Monthly Traffic Safety Analysis

29 CRASHES IN
FOXBOROUGH, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

Total crashes in FOXBOROUGH, MA increased by 16% from 25 in March 2021 to 29 in March 2022. The most notable year-over-year shift was the increase in total fatalities from 0 in March 2021 to 1 in March 2022.

29

16.0%was 25

Total Crash Events

1

Persons Killed

13

44.4%was 9

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities. 2 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in FOXBOROUGH, MA saw an upward trend year-over-year, with total crashes increasing by 16% from 25 to 29. This period also marked a significant increase in crash severity, with total fatalities rising from 0 to 1 and total injuries increasing by 44.4% from 9 to 13.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

1

Cyclists Injured

Prior: 0%

12

Motorists Injured

Prior: 933.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns for crashes remained consistent year-over-year, with both March 2021 and March 2022 identifying Thursday as the peak day for crashes, increasing from 7 to 9 incidents. Similarly, 4 PM remained the peak hour for crashes in both periods, with counts rising from 5 to 6.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity increased significantly year-over-year, with total fatalities rising from 0 in March 2021 to 1 in March 2022. The number of minor injuries (severity B) increased from 1 to 6, while possible injuries (severity C) decreased from 5 to 3. Additionally, March 2021 recorded 2 serious injuries (severity A) which were not present in March 2022 data.

Outcome by Severity (Crash Events)

Fatal1fatal crashes3.4%
Minor Injury6minor injury crashes20.7%
500.0%prior 1
Possible Injury3possible injury crashes10.3%
-40.0%prior 5
No Injury17no injury crashes58.6%
0.0%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Followed too closely" increased by 1 (16.7%) from 6 in March 2021 to 7 in March 2022, maintaining a similar share of total crashes at approximately 24%. "Inattention" crashes decreased by 3 (37.5%) from 8 to 5, resulting in its share of crashes falling from 32% to 17.2%. Crashes attributed to "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" saw a substantial increase of 3 (300%) from 1 to 4.

Officer-Reported Primary Contributing Cause

Followed too closely7 (24.1%)16.7%prior 6
Inattention5 (17.2%)-37.5%prior 8
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner4 (13.8%)
No improper driving4 (13.8%)
Failed to yield right of way1 (3.4%)
Operating defective equipment1 (3.4%)
Distracted1 (3.4%)
Other improper action1 (3.4%)
Visibility obstructed1 (3.4%)
Disregarded traffic signs, signals, road markings1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Clear weather remained the predominant condition for crashes in both periods, with 19 crashes in March 2022 compared to 18 in March 2021. While Daylight was the leading lighting condition for crashes in both years, crashes occurring in "Dark - lighted roadway" conditions increased from 3 in March 2021 to 7 in March 2022. Dry road surfaces were consistently associated with the majority of crashes, accounting for 23 incidents in March 2022 and 22 in March 2021.

Weather

Clear19 (70.4%)
5.6%prior 18
Cloudy3 (11.1%)
Snow2 (7.4%)
Rain1 (3.7%)
Cloudy/Rain1 (3.7%)
Fog, smog, smoke1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Weather condition at time of crash

Lighting

Daylight16 (55.2%)
-15.8%prior 19
Dark - lighted roadway7 (24.1%)
Dark - roadway not lighted5 (17.2%)
Dawn1 (3.4%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Lighting condition field

Road Surface

Dry23 (82.1%)
4.5%prior 22
Wet4 (14.3%)
Slush1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (60 vehicles)

1
TOYOTA11 (18.3%)
-8.3%prior 12
2
CHEVROLET9 (15%)
3
HONDA7 (11.7%)
4
FORD7 (11.7%)
5
NISSAN3 (5%)
6
GMC2 (3.3%)
7
JEEP2 (3.3%)
8
SUBARU2 (3.3%)
9
HYUNDAI2 (3.3%)
10
MAZDA2 (3.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Vehicle unit records

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

Sex Distribution (62 persons with recorded sex)

Male50 (80.6%)
78.6%prior 28
Female12 (19.4%)
-55.6%prior 27

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 65 MPH speed limit zone increased from 6 in March 2021 to 12 in March 2022, and this zone recorded the only fatal crash in March 2022. The 35 MPH zone also saw an increase in crashes, rising from 2 to 7 year-over-year. Conversely, crashes in the 30 MPH zone slightly decreased from 3 to 2.

Fatal crashes by zone: 65 mph: 1 of 12 (8.333%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-03-01 to 2022-03-31 · 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: 2022-03-01 through 2022-03-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-03-01 through 2022-03-31 (31 days)
  • Geographic scope: FOXBOROUGH, MA
  • Total crash records analyzed: 29
  • Total persons involved: 66
  • Total vehicles involved: 60

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: March 2022." Published June 21, 2026. Reporting period: 2022-03-01 to 2022-03-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/foxborough/march-2022-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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Foxborough, MA Crash Report — March 2022 | ThatCarHitMe.com