Monthly Traffic Safety Analysis

48 CRASHES IN
MANSFIELD, MA
SEPTEMBER 2023

All metrics benchmarked againstSeptember 2022

In September 2023, MANSFIELD experienced 48 crashes, a 60% increase compared to the 30 crashes recorded in September 2022. While total crashes rose significantly, total injuries decreased from 20 to 12 over the same period. The number of DUI crashes notably increased from 0 in the prior year to 2 in the current period.

48

60.0%was 30

Total Crash Events

0

Persons Killed

12

-40.0%was 20

Persons Injured

2

100.0%was 1

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in total crashes year-over-year, rising from 30 in September 2022 to 48 in September 2023, representing a 60% increase. Despite this rise in crash incidents, the total number of injuries decreased by 40%, from 20 to 12.

2

Hit-and-Run Crashes — September 2023

100.0% vs prior (1)

The number of hit-and-run crashes increased from 1 in September 2022 to 2 in September 2023, a 100% increase. Concurrently, the hit-and-run rate rose from 3.3% of total crashes in the prior period to 4.2% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 0%

11

Motorists Injured

Prior: 19-42.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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 Thursday with 8 crashes in September 2022 to Tuesday with 10 crashes in September 2023. Similarly, the peak hour for crashes changed from 4 PM with 7 crashes in the prior period to 8 AM with 5 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

There were no fatalities reported in either September 2022 or September 2023. Serious injuries remained constant at 1 crash in both periods. However, minor injuries decreased from 8 in the prior period to 6 in the current period, and the overall injury rate declined from 66.7% to 25% of total crashes.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2.1%
0.0%prior 1
Minor Injury6minor injury crashes12.5%
-25.0%prior 8
Possible Injury4possible injury crashes8.3%
0.0%prior 4
No Injury37no injury crashes77.1%
117.6%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Most severe injury per crash record

Top Contributing Factors

Among contributing factors, 'No improper driving' saw a significant increase in count from 3 to 8 crashes, a 166.7% change. 'Followed too closely' increased from 6 to 9 crashes, a 50% increase in count. 'Failed to yield right of way' also rose from 5 to 7 crashes, a 40% increase in count.

Officer-Reported Primary Contributing Cause

Followed too closely9 (18.8%)50.0%prior 6
No improper driving8 (16.7%)
Failed to yield right of way7 (14.6%)40.0%prior 5
Inattention6 (12.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner3 (6.3%)
Driving too fast for conditions2 (4.2%)
Exceeded authorized speed limit1 (2.1%)
Distracted1 (2.1%)
Other improper action1 (2.1%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring on wet road surfaces increased from 5 in September 2022 to 10 in September 2023, a 100% increase. Incidents during rain or cloudy weather conditions rose from 4 to 10 crashes, a 150% increase. Crashes in dark conditions (roadway lighted or not lighted) increased from 9 to 15, a 66.7% increase.

Weather

Clear30 (62.5%)
25.0%prior 24
Cloudy6 (12.5%)
Rain5 (10.4%)
Cloudy/Rain4 (8.3%)
Fog, smog, smoke2 (4.2%)
Rain/Cloudy1 (2.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Weather condition at time of crash

Lighting

Daylight31 (64.6%)
55.0%prior 20
Dark - roadway not lighted8 (16.7%)
Dark - lighted roadway7 (14.6%)
Dusk2 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Lighting condition field

Road Surface

Dry38 (79.2%)
52.0%prior 25
Wet10 (20.8%)
100.0%prior 5

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 56 in September 2022 to 91 in September 2023, a 62.5% increase. Toyota vehicles involved in crashes increased from 8 to 14, while Hyundai vehicles decreased from 8 to 4. Chevrolet and Nissan vehicles each saw a 200% increase in involvement, rising from 3 to 9.

Top Vehicle Makes (91 vehicles)

1
TOYOTA14 (15.4%)
75.0%prior 8
2
CHEVROLET9 (9.9%)
3
NISSAN9 (9.9%)
4
FORD9 (9.9%)
50.0%prior 6
5
HONDA8 (8.8%)
0.0%prior 8
6
JEEP5 (5.5%)
7
VOLKSWAGEN4 (4.4%)
8
GMC4 (4.4%)
9
HYUNDAI4 (4.4%)
-50.0%prior 8
10
KIA4 (4.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Vehicle unit records

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

Sex Distribution (93 persons with recorded sex)

Male57 (61.3%)
23.9%prior 46
Female36 (38.7%)
38.5%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 65 mph speed zones increased from 11 to 17, a 54.5% increase, while crashes in 30 mph zones decreased from 12 to 8. Notably, crashes in 40 mph zones saw a 900% increase, rising from 1 to 10. Crashes in 20 mph zones (3) and 50 mph zones (1) were reported in the current period but not the prior.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-09-01 to 2023-09-30 · 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: 2023-09-01 through 2023-09-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-09-01 through 2023-09-30 (30 days)
  • Geographic scope: MANSFIELD, MA
  • Total crash records analyzed: 48
  • Total persons involved: 104
  • Total vehicles involved: 91

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: September 2023." Published June 21, 2026. Reporting period: 2023-09-01 to 2023-09-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mansfield/september-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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Mansfield, MA Crash Report — September 2023 | ThatCarHitMe.com