Monthly Traffic Safety Analysis

82 CRASHES IN
STOUGHTON, MA
OCTOBER 2022

All metrics benchmarked againstOctober 2021

In October 2022, Stoughton recorded 82 crashes, a decrease of 7.87% compared to the 89 crashes reported in October 2021. While total crashes declined, the number of injuries increased significantly by 57.14%, from 7 in October 2021 to 11 in October 2022. Fatalities remained at 0 in both periods.

82

-7.9%was 89

Total Crash Events

0

Persons Killed

11

57.1%was 7

Persons Injured

1

-66.7%was 3

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the number of crashes in Stoughton decreased by 7.87%, from 89 in October 2021 to 82 in October 2022. Despite this reduction in total incidents, the number of injuries saw a notable increase of 57.14%, rising from 7 to 11 year-over-year. Fatalities remained stable at zero in both periods.

1

Hit-and-Run Crashes — October 2022

-66.7% vs prior (3)

The number of hit-and-run crashes decreased significantly from 3 incidents in October 2021 to 1 incident in October 2022. Consequently, the hit-and-run rate also declined from 3.4% of total crashes in the prior period to 1.2% in the current period, indicating a downward trend.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

11

Motorists Injured

Prior: 757.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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 October 2022, the peak day for crashes was Friday with 18 incidents, whereas in October 2021, both Friday and Saturday shared the peak with 15 crashes each. The peak crash hour also changed, moving from 4 p.m. with 8 crashes in the prior period to 8 a.m. with 11 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes remained at 0 in both October 2021 and October 2022. However, the total number of persons injured increased by 57.14%, from 7 in the prior period to 11 in the current period. The proportion of crashes categorized as resulting in minor injury (code B) increased from 2.2% (2 crashes) in October 2021 to 8.5% (7 crashes) in October 2022.

Outcome by Severity (Crash Events)

Minor Injury7minor injury crashes8.5%
250.0%prior 2
Possible Injury2possible injury crashes2.4%
0.0%prior 2
No Injury7no injury crashes8.5%
40.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' remained the most frequent, increasing from 22 crashes in October 2021 to 26 crashes in October 2022. 'Followed too closely' saw a notable increase of 5 crashes, rising from 9 to 14, and moved from the third to the second most common factor. Conversely, 'Failed to yield right of way' decreased by 5 crashes, from 13 to 8, and its ranking dropped from second to third.

Officer-Reported Primary Contributing Cause

No improper driving26 (31.7%)18.2%prior 22
Followed too closely14 (17.1%)55.6%prior 9
Failed to yield right of way8 (9.8%)-38.5%prior 13
Inattention6 (7.3%)0.0%prior 6
Disregarded traffic signs, signals, road markings4 (4.9%)-20.0%prior 5
Distracted4 (4.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (2.4%)
Glare2 (2.4%)
Other improper action2 (2.4%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (2.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 50 in October 2021 to 61 in October 2022, representing a higher proportion of total crashes. Concurrently, incidents under 'Dark - lighted roadway' conditions decreased from 18 to 10 crashes year-over-year. There was also a notable reduction in crashes on wet road surfaces, falling from 29 in the prior period to 17 in the current period.

Weather

Clear61 (75.3%)
22.0%prior 50
Rain11 (13.6%)
0.0%prior 11
Cloudy/Rain5 (6.2%)
-50.0%prior 10
Cloudy4 (4.9%)
-55.6%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Weather condition at time of crash

Lighting

Daylight63 (76.8%)
5.0%prior 60
Dark - lighted roadway10 (12.2%)
-44.4%prior 18
Dark - roadway not lighted6 (7.3%)
-25.0%prior 8
Dusk2 (2.4%)
Dark - unknown roadway lighting1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Lighting condition field

Road Surface

Dry63 (77.8%)
5.0%prior 60
Wet17 (21.0%)
-41.4%prior 29
Sand, mud, dirt, oil, gravel1 (1.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 172 in October 2021 to 159 in October 2022. Toyota remained the most frequently involved vehicle make, increasing from 32 to 39 vehicles. Ford saw a decrease of 10 vehicles, falling from 25 to 15, while Honda also decreased from 23 to 16 vehicles involved.

Top Vehicle Makes (159 vehicles)

1
TOYOTA39 (24.5%)
21.9%prior 32
2
HONDA16 (10.1%)
-30.4%prior 23
3
FORD15 (9.4%)
-40.0%prior 25
4
CHEVROLET9 (5.7%)
-47.1%prior 17
5
NISSAN9 (5.7%)
-35.7%prior 14
6
JEEP9 (5.7%)
7
HYUNDAI8 (5%)
33.3%prior 6
8
MAZDA6 (3.8%)
9
DODGE5 (3.1%)
10
MERCEDES-BENZ4 (2.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Vehicle unit records

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

Sex Distribution (182 persons with recorded sex)

Male97 (53.3%)
-13.4%prior 112
Female85 (46.7%)
-2.3%prior 87

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 38 in October 2021 to 31 in October 2022, and incidents in 35 mph zones also declined from 26 to 15. Conversely, crashes in 65 mph zones increased from 8 to 13, and those in 40 mph zones rose from 9 to 11. This indicates a shift in the distribution of crashes, with fewer occurring in moderate speed zones and more occurring in higher speed zones.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-10-01 to 2022-10-31 · 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: 2022-10-01 through 2022-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-10-01 through 2022-10-31 (31 days)
  • Geographic scope: STOUGHTON, MA
  • Total crash records analyzed: 82
  • Total persons involved: 195
  • Total vehicles involved: 159

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: October 2022." Published June 21, 2026. Reporting period: 2022-10-01 to 2022-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/stoughton/october-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 — October 2022 | ThatCarHitMe.com