Monthly Traffic Safety Analysis

67 CRASHES IN
STOUGHTON, MA
JUNE 2025

All metrics benchmarked againstJune 2024

STOUGHTON experienced a slight decrease in total crashes, from 68 in June 2024 to 67 in June 2025, representing a 1.5% decline. The most notable year-over-year shift was a significant 27.3% reduction in total injuries, decreasing from 33 to 24.

67

-1.5%was 68

Total Crash Events

0

Persons Killed

24

-27.3%was 33

Persons Injured

6

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 · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in STOUGHTON remained relatively stable year-over-year, with a minor decrease of 1 crash, from 68 to 67. However, total injuries saw a more substantial decline, decreasing by 9 injuries, from 33 to 24, indicating a positive trend in injury reduction.

6

Hit-and-Run Crashes — June 2025

0.0% vs prior (6)

The number of hit-and-run crashes remained constant at 6 for both June 2024 and June 2025. The hit-and-run rate saw a minor increase from 8.8% in June 2024 to 9% in June 2025.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

24

Motorists Injured

Prior: 32-25.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes shifted from Saturday, with 17 crashes in June 2024, to Monday, with 16 crashes in June 2025. While 5p remained the peak hour for crashes in both periods, the count increased from 6 crashes in June 2024 to 8 crashes in June 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatal crashes in either June 2024 or June 2025. Total injuries decreased from 33 to 24 year-over-year, a 27.3% reduction. Serious injuries (Severity A) saw a slight increase from 1 crash (1.5% of crashes) to 2 crashes (3% of crashes), while possible injuries (Severity C) decreased from 9 crashes (13.2% of crashes) to 3 crashes (4.5% of crashes).

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes3%
100.0%prior 1
Minor Injury10minor injury crashes14.9%
-9.1%prior 11
Possible Injury3possible injury crashes4.5%
-66.7%prior 9
No Injury47no injury crashes70.1%
2.2%prior 46

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

The count of 'No improper driving' crashes decreased from 21 to 18. 'Failed to yield right of way' crashes increased significantly from 8 to 15, an increase of 7 crashes, maintaining its position as a top contributing factor. 'Followed too closely' crashes also doubled, increasing from 4 to 8 crashes, and rose in ranking.

Officer-Reported Primary Contributing Cause

No improper driving18 (26.9%)-14.3%prior 21
Failed to yield right of way15 (22.4%)87.5%prior 8
Followed too closely8 (11.9%)
Inattention4 (6%)-20.0%prior 5
Failure to keep in proper lane or running off road4 (6%)
Disregarded traffic signs, signals, road markings4 (6%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3%)
Operating defective equipment1 (1.5%)
Other improper action1 (1.5%)
Over-correcting/over-steering1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in daylight conditions increased from 50 in June 2024 to 58 in June 2025. Conversely, crashes occurring in 'Dark - lighted roadway' conditions decreased from 13 to 5. The number of crashes during clear weather remained consistent at 53 in June 2024 and 54 in June 2025.

Weather

Clear54 (81.8%)
1.9%prior 53
Cloudy4 (6.1%)
-20.0%prior 5
Rain3 (4.5%)
Clear/Cloudy2 (3.0%)
Clear/Clear1 (1.5%)
Cloudy/Cloudy1 (1.5%)
Cloudy/Rain1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight58 (87.9%)
16.0%prior 50
Dark - lighted roadway5 (7.6%)
-61.5%prior 13
Dark - roadway not lighted2 (3.0%)
Dark - unknown roadway lighting1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry58 (87.9%)
-4.9%prior 61
Wet8 (12.1%)
14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The age distribution of persons involved in crashes showed notable shifts; the 0-15 age group decreased from 14 to 2, and the 16-20 age group decreased from 17 to 6. Conversely, the 21-25 age group increased from 15 to 27, and the 65+ age group increased from 11 to 19. Toyota remained the top vehicle make involved, though its count decreased from 24 to 21, while Ford increased its representation from 7 to 15, moving into the top three makes.

Top Vehicle Makes (131 vehicles)

1
TOYOTA21 (16%)
-12.5%prior 24
2
HONDA15 (11.5%)
15.4%prior 13
3
FORD15 (11.5%)
114.3%prior 7
4
CHEVROLET8 (6.1%)
-27.3%prior 11
5
SUBARU6 (4.6%)
6
MERCEDES-BENZ5 (3.8%)
7
NISSAN5 (3.8%)
-37.5%prior 8
8
JEEP4 (3.1%)
9
INFI4 (3.1%)
10
HYUNDAI4 (3.1%)
-33.3%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

19 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (134 persons with recorded sex)

Male76 (56.7%)
-7.3%prior 82
Female58 (43.3%)
5.5%prior 55

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 29 to 24, while crashes in the 35 mph zone increased from 14 to 19. Crashes in the 65 mph speed zone saw a notable decrease from 8 to 2. There were no fatal crashes reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: STOUGHTON, MA
  • Total crash records analyzed: 67
  • Total persons involved: 156
  • Total vehicles involved: 131

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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/june-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

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Stoughton, MA Crash Report — June 2025 | ThatCarHitMe.com