Monthly Traffic Safety Analysis

16 CRASHES IN
SUTTON, MA
OCTOBER 2023

All metrics benchmarked againstOctober 2022

In Sutton, total crashes remained stable at 16 for October 2023 compared to October 2022. Total injuries increased by 16.7%, rising from 6 to 7. A notable shift was the 100% decrease in speeding-related crashes, which went from 1 in the prior period to 0 in the current period.

16

Total Crash Events

0

Persons Killed

7

16.7%was 6

Persons Injured

0

Fatal Crash Events

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 · 2023-10-01 to 2023-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend for crashes in Sutton remained stable year-over-year, with 16 total crashes reported in both October 2022 and October 2023. While total crashes were unchanged, injuries saw an increase of 16.7%, rising from 6 injured persons in the prior period to 7 in the current period. Fatalities remained at zero in both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

7

Motorists Injured

Prior: 616.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal distribution of crashes shifted year-over-year. In October 2023, both Monday and Thursday recorded the highest number of crashes with 6 each, and the peak hour was 4 PM with 3 crashes. This contrasts with October 2022, where Thursday was the peak day with 4 crashes, and the peak hour was 2 PM with 2 crashes.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity distribution showed a slight increase in overall injuries, rising from 6 in October 2022 to 7 in October 2023. Minor injury crashes remained constant at 4 crashes in both periods, representing 25% of total crashes. Possible injury crashes decreased from 1 in the prior period to 0 in the current period, while fatal crashes remained at 0 in both periods.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes25%
0.0%prior 4
No Injury12no injury crashes75%
9.1%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Most severe injury per crash record

Top Contributing Factors

Contributing factors saw shifts in several categories year-over-year. Crashes attributed to 'No improper driving' increased by 5, from 3 in the prior period to 8 in the current period. Conversely, 'Inattention' crashes decreased by 4, falling from 5 to 1. 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner' crashes increased by 1, from 1 to 2, while 'Followed too closely' crashes remained stable at 2 in both periods.

Officer-Reported Primary Contributing Cause

No improper driving8 (50%)
Followed too closely2 (12.5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (12.5%)
Inattention1 (6.3%)-80.0%prior 5
Made an improper turn1 (6.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Weather conditions for crashes saw an increase in 'Clear' conditions, rising from 11 crashes in October 2022 to 14 in October 2023. Crashes occurring in 'Rain/Cloudy' conditions decreased from a combined 5 in the prior period to 1 in the current period. For lighting, 'Daylight' crashes increased from 11 to 15, while 'Dark - roadway not lighted' crashes decreased from 3 to 1. Road surface conditions showed a slight increase in 'Dry' crashes from 13 to 14, and a decrease in 'Wet' crashes from 3 to 2.

Weather

Clear14 (93.3%)
27.3%prior 11
Rain/Cloudy1 (6.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Weather condition at time of crash

Lighting

Daylight15 (93.8%)
36.4%prior 11
Dark - roadway not lighted1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Lighting condition field

Road Surface

Dry14 (87.5%)
7.7%prior 13
Wet2 (12.5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (27 vehicles)

1
JEEP4 (14.8%)
2
CHEVROLET4 (14.8%)
3
FORD2 (7.4%)
4
HONDA2 (7.4%)
5
TOYOTA2 (7.4%)
-66.7%prior 6
6
HYUNDAI2 (7.4%)
7
MAZDA1 (3.7%)
8
MERCEDES-BENZ1 (3.7%)
9
NISSAN1 (3.7%)
10
PTRB1 (3.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Vehicle unit records

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

Sex Distribution (32 persons with recorded sex)

Male18 (56.3%)
-10.0%prior 20
Female14 (43.8%)
-22.2%prior 18

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · Person-level records linked to crash events

Speed Limit Zones

The distribution of crashes across speed zones saw some changes year-over-year. Crashes in the 35 mph speed zone decreased from 3 in October 2022 to 1 in October 2023. A crash in a 15 mph speed zone was recorded in the current period, which was not present in the prior period. Other speed zones, including 30 mph, 40 mph, 50 mph, 55 mph, and 65 mph, maintained consistent crash counts between the two periods, and no fatal crashes occurred in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-10-01 to 2023-10-31 · 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: 2023-10-01 through 2023-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-10-01 through 2023-10-31 (31 days)
  • Geographic scope: SUTTON, MA
  • Total crash records analyzed: 16
  • Total persons involved: 33
  • Total vehicles involved: 27

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: October 2023." Published June 21, 2026. Reporting period: 2023-10-01 to 2023-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/sutton/october-2023-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 — October 2023 | ThatCarHitMe.com