Monthly Traffic Safety Analysis

37 CRASHES IN
MANSFIELD, MA
APRIL 2024

All metrics benchmarked againstApril 2023

Total crashes in MANSFIELD, MA increased slightly from 36 in April 2023 to 37 in April 2024, representing a 2.8% rise. Despite this minor increase in crash events, there was a significant decrease in severity, with total fatalities dropping from 2 to 0 and total injuries decreasing by 40% from 15 to 9. This suggests an overall improvement in crash outcomes year-over-year.

37

2.8%was 36

Total Crash Events

0

-100.0%was 2

Persons Killed

9

-40.0%was 15

Persons Injured

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 · 2024-04-01 to 2024-04-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a slight increase in total crash events, rising by 2.8% from 36 crashes in April 2023 to 37 crashes in April 2024. However, crash severity significantly decreased, with total fatalities dropping from 2 to 0 and total injuries decreasing from 15 to 9. This indicates that while crash frequency was stable, the impact on human harm was reduced.

1

Hit-and-Run Crashes — April 2024

0.0% vs prior (1)

The number of hit-and-run crashes remained consistent at 1 for both April 2023 and April 2024. The hit-and-run crash rate saw a marginal decrease, from 2.8% in the prior period to 2.7% in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 2-100.0%

1

Cyclists Injured

Prior: 10.0%

8

Motorists Injured

Prior: 14-42.9%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns shifted, with the peak day for crashes moving from Thursday (8 crashes) in April 2023 to Tuesday (11 crashes) in April 2024. The peak hour also changed from 3 PM (4 crashes) in the prior period to 2 PM (7 crashes) in the current period. Notably, crashes on Saturday decreased from 6 in the prior period to 0 in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities decreased from 2 in April 2023 to 0 in April 2024, resulting in a 100% reduction in fatal crashes. Total injuries also decreased by 40%, from 15 to 9. The proportion of crashes resulting in serious injury increased from 2.8% to 5.4%, while minor injuries decreased from 16.7% to 10.8%.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes5.4%
100.0%prior 1
Minor Injury4minor injury crashes10.8%
-33.3%prior 6
Possible Injury1possible injury crashes2.7%
-75.0%prior 4
No Injury30no injury crashes81.1%
30.4%prior 23

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Most severe injury per crash record

Top Contributing Factors

The contributing factor 'Followed too closely' saw a significant increase, rising from 4 crashes in April 2023 to 9 crashes in April 2024, becoming the top factor in the current period. Conversely, 'No improper driving' decreased from 9 crashes to 5 crashes year-over-year. 'Failed to yield right of way' crashes doubled from 3 to 6, while 'Inattention' crashes decreased from 5 to 3.

Officer-Reported Primary Contributing Cause

Followed too closely9 (24.3%)
Failed to yield right of way6 (16.2%)
No improper driving5 (13.5%)-44.4%prior 9
Failure to keep in proper lane or running off road4 (10.8%)
Inattention3 (8.1%)-40.0%prior 5
Distracted3 (8.1%)
Disregarded traffic signs, signals, road markings2 (5.4%)
Made an improper turn2 (5.4%)
Driving too fast for conditions1 (2.7%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The number of crashes occurring in clear weather remained constant at 24 for both April 2023 and April 2024. Crashes in rainy conditions decreased slightly from 4 in the prior period to 3 in the current period. Crashes on dry road surfaces increased from 29 to 31, while those on wet road surfaces decreased from 7 to 6.

Weather

Clear24 (64.9%)
0.0%prior 24
Cloudy7 (18.9%)
0.0%prior 7
Rain3 (8.1%)
Cloudy/Rain2 (5.4%)
Rain/Cloudy1 (2.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Weather condition at time of crash

Lighting

Daylight31 (83.8%)
19.2%prior 26
Dark - lighted roadway4 (10.8%)
Dark - roadway not lighted2 (5.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Lighting condition field

Road Surface

Dry31 (83.8%)
6.9%prior 29
Wet6 (16.2%)
-14.3%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Road surface condition field

Vehicles & Demographics

The age group 16-20 saw a decrease in involved persons, from 11 in April 2023 to 7 in April 2024. Conversely, the 26-34 age group experienced an increase in involved persons, from 8 to 14. Toyota vehicles involved decreased from 15 to 10, while Honda vehicles involved increased from 4 to 10, shifting their respective rankings among top makes.

Top Vehicle Makes (72 vehicles)

1
HONDA10 (13.9%)
2
TOYOTA10 (13.9%)
-33.3%prior 15
3
CHEVROLET7 (9.7%)
4
FORD7 (9.7%)
16.7%prior 6
5
MAZDA5 (6.9%)
6
NISSAN5 (6.9%)
0.0%prior 5
7
JEEP3 (4.2%)
8
RAM3 (4.2%)
9
SUBARU3 (4.2%)
10
HYUNDAI2 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Vehicle unit records

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

Sex Distribution (77 persons with recorded sex)

Male40 (51.9%)
-9.1%prior 44
Female37 (48.1%)
23.3%prior 30

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased from 16 in April 2023 to 8 in April 2024. Conversely, crashes in the 65 mph speed zone increased from 9 to 11. While fatal crashes were recorded in the 30 mph and 65 mph zones in the prior period, no fatal crashes occurred in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2024-04-01 to 2024-04-30 · 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: 2024-04-01 through 2024-04-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2024-04-01 through 2024-04-30 (30 days)
  • Geographic scope: MANSFIELD, MA
  • Total crash records analyzed: 37
  • Total persons involved: 83
  • Total vehicles involved: 72

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: April 2024." Published June 21, 2026. Reporting period: 2024-04-01 to 2024-04-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mansfield/april-2024-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 — April 2024 | ThatCarHitMe.com