ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · FOXBOROUGH, 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/foxborough/2022-annual-report
Yearly Traffic Safety Analysis
508 CRASHES IN
FOXBOROUGH, MA
2022
In 2022, Foxborough recorded 508 total crashes, a 5.4% increase from the 482 crashes reported in 2021. The most significant change was the emergence of traffic fatalities, with 5 deaths occurring in 2022 compared to zero in the previous year. Total injuries also rose from 149 to 186 during the same period.
508
▲ 5.4%was 482
Total Crash Events
5
Persons Killed
186
▲ 24.8%was 149
Persons Injured
20
▲ 25.0%was 16
Hit-and-Run Crashes
Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 7 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 crashes is upward year-over-year. Total collisions increased by 5.4%, rising from 482 in 2021 to 508 in 2022. This increase was accompanied by a more substantial rise in persons injured, which grew by 24.8% from 149 to 186, and a shift from zero traffic fatalities in 2021 to five in 2022.
20
Hit-and-Run Crashes — 2022
▲ 25.0% vs prior (16)
Hit-and-run incidents increased in both count and rate from 2021 to 2022. The number of hit-and-run crashes rose from 16 to 20, representing a 25% increase in count. Consequently, the hit-and-run rate as a percentage of total crashes also trended upward, climbing from 3.3% in 2021 to 3.9% in 2022.
Vulnerable Road User Casualties
1
Pedestrians Killed
0
Cyclists Killed
4
Motorists Killed
0
Other Killed
1
Pedestrians Injured
2
Cyclists Injured
177
Motorists Injured
6
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
The timing of crashes showed some shifts between the two periods. In 2022, the peak day for crashes moved to Friday with 95 incidents, compared to Thursday in 2021 which had 94 incidents. The peak hour for collisions shifted an hour earlier to 4 p.m. in 2022, which saw 58 crashes, up from the 2021 peak of 46 crashes at 5 p.m.
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
Crash severity worsened significantly in 2022, with 5 fatal incidents recorded, accounting for 1% of all crashes, compared to zero fatal crashes in 2021. While the number of serious injury crashes decreased from 9 to 4, minor injury crashes increased from 60 to 75. The proportion of crashes resulting in no injury remained unchanged at 73% in both years.
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 leading contributing factors remained consistent, with 'Inattention' and 'No improper driving' ranking first and second in both years, though their counts decreased from 96 to 87 and 94 to 82, respectively. Crashes attributed to 'Followed too closely' increased by 19% in count, from 58 in 2021 to 69 in 2022. Notably, incidents involving 'Failed to yield right of way' rose by 46% from 39 to 57, and crashes linked to distraction more than doubled in count from 7 to 19.
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
Crash conditions remained broadly similar year-over-year, with the majority of incidents in both periods occurring in clear weather and during daylight hours. In 2022, 400 crashes happened on dry roads, an increase from 367 in 2021. Conversely, crashes on wet roads saw a decrease, falling from 95 incidents in 2021 to 81 in 2022.
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 remained Toyota, Ford, and Honda in both years, with Honda's involvement increasing from 89 vehicles in 2021 to 110 in 2022. Demographically, the 26-34 age group continued to be the most represented group of persons involved in crashes, with their count rising from 198 to 219. The 21-25 age group also saw a notable increase in involvement, growing from 121 persons in 2021 to 162 in 2022.
Top Vehicle Makes (970 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records
56 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (1,120 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
Crashes in higher speed zones saw an increase in 2022, with incidents in 65 mph zones rising from 141 to 164. Similarly, crashes in 35 mph zones grew from 66 to 80. In 2022, all 5 fatalities occurred in zones with speed limits of 35 mph or higher, including 3 deaths in the 65 mph zone, whereas 2021 recorded no fatal crashes in any speed zone.
Fatal crashes by zone: 35 mph: 1 of 80 (1.25%) · 45 mph: 1 of 31 (3.226%) · 65 mph: 3 of 164 (1.829%)
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: FOXBOROUGH, MA
- Total crash records analyzed: 508
- Total persons involved: 1,218
- Total vehicles involved: 970
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). "FOXBOROUGH, 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/foxborough/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