Monthly Traffic Safety Analysis

17 CRASHES IN
SUTTON, MA
MAY 2022

All metrics benchmarked againstMay 2021

Total crashes in Sutton increased significantly from 8 in May 2021 to 17 in May 2022, representing a 112.5% rise year-over-year. Concurrently, total injuries rose by 75%, from 4 to 7. A notable positive shift was the absence of fatalities in May 2022, compared to 1 fatality recorded in May 2021.

17

112.5%was 8

Total Crash Events

0

-100.0%was 1

Persons Killed

7

75.0%was 4

Persons Injured

1

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 · 2022-05-01 to 2022-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in crash incidents, with total crashes rising from 8 in May 2021 to 17 in May 2022, marking a 112.5% increase. Total injuries also saw an upward trend, increasing from 4 to 7, a 75% rise. Despite the increase in crashes and injuries, the number of fatalities decreased from 1 to 0.

1

Hit-and-Run Crashes — May 2022

5.9% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

7

Motorists Injured

Prior: 475.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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 Saturday with 3 incidents in May 2021 to Monday with 5 incidents in May 2022. Similarly, the peak crash hour moved from 7 PM with 1 incident in May 2021 to 11 PM with 2 incidents in May 2022. The distribution of crashes across days and hours appears more varied in May 2022 compared to the prior year.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1, accounting for 12.5% of crashes in May 2021, to 0 in May 2022. The proportion of crashes resulting in any injury (Fatal, Minor, or Possible) decreased from 62.5% (5 out of 8 crashes) in May 2021 to 35.3% (6 out of 17 crashes) in May 2022. Minor injury crashes increased from 4 to 5, while possible injury crashes appeared with 1 incident in May 2022.

Outcome by Severity (Crash Events)

Minor Injury5minor injury crashes29.4%
25.0%prior 4
Possible Injury1possible injury crashes5.9%
No Injury11no injury crashes64.7%
450.0%prior 2

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Most severe injury per crash record

Top Contributing Factors

The factor 'No improper driving' saw a significant increase, from 2 crashes in May 2021 to 7 crashes in May 2022. 'Failed to yield right of way' also increased from 1 crash to 2 crashes year-over-year. Factors such as 'Failure to keep in proper lane or running off road' (2 crashes) and 'Other improper action' (1 crash) were top contributing factors in May 2021 but were not among the top factors in May 2022.

Officer-Reported Primary Contributing Cause

No improper driving7 (41.2%)
Failed to yield right of way2 (11.8%)
Inattention1 (5.9%)
Fatigued/asleep1 (5.9%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5.9%)
Physical impairment1 (5.9%)
Visibility obstructed1 (5.9%)
Followed too closely1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in clear weather conditions increased from 62.5% (5 out of 8 crashes) in May 2021 to 94.1% (16 out of 17 crashes) in May 2022. Crashes on dry road surfaces also increased proportionally from 75% (6 out of 8 crashes) to 88.2% (15 out of 17 crashes). While daylight crashes increased in count from 6 to 11, their proportion decreased from 75% to 64.7%, and crashes in dark conditions saw an increase in both count (from 1 to 6) and proportion (from 12.5% to 35.3%).

Weather

Clear16 (94.1%)
220.0%prior 5
Rain/Cloudy1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Weather condition at time of crash

Lighting

Daylight11 (64.7%)
83.3%prior 6
Dark - roadway not lighted4 (23.5%)
Dark - lighted roadway2 (11.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Lighting condition field

Road Surface

Dry15 (88.2%)
150.0%prior 6
Sand, mud, dirt, oil, gravel1 (5.9%)
Wet1 (5.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (26 vehicles)

1
TOYOTA7 (26.9%)
2
ACURA2 (7.7%)
3
GMC2 (7.7%)
4
LEXUS2 (7.7%)
5
SUBARU1 (3.8%)
6
HONDA1 (3.8%)
7
INFINITI1 (3.8%)
8
JEEP1 (3.8%)
9
CHEVROLET1 (3.8%)
10
MACK1 (3.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Vehicle unit records

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

Sex Distribution (29 persons with recorded sex)

Female16 (55.2%)
128.6%prior 7
Male13 (44.8%)
85.7%prior 7

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph zone increased from 1 to 3, and in the 65 mph zone from 2 to 5 year-over-year. Conversely, crashes in the 35 mph zone decreased from 3 to 1, and the 40 mph zone decreased from 2 to 1. Notably, the 35 mph zone had 1 fatal crash in May 2021, but no fatal crashes were recorded in any speed zone in May 2022.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2022-05-01 to 2022-05-31 · 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: 2022-05-01 through 2022-05-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2022-05-01 through 2022-05-31 (31 days)
  • Geographic scope: SUTTON, MA
  • Total crash records analyzed: 17
  • Total persons involved: 33
  • Total vehicles involved: 26

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: May 2022." Published June 21, 2026. Reporting period: 2022-05-01 to 2022-05-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sutton/may-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 — May 2022 | ThatCarHitMe.com