Yearly Traffic Safety Analysis

475 CRASHES IN
MANSFIELD, MA
2023

All metrics benchmarked against2022

In 2023, Mansfield recorded 475 total traffic crashes, a 3.5% decrease from the 492 crashes reported in 2022. While total crashes and the number of people injured declined, the number of fatal crashes increased from 2 in 2022 to 3 in 2023, and serious injury crashes rose from 8 to 11. The total number of fatalities remained constant at 3 for both years.

475

-3.5%was 492

Total Crash Events

3

Persons Killed

148

-13.5%was 171

Persons Injured

15

25.0%was 12

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 3 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic collisions in Mansfield saw a slight decline in 2023 compared to the previous year. The total number of crashes decreased by 3.5%, from 492 in 2022 to 475 in 2023. This downward trend was also reflected in total injuries, which fell by 13.5% from 171 to 148, although the number of fatalities remained unchanged at 3.

15

Hit-and-Run Crashes — 2023

25.0% vs prior (12)

Hit-and-run incidents in Mansfield trended upward in 2023 compared to the previous year. The total number of hit-and-run crashes increased by 25%, from 12 in 2022 to 15 in 2023. This rise is also reflected in the hit-and-run rate, which climbed from 2.4% of all crashes in 2022 to 3.2% in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

3

Motorists Killed

Prior: 30.0%

4

Pedestrians Injured

Prior: 333.3%

4

Cyclists Injured

Prior: 333.3%

140

Motorists Injured

Prior: 164-14.6%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year, with Wednesday being the peak day for collisions in both 2023 (79 crashes) and 2022 (80 crashes). However, the peak hour for crashes shifted earlier in the day. In 2023, the most crashes occurred at 2 p.m. with 45 incidents, whereas in 2022, the peak was later at 4 p.m. with 51 incidents.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes decreased, the severity of incidents increased in 2023. The number of fatal crashes rose from 2 to 3, and the corresponding fatal crash rate increased from 0.41% to 0.63%. Similarly, serious injury crashes increased in both count (from 8 to 11) and as a percentage of all crashes (from 1.6% to 2.3%). Conversely, crashes resulting in minor or possible injuries saw a combined decrease from 115 incidents in 2022 to 100 in 2023.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
50.0%prior 2
Serious Injury11serious injury crashes2.3%
37.5%prior 8
Minor Injury66minor injury crashes13.9%
-10.8%prior 74
Possible Injury34possible injury crashes7.2%
-17.1%prior 41
No Injury358no injury crashes75.4%
-1.6%prior 364

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

The ranking of top contributing factors shifted between 2022 and 2023. "Inattention" was the leading factor in 2022 with 97 crashes, but its count fell by 15.5% to 82 crashes in 2023, making it the second most common factor. The "No improper driving" category saw its count rise by 25.4% from 71 to 89, becoming the most frequently cited factor in 2023. The count for crashes involving "Followed too closely" remained stable at 70 and 71, respectively.

Officer-Reported Primary Contributing Cause

No improper driving89 (18.7%)25.4%prior 71
Inattention82 (17.3%)-15.5%prior 97
Followed too closely71 (14.9%)1.4%prior 70
Failed to yield right of way67 (14.1%)11.7%prior 60
Driving too fast for conditions17 (3.6%)6.3%prior 16
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner17 (3.6%)30.8%prior 13
Failure to keep in proper lane or running off road15 (3.2%)-16.7%prior 18
Other improper action13 (2.7%)-7.1%prior 14
Distracted12 (2.5%)-33.3%prior 18
Disregarded traffic signs, signals, road markings8 (1.7%)-42.9%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

In 2023, a larger proportion of crashes occurred during adverse road and weather conditions compared to 2022. The number of crashes on wet road surfaces increased from 58 to 86, representing a shift in share from 11.8% to 18.1% of all crashes. Correspondingly, crashes during rain increased from 24 to 39 incidents. The distribution of crashes by lighting conditions remained relatively stable, with about two-thirds of incidents in both years occurring during daylight.

Weather

Clear338 (71.2%)
-13.8%prior 392
Cloudy61 (12.8%)
64.9%prior 37
Rain39 (8.2%)
62.5%prior 24
Cloudy/Rain13 (2.7%)
160.0%prior 5
Snow9 (1.9%)
-25.0%prior 12
Rain/Severe crosswinds3 (0.6%)
Fog, smog, smoke3 (0.6%)
Rain/Cloudy3 (0.6%)
Sleet, hail (freezing rain or drizzle)2 (0.4%)
Clear/Cloudy2 (0.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight313 (65.9%)
-2.5%prior 321
Dark - lighted roadway83 (17.5%)
-6.7%prior 89
Dark - roadway not lighted52 (10.9%)
10.6%prior 47
Dusk16 (3.4%)
14.3%prior 14
Dawn8 (1.7%)
-27.3%prior 11
Dark - unknown roadway lighting3 (0.6%)
-66.7%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry377 (79.4%)
-6.2%prior 402
Wet86 (18.1%)
48.3%prior 58
Ice5 (1.1%)
-54.5%prior 11
Snow5 (1.1%)
-73.7%prior 19
Sand, mud, dirt, oil, gravel1 (0.2%)
Slush1 (0.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained consistent between 2022 and 2023, with only minor fluctuations in their counts. A more notable change occurred in the age demographics of people involved in crashes. The number of individuals in the 16-20 age group dropped from 170 to 123, while involvement for the 26-34 age group increased from 179 to 209. Similarly, the 55-64 age group saw an increase in involvement from 121 to 134 persons.

Top Vehicle Makes (892 vehicles)

1
TOYOTA142 (15.9%)
6.0%prior 134
2
HONDA99 (11.1%)
-8.3%prior 108
3
FORD94 (10.5%)
-12.1%prior 107
4
NISSAN62 (7%)
24.0%prior 50
5
CHEVROLET59 (6.6%)
13.5%prior 52
6
JEEP52 (5.8%)
0.0%prior 52
7
HYUNDAI41 (4.6%)
-6.8%prior 44
8
KIA30 (3.4%)
36.4%prior 22
9
SUBARU30 (3.4%)
11.1%prior 27
10
GMC29 (3.3%)
3.6%prior 28

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (1,004 persons with recorded sex)

Male572 (57.0%)
-10.2%prior 637
Female432 (43.0%)
-6.3%prior 461

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones saw some shifts between 2022 and 2023. Crashes in 65 mph zones remained stable at 131, accounting for 2 fatal crashes in both years. In contrast, incidents in 30 mph zones decreased from 181 to 158; however, a fatal crash was recorded in a 30 mph zone in 2023, where none had occurred in 2022. Crashes in 40 mph zones increased from 63 to 72.

Fatal crashes by zone: 30 mph: 1 of 158 (0.633%) · 65 mph: 2 of 131 (1.527%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: MANSFIELD, MA
  • Total crash records analyzed: 475
  • Total persons involved: 1,085
  • Total vehicles involved: 892

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: 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mansfield/2023-annual-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 — 2023 | ThatCarHitMe.com