Monthly Traffic Safety Analysis

59 CRASHES IN
STOUGHTON, MA
NOVEMBER 2022

All metrics benchmarked againstNovember 2021

In November 2022, STOUGHTON experienced a notable decrease in overall crash incidents compared to November 2021, with total crashes falling from 81 to 59, representing a 27.2% reduction. Concurrently, total injuries saw a substantial decline, dropping from 7 to 1, marking the most significant year-over-year shift.

59

-27.2%was 81

Total Crash Events

0

Persons Killed

1

-85.7%was 7

Persons Injured

4

-20.0%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. 49 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a significant decline in crash activity in STOUGHTON year-over-year. Total crashes decreased by 27.2%, from 81 crashes in November 2021 to 59 crashes in November 2022. Total injuries also saw a substantial reduction, falling by 85.7% from 7 to 1 during the same period.

4

Hit-and-Run Crashes — November 2022

-20.0% vs prior (5)

The number of hit-and-run crashes decreased from 5 incidents in November 2021 to 4 in November 2022. The hit-and-run crash rate increased slightly from 6.2% of total crashes in November 2021 to 6.8% in November 2022.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 7-85.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes shifted between the two periods. In November 2022, the peak day for crashes was Thursday with 17 incidents, while in November 2021, Friday was the peak day with 16 crashes. The peak crash hour also shifted from 4 PM with 10 crashes in November 2021 to 5 PM with 8 crashes in November 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both November 2021 and November 2022. Total injuries decreased significantly from 7 in November 2021 to 1 in November 2022. The number of crashes resulting in a 'Possible Injury' decreased from 2 in November 2021 to 1 in November 2022, and 'Minor Injury' crashes, which accounted for 4 incidents in November 2021, were not reported in November 2022.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes1.7%
-50.0%prior 2
No Injury9no injury crashes15.3%
200.0%prior 3

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' decreased by 6 crashes (from 25 to 19), and 'Inattention' saw a 75% reduction in count, dropping from 8 crashes to 2 crashes. Conversely, 'Followed too closely' incidents increased by 1 crash, from 8 to 9. 'Failed to yield right of way' decreased by 4 crashes, from 11 to 7.

Officer-Reported Primary Contributing Cause

No improper driving19 (32.2%)-24.0%prior 25
Followed too closely9 (15.3%)12.5%prior 8
Failed to yield right of way7 (11.9%)-36.4%prior 11
Inattention2 (3.4%)-75.0%prior 8
Failure to keep in proper lane or running off road2 (3.4%)
Fatigued/asleep2 (3.4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (3.4%)
Visibility obstructed2 (3.4%)
Wrong side or wrong way2 (3.4%)
Distracted1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring under 'Clear' weather conditions decreased from 63 in November 2021 to 49 in November 2022. Similarly, crashes on 'Dry' road surfaces decreased from 69 to 53, and those on 'Wet' surfaces decreased from 12 to 6. Crashes during 'Daylight' conditions also saw a reduction, from 46 to 25.

Weather

Clear49 (83.1%)
-22.2%prior 63
Cloudy3 (5.1%)
-62.5%prior 8
Cloudy/Rain3 (5.1%)
Rain3 (5.1%)
-57.1%prior 7
Clear/Unknown1 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Weather condition at time of crash

Lighting

Daylight25 (42.4%)
-45.7%prior 46
Dark - lighted roadway21 (35.6%)
-19.2%prior 26
Dark - roadway not lighted5 (8.5%)
-16.7%prior 6
Dawn3 (5.1%)
Dusk3 (5.1%)
Dark - unknown roadway lighting2 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Lighting condition field

Road Surface

Dry53 (89.8%)
-23.2%prior 69
Wet6 (10.2%)
-50.0%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 152 in November 2021 to 112 in November 2022. While TOYOTA remained the most frequently involved make with 29 vehicles in both periods, HONDA decreased from 20 to 16, and CHEVROLET decreased from 12 to 8. Among persons involved, the 55-64 age group saw a significant decrease from 23 to 10 individuals, while the 0-15 age group increased from 8 to 10.

Top Vehicle Makes (112 vehicles)

1
TOYOTA29 (25.9%)
0.0%prior 29
2
HONDA16 (14.3%)
-20.0%prior 20
3
NISSAN9 (8%)
-25.0%prior 12
4
FORD9 (8%)
-10.0%prior 10
5
CHEVROLET8 (7.1%)
-33.3%prior 12
6
JEEP4 (3.6%)
-50.0%prior 8
7
BUIC4 (3.6%)
8
SUBARU3 (2.7%)
-40.0%prior 5
9
MAZDA3 (2.7%)
10
DODGE3 (2.7%)
-50.0%prior 6

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Vehicle unit records

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

Sex Distribution (129 persons with recorded sex)

Male69 (53.5%)
-17.9%prior 84
Female60 (46.5%)
-16.7%prior 72

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 40 mph speed zones saw the largest decrease, falling from 15 incidents in November 2021 to 7 in November 2022. Crashes in 35 mph zones also decreased from 17 to 12, while crashes in 65 mph zones slightly increased from 8 to 9. No fatal crashes were reported in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-11-01 to 2022-11-30 · 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: 2022-11-01 through 2022-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-11-01 through 2022-11-30 (30 days)
  • Geographic scope: STOUGHTON, MA
  • Total crash records analyzed: 59
  • Total persons involved: 140
  • Total vehicles involved: 112

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: November 2022." Published June 21, 2026. Reporting period: 2022-11-01 to 2022-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/november-2022-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 — November 2022 | ThatCarHitMe.com