Monthly Traffic Safety Analysis

65 CRASHES IN
STOUGHTON, MA
MAY 2023

All metrics benchmarked againstMay 2022

In May 2023, STOUGHTON experienced 65 crashes, a decrease of 8.45% from the 71 crashes reported in May 2022. Despite the overall reduction in crashes, total injuries increased by 100%, rising from 2 in May 2022 to 4 in May 2023.

65

-8.5%was 71

Total Crash Events

0

Persons Killed

4

100.0%was 2

Persons Injured

0

Fatal Crash Events

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. 57 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in STOUGHTON shows a decrease, with total crashes falling by 8.45% from 71 in May 2022 to 65 in May 2023. However, total injuries saw a significant increase of 100%, rising from 2 in May 2022 to 4 in May 2023, while fatalities remained at 0 in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

4

Motorists Injured

Prior: 2100.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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 Sunday (15 crashes) in May 2022 to Thursday (14 crashes) in May 2023. Similarly, the peak hour for crashes moved from 4 PM (8 crashes) in May 2022 to 3 PM (6 crashes) in May 2023. Notably, crashes on Sunday decreased significantly from 15 to 2, while crashes on Thursday increased from 8 to 14.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both May 2022 and May 2023. Total injuries increased by 100%, from 2 injured persons in May 2022 to 4 injured persons in May 2023. The prior period recorded 1 serious injury and 1 minor injury, while the current period reported 3 minor injuries and 1 possible injury.

Outcome by Severity (Crash Events)

Minor Injury3minor injury crashes4.6%
200.0%prior 1
Possible Injury1possible injury crashes1.5%
No Injury4no injury crashes6.2%
-20.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Most severe injury per crash record

Top Contributing Factors

The top contributing factor, 'Failed to yield right of way,' increased by 5 crashes (a 33.3% increase) from 15 in May 2022 to 20 in May 2023, becoming the leading factor. Conversely, 'No improper driving' decreased by 7 crashes (a 31.8% decrease) from 22 to 15. 'Inattention' crashes saw a substantial increase of 6 incidents (a 300% increase), rising from 2 to 8 crashes.

Officer-Reported Primary Contributing Cause

Failed to yield right of way20 (30.8%)33.3%prior 15
No improper driving15 (23.1%)-31.8%prior 22
Inattention8 (12.3%)
Followed too closely4 (6.2%)-33.3%prior 6
Over-correcting/over-steering3 (4.6%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (3.1%)
Visibility obstructed2 (3.1%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.1%)
Disregarded traffic signs, signals, road markings1 (1.5%)
Fatigued/asleep1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on wet road surfaces increased significantly by 500%, from 1 incident in May 2022 to 6 incidents in May 2023. Daylight crashes decreased from 60 to 52, while crashes in dark conditions with unlighted roadways increased from 1 to 5. Clear weather conditions remained the most common, though the count decreased from 62 to 56 crashes.

Weather

Clear56 (87.5%)
-9.7%prior 62
Cloudy2 (3.1%)
-71.4%prior 7
Rain2 (3.1%)
Cloudy/Rain1 (1.6%)
Rain/Cloudy1 (1.6%)
Clear/Cloudy1 (1.6%)
Clear/Rain1 (1.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Weather condition at time of crash

Lighting

Daylight52 (80.0%)
-13.3%prior 60
Dark - lighted roadway7 (10.8%)
16.7%prior 6
Dark - roadway not lighted5 (7.7%)
Dusk1 (1.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Lighting condition field

Road Surface

Dry59 (90.8%)
-15.7%prior 70
Wet6 (9.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased slightly from 133 in May 2022 to 128 in May 2023. Honda vehicles involved in crashes increased from 15 to 23, a 53.3% rise, while Toyota and Ford remained stable at 23 and 14 respectively. The age group 0-15 saw a 100% increase in persons involved, from 4 to 8, and the 21-25 age group increased from 20 to 27 persons.

Top Vehicle Makes (128 vehicles)

1
TOYOTA23 (18%)
0.0%prior 23
2
HONDA23 (18%)
53.3%prior 15
3
FORD14 (10.9%)
0.0%prior 14
4
NISSAN12 (9.4%)
0.0%prior 12
5
CHEVROLET10 (7.8%)
-9.1%prior 11
6
HYUNDAI7 (5.5%)
7
GMC5 (3.9%)
8
JEEP5 (3.9%)
-28.6%prior 7
9
KIA4 (3.1%)
10
MERCEDES-BENZ3 (2.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Vehicle unit records

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

Sex Distribution (149 persons with recorded sex)

Male85 (57.0%)
9.0%prior 78
Female64 (43.0%)
-23.8%prior 84

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 35 mph speed zone decreased by 8 incidents, from 24 in May 2022 to 16 in May 2023. Conversely, crashes in the 30 mph speed zone increased by 4 incidents, rising from 23 to 27. Crashes in the 45 mph zone decreased from 4 to 1, while crashes in the 20 mph zone increased from 0 to 2.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-05-01 to 2023-05-31 · 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: 2023-05-01 through 2023-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-05-01 through 2023-05-31 (31 days)
  • Geographic scope: STOUGHTON, MA
  • Total crash records analyzed: 65
  • Total persons involved: 163
  • 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: May 2023." Published June 21, 2026. Reporting period: 2023-05-01 to 2023-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/may-2023-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 — May 2023 | ThatCarHitMe.com