Monthly Traffic Safety Analysis

11 CRASHES IN
SUTTON, MA
MARCH 2022

All metrics benchmarked againstMarch 2021

Total crashes in Sutton decreased by 42.1%, from 19 in March 2021 to 11 in March 2022. Despite this reduction in overall incidents, the number of fatalities increased from 0 to 2 over the same period. This indicates a significant shift towards more severe outcomes in the current month.

11

-42.1%was 19

Total Crash Events

2

Persons Killed

2

Persons Injured

0

-100.0%was 4

Hit-and-Run Crashes

Note: "Persons Killed" (2) 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.

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

The overall trend shows a substantial decrease in the total number of crashes, with incidents falling from 19 to 11 year-over-year, representing a 42.1% reduction. However, this period also saw a critical increase in fatalities, rising from 0 in March 2021 to 2 in March 2022.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

1

Motorists Killed

Prior: 0%

0

Pedestrians Injured

Prior: 00.0%

2

Motorists Injured

Prior: 20.0%

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 peak day for crashes shifted from Tuesday, with 6 incidents in March 2021, to Wednesday and Thursday, each with 4 incidents in March 2022. The peak hour for crashes remained 9 PM for both periods, though other hours also had similar counts.

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

The fatal crash rate increased significantly from 0% in March 2021 to 18.2% in March 2022, with 2 fatal crashes occurring. In March 2022, 9.1% of crashes resulted in possible injuries, compared to 5.3% for minor injuries and 5.3% for possible injuries in March 2021.

Outcome by Severity (Crash Events)

Fatal2fatal crashes18.2%
Possible Injury1possible injury crashes9.1%
0.0%prior 1
No Injury8no injury crashes72.7%
-46.7%prior 15

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 "No improper driving" decreased by 80% in count, from 5 in March 2021 to 1 in March 2022. "Operating vehicle in erratic, reckless, careless, negligent or aggressive manner" crashes also saw a 75% reduction in count, from 4 to 1. Factors such as "Inattention," "Physical impairment," and "Failure to keep in proper lane or running off road" maintained consistent crash counts of 1 or 2 across both periods.

Officer-Reported Primary Contributing Cause

Inattention2 (18.2%)
Other improper action2 (18.2%)
Glare1 (9.1%)
No improper driving1 (9.1%)-80.0%prior 5
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (9.1%)
Physical impairment1 (9.1%)
Failed to yield right of way1 (9.1%)
Failure to keep in proper lane or running off road1 (9.1%)

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

Weather conditions in March 2022 showed more diversity, with 4 crashes occurring in non-clear conditions (Cloudy, Cloudy/Rain, Rain, Snow), compared to 2 crashes in 'Clear/Other' conditions in March 2021, where 17 crashes occurred in clear weather. Crashes occurring during daylight hours decreased from 11 in March 2021 to 7 in March 2022, while crashes in 'Dark - lighted roadway' increased from 1 to 4.

Weather

Clear7 (63.6%)
-58.8%prior 17
Cloudy1 (9.1%)
Cloudy/Rain1 (9.1%)
Rain1 (9.1%)
Snow1 (9.1%)

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

Lighting

Daylight7 (63.6%)
-36.4%prior 11
Dark - lighted roadway4 (36.4%)

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

Road Surface

Dry7 (63.6%)
Wet2 (18.2%)
Ice1 (9.1%)
Snow1 (9.1%)

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 (21 vehicles)

1
TOYOTA5 (23.8%)
2
HONDA3 (14.3%)
3
MERCEDES-BENZ3 (14.3%)
4
GMC2 (9.5%)
5
FORD2 (9.5%)
6
CHEVROLET2 (9.5%)
7
SUBARU1 (4.8%)
8
CADI1 (4.8%)
9
AUDI1 (4.8%)
10
NISSAN1 (4.8%)

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

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

Sex Distribution (25 persons with recorded sex)

Male16 (64.0%)
-15.8%prior 19
Female9 (36.0%)
-43.8%prior 16

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

In March 2022, there were 2 fatal crashes, occurring in 25 mph and 35 mph speed limit zones, whereas no fatal crashes were recorded across any speed limits in March 2021. Crashes in 30 mph zones, which accounted for 7 incidents in March 2021, were not present in March 2022. Conversely, crashes at 55 mph increased from 2 in March 2021 to 4 in March 2022.

Fatal crashes by zone: 25 mph: 1 of 1 (100%) · 35 mph: 1 of 2 (50%)

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: SUTTON, MA
  • Total crash records analyzed: 11
  • Total persons involved: 28
  • Total vehicles involved: 21

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). "SUTTON, 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/sutton/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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Sutton, MA Crash Report — March 2022 | ThatCarHitMe.com