ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · STOUGHTON, MA · JANUARY 2026
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/january-2026-report
Monthly Traffic Safety Analysis
83 CRASHES IN
STOUGHTON, MA
JANUARY 2026
In January 2026, Stoughton experienced 83 crashes, marking a 33.9% increase from the 62 crashes reported in January 2025. Total injuries also rose significantly, from 27 to 39, representing a 44.4% increase year-over-year. The most notable shift was a 250% increase in crashes attributed to 'Driving too fast for conditions', which rose from 1 crash to 5 crashes.
83
▲ 33.9%was 62
Total Crash Events
0
Persons Killed
39
▲ 44.4%was 27
Persons Injured
12
▲ 71.4%was 7
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. 5 crashes with unreported severity are not shown in the severity breakdown.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend indicates a notable increase in crash incidents in Stoughton, with total crashes rising by 33.9% from 62 in January 2025 to 83 in January 2026. This upward trend is also reflected in a 44.4% increase in total injuries, which climbed from 27 to 39 over the same period.
12
Hit-and-Run Crashes — January 2026
▲ 71.4% vs prior (7)
Hit-and-run incidents increased in January 2026, with 12 crashes reported compared to 7 in January 2025, marking a 71.4% increase in count. The hit-and-run rate also rose from 11.3% of total crashes in January 2025 to 14.5% in January 2026, indicating an upward trend.
Vulnerable Road User Casualties
0
Motorists Killed
39
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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 January 2025, Monday was the peak day for crashes with 13 incidents, while in January 2026, Friday became the peak day with 17 crashes. The peak hour for crashes also changed from 8 AM with 8 crashes in the prior year to 2 PM with 8 crashes in the current year.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
There were no fatal crashes in either January 2025 or January 2026. However, the severity distribution of injuries changed, with 3 serious injury crashes (3.6% of total crashes) reported in January 2026, compared to none in January 2025. Minor injury crashes decreased from 12 (19.4% share) to 11 (13.3% share), while possible injury crashes remained constant at 8, though their share decreased from 12.9% to 9.6%.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Most severe injury per crash record
Top Contributing Factors
Several contributing factors saw significant changes year-over-year. Crashes attributed to 'Inattention' increased from a count of 2 to 9, while 'Driving too fast for conditions' rose from 1 crash to 5 crashes, representing a 400% increase in count. Conversely, crashes due to 'Failed to yield right of way' decreased from 9 to 7, and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' dropped from 4 to 1 crash.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Adverse weather and road surface conditions played a more prominent role in crashes in January 2026 compared to the prior year. Crashes occurring in 'Snow' weather conditions increased from 2 to 9, and those in 'Rain' conditions rose from 1 to 5. Similarly, crashes on 'Snow' road surfaces increased from 7 to 21, and on 'Wet' surfaces from 4 to 14, indicating a higher proportion of crashes under these conditions.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Road surface condition field
Vehicles & Demographics
The total number of vehicles involved in crashes increased by 37.9%, from 116 in January 2025 to 160 in January 2026. Among vehicle makes, HONDA saw a significant increase in involvement from 5 to 21 vehicles, while TOYOTA also rose from 24 to 31. The age distribution of persons involved showed a notable increase in the 26-34 age group, rising from 15 to 40 individuals, and in the 55-64 age group, increasing from 11 to 22 individuals.
Top Vehicle Makes (160 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Vehicle unit records
20 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (166 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · Person-level records linked to crash events
Speed Limit Zones
Crashes occurred across a broader range of speed zones in January 2026 compared to the prior year. The highest number of crashes continued to be in the 30 mph zone, increasing from 24 to 33. Crashes in the 65 mph zone also rose from 6 to 9, and crashes in the 40 mph zone increased from 9 to 12. There were no fatal crashes reported in any speed zone during either period.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2026-01-01 to 2026-01-31 · 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: 2026-01-01 through 2026-01-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2026-01-01 through 2026-01-31 (31 days)
- Geographic scope: STOUGHTON, MA
- Total crash records analyzed: 83
- Total persons involved: 189
- Total vehicles involved: 160
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: January 2026." Published June 21, 2026. Reporting period: 2026-01-01 to 2026-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/january-2026-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: 2026-01-01 – 2026-01-31
Generated: June 21, 2026 · All rights reserved