ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · MANSFIELD, MA · 2022
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/massachusetts/mansfield/2022-annual-report
Yearly Traffic Safety Analysis
492 CRASHES IN
MANSFIELD, MA
2022
In 2022, Mansfield recorded 492 total crashes, an increase of 12.1% from the 439 crashes documented in 2021. While total fatalities remained unchanged at 3 for both years, the number of people injured rose from 146 to 171. The most significant year-over-year change was in hit-and-run incidents, which tripled from 4 in 2021 to 12 in 2022.
492
▲ 12.1%was 439
Total Crash Events
3
Persons Killed
171
▲ 17.1%was 146
Persons Injured
12
▲ 200.0%was 4
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in traffic incidents in Mansfield shows an increase year-over-year. Total crashes rose by 12.1%, from 439 incidents in 2021 to 492 in 2022. Correspondingly, the number of people injured in these crashes increased by 17.1% to 171, while the number of fatalities remained constant at 3.
12
Hit-and-Run Crashes — 2022
▲ 200.0% vs prior (4)
The number of hit-and-run crashes in Mansfield demonstrated a significant upward trend. In 2022, there were 12 reported hit-and-run incidents, a 200% increase from the 4 incidents recorded in 2021. Consequently, the hit-and-run rate, as a proportion of all crashes, more than doubled from 0.9% in 2021 to 2.4% in 2022.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
3
Motorists Killed
0
Other Killed
3
Pedestrians Injured
3
Cyclists Injured
164
Motorists Injured
1
Other Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
Temporal analysis shows that crash patterns remained broadly consistent, though the peak day for crashes shifted from Thursday (77 crashes) in 2021 to Wednesday (80 crashes) in 2022. The peak hour for crashes was unchanged at 4 p.m. in both periods, but the number of incidents during this hour increased from 40 in 2021 to 51 in 2022.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity distribution of crashes saw minor shifts between 2021 and 2022. The number of fatal crashes decreased from 3 to 2, causing the fatal crash rate to fall from 0.7% to 0.4% of all incidents. While the absolute count of crashes involving an injury increased from 112 to 123, their proportion relative to all crashes remained stable, accounting for 25.5% in 2021 and 25.0% in 2022.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record
Top Contributing Factors
The ranking of top contributing factors shifted between 2021 and 2022, with 'Inattention' becoming the leading factor. The count of crashes attributed to inattention increased by 49.2% from 65 to 97 incidents, overtaking 'No improper driving,' which was the top factor in 2021. The count of crashes due to 'Followed too closely' rose by 20.7% (from 58 to 70), and 'Failed to yield right of way' increased by 27.7% (from 47 to 60).
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes in 2022 were more likely to occur in favorable conditions compared to the prior year. The proportion of crashes happening in clear weather increased from 72.0% in 2021 to 79.7% in 2022, while the share of crashes on dry road surfaces rose from 79.3% to 81.7%. Lighting conditions for crashes remained relatively stable, with approximately two-thirds of incidents in both years occurring during daylight hours.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field
Vehicles & Demographics
The top three vehicle makes involved in crashes—Toyota, Honda, and Ford—remained the same across both years, with minor changes in their rankings. In 2022, Honda (108 vehicles) surpassed Ford (107 vehicles) for the second most common make, while Toyota remained first. Analysis of persons involved shows a shift in demographics, with the 35-44 age group becoming the most represented in 2022, and a 43.8% increase in the number of individuals aged 65 and older involved in crashes (from 80 to 115).
Top Vehicle Makes (915 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
46 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,099 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Person-level records linked to crash events
Speed Limit Zones
The distribution of crashes across speed zones changed in 2022, with a notable increase in incidents in 30 mph zones, which rose by 30.2% from 139 to 181 crashes. In 2022, both of the year's fatal crashes occurred in 65 mph speed zones. This compares to 2021, when fatal crashes were recorded in both 65 mph (2 crashes) and 45 mph (1 crash) zones.
Fatal crashes by zone: 65 mph: 2 of 129 (1.55%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2022-01-01 through 2022-12-31 (365 days)
- Geographic scope: MANSFIELD, MA
- Total crash records analyzed: 492
- Total persons involved: 1,182
- Total vehicles involved: 915
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: 2022." Published June 21, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/mansfield/2022-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2022-01-01 – 2022-12-31
Generated: June 21, 2026 · All rights reserved