29, and the number of females involved increased from 52 to 68.
Top Vehicle Makes (128 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records
8 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (147 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · Person-level records linked to crash events
Speed Limit Zones
The highest number of crashes in July 2025 occurred in 30 mph zones, with 28 crashes, an increase from 19 crashes in July 2024. Crashes in 35 mph zones decreased from 16 to 13, and 65 mph zones decreased from 6 to 4. No fatal crashes were reported across any speed limit zone in either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-07-01 through 2025-07-31 (31 days)
- Geographic scope: STOUGHTON, MA
- Total crash records analyzed: 65
- Total persons involved: 160
- Total vehicles involved: 128
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: July 2025." Published June 21, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/july-2025-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: 2025-07-01 – 2025-07-31
Generated: June 21, 2026 · All rights reserved