Monthly Traffic Safety Analysis

58 CRASHES IN
MANSFIELD, MA
OCTOBER 2022

All metrics benchmarked againstOctober 2021

In October 2022, Mansfield experienced 58 crashes, a significant increase from the 37 crashes recorded in October 2021, representing a 56.76% rise. The most notable shift is the increase in fatalities, with 2 persons killed in 1 fatal crash in October 2022, compared to zero fatalities and fatal crashes in the prior year. Total injuries also doubled from 8 to 16.

58

56.8%was 37

Total Crash Events

2

Persons Killed

16

100.0%was 8

Persons Injured

3

200.0%was 1

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

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, crash data for October shows an upward trend year-over-year in Mansfield. Total crashes increased by 21, from 37 in October 2021 to 58 in October 2022, marking a 56.76% rise. This increase was accompanied by a rise in total fatalities from 0 to 2 and a doubling of total injuries from 8 to 16.

3

Hit-and-Run Crashes — October 2022

200.0% vs prior (1)

Hit-and-run incidents increased year-over-year, with 3 crashes reported in October 2022 compared to 1 crash in October 2021. Consequently, the hit-and-run rate also rose from 2.7% to 5.2% of total crashes, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

2

Motorists Killed

Prior: 0%

1

Pedestrians Injured

Prior: 0%

15

Motorists Injured

Prior: 887.5%

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, Saturday was the peak day for crashes with 13 incidents, whereas Monday was the peak day in October 2021 with 8 crashes. The peak hour for crashes also shifted from 3 p.m. with 4 crashes in October 2021 to 2 p.m. with 7 crashes in October 2022.

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

Crash severity saw a notable increase in the current period, with 1 fatal crash and 2 total fatalities in October 2022, compared to zero in October 2021. The number of injury crashes (Minor and Possible) increased from 7 in October 2021 to 11 in October 2022. While the share of injury crashes remained relatively stable at 18.9% in the prior period and 19% in the current period, the total number of injured persons doubled from 8 to 16.

Severity is per crash event (most severe injury). 1 fatal crash events resulted in 2 persons killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes1.7%
Minor Injury9minor injury crashes15.5%
80.0%prior 5
Possible Injury2possible injury crashes3.4%
0.0%prior 2
No Injury46no injury crashes79.3%
53.3%prior 30

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

Several contributing factors saw significant increases in crash counts year-over-year. Crashes attributed to 'Inattention' rose from 5 to 12, a 140% increase in count, while 'Failed to yield right of way' crashes increased from 3 to 8, a 166.7% increase in count. 'Followed too closely' crashes also increased from 4 to 6, a 50% increase in count. 'No improper driving' remained constant at 9 crashes in both periods.

Officer-Reported Primary Contributing Cause

Inattention12 (20.7%)140.0%prior 5
No improper driving9 (15.5%)0.0%prior 9
Failed to yield right of way8 (13.8%)
Followed too closely6 (10.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (5.2%)
Fatigued/asleep2 (3.4%)
Exceeded authorized speed limit2 (3.4%)
Driving too fast for conditions2 (3.4%)
Visibility obstructed2 (3.4%)
Disregarded traffic signs, signals, road markings1 (1.7%)

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 33 in October 2021 to 46 in October 2022, while crashes in wet road surface conditions increased from 5 to 12. Daylight crashes rose from 21 to 37, and crashes in dark-lighted roadway conditions increased from 10 to 17. This indicates an overall increase in crashes across various weather, lighting, and road surface conditions.

Weather

Clear46 (79.3%)
39.4%prior 33
Cloudy4 (6.9%)
Rain4 (6.9%)
Clear/Other1 (1.7%)
Cloudy/Rain1 (1.7%)
Rain/Fog, smog, smoke1 (1.7%)
Clear/Unknown1 (1.7%)

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

Lighting

Daylight37 (63.8%)
76.2%prior 21
Dark - lighted roadway17 (29.3%)
70.0%prior 10
Dark - roadway not lighted4 (6.9%)
-20.0%prior 5

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

Road Surface

Dry46 (79.3%)
43.8%prior 32
Wet12 (20.7%)
140.0%prior 5

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 persons involved in crashes increased from 95 to 128 year-over-year. There was a notable increase in persons aged 35-44, rising from 13 to 23, and persons aged 45-54, increasing from 10 to 17. Among vehicle makes, Honda saw an increase in representation from 9 to 14, while Toyota increased from 13 to 14, and Ford from 11 to 12.

Top Vehicle Makes (110 vehicles)

1
HONDA14 (12.7%)
55.6%prior 9
2
TOYOTA14 (12.7%)
7.7%prior 13
3
FORD12 (10.9%)
9.1%prior 11
4
JEEP8 (7.3%)
14.3%prior 7
5
DODGE7 (6.4%)
6
VOLKSWAGEN7 (6.4%)
7
NISSAN6 (5.5%)
8
CHEVROLET6 (5.5%)
9
MAZDA4 (3.6%)
10
HYUNDAI4 (3.6%)

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

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

Sex Distribution (116 persons with recorded sex)

Male73 (62.9%)
37.7%prior 53
Female43 (37.1%)
13.2%prior 38

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 65 mph speed zones increased from 7 in October 2021 to 13 in October 2022, with the current period recording 1 fatal crash in this zone compared to none previously. Crashes in 40 mph zones increased from 7 to 12, and in 45 mph zones from 2 to 7. This indicates a shift towards more crashes occurring in higher speed limit areas.

Fatal crashes by zone: 65 mph: 1 of 13 (7.692%)

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: MANSFIELD, MA
  • Total crash records analyzed: 58
  • Total persons involved: 128
  • Total vehicles involved: 110

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). "MANSFIELD, 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/mansfield/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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Mansfield, MA Crash Report — October 2022 | ThatCarHitMe.com