Monthly Traffic Safety Analysis

20 CRASHES IN
KINGSTON, MA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

In October 2025, KINGSTON, MA experienced 20 crashes, a 9.1% decrease compared to the 22 crashes reported in October 2024. A significant positive shift is the reduction in fatalities, with 0 reported in the current period compared to 1 in the prior year. This indicates a notable improvement in crash outcomes for the month.

20

-9.1%was 22

Total Crash Events

0

-100.0%was 1

Persons Killed

10

11.1%was 9

Persons Injured

0

-100.0%was 1

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 · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, the trend for October in KINGSTON, MA shows a decrease in total crashes, falling from 22 in the prior year to 20 in the current period. This represents a 9.1% reduction in crash events. A positive development is the absence of crash fatalities in the current month, compared to one fatality in the prior year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1-100.0%

10

Motorists Injured

Prior: 911.1%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · 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, with the peak day moving from Saturday (7 crashes) in October 2024 to Friday (5 crashes) in October 2025. Similarly, the peak crash hour changed from 12 p.m. (4 crashes) in the prior period to 11 a.m. (3 crashes) in the current period. This indicates a shift in the busiest crash times for the month.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a positive shift, with fatal crashes decreasing from 1 in October 2024 to 0 in October 2025. Serious injuries (Severity A) also decreased from 2 crashes (9.1% of total) to 0 crashes year-over-year. However, minor injuries (Severity B) increased from 5 crashes (22.7% of total) to 6 crashes (30% of total), and possible injuries (Severity C) rose from 0 to 1 crash (5% of total).

Outcome by Severity (Crash Events)

Minor Injury6minor injury crashes30%
20.0%prior 5
Possible Injury1possible injury crashes5%
No Injury13no injury crashes65%
-7.1%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record

Top Contributing Factors

A notable shift in contributing factors shows "Inattention" crashes increased from 1 in October 2024 to 5 in October 2025, while crashes attributed to "No improper driving" decreased significantly from 10 to 4. "Failed to yield right of way" also saw an increase, rising from 1 crash to 3 crashes year-over-year. Other factors like "Glare" and "Operating vehicle in an erratic manner" remained constant with 1 crash each in both periods.

Officer-Reported Primary Contributing Cause

Inattention5 (25%)
No improper driving4 (20%)-60.0%prior 10
Failed to yield right of way3 (15%)
Glare1 (5%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (5%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway1 (5%)
Visibility obstructed1 (5%)
Driving too fast for conditions1 (5%)
Failure to keep in proper lane or running off road1 (5%)
Followed too closely1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 17 in October 2024 to 14 in October 2025, while crashes during rainy conditions increased from 0 to 4. There was a significant shift in lighting conditions, with daylight crashes increasing from 9 to 14, and crashes occurring in dark conditions decreasing from 10 to 5. The road surface conditions data was not available for comparison in the prior period.

Weather

Clear13 (65.0%)
-13.3%prior 15
Cloudy2 (10.0%)
Cloudy/Rain2 (10.0%)
Clear/Clear1 (5.0%)
Rain1 (5.0%)
Rain/Rain1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash

Lighting

Daylight14 (70.0%)
55.6%prior 9
Dark - roadway not lighted3 (15.0%)
Dark - lighted roadway2 (10.0%)
Dawn1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field

Road Surface

Dry16 (80.0%)
Wet4 (20.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (36 vehicles)

1
CHEVROLET5 (13.9%)
0.0%prior 5
2
HONDA5 (13.9%)
3
TOYOTA4 (11.1%)
-33.3%prior 6
4
HYUNDAI4 (11.1%)
5
FORD3 (8.3%)
6
JEEP3 (8.3%)
7
VOLKSWAGEN2 (5.6%)
8
NISSAN2 (5.6%)
9
KIA1 (2.8%)
10
GMC1 (2.8%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records

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

Sex Distribution (41 persons with recorded sex)

Female26 (63.4%)
8.3%prior 24
Male15 (36.6%)
-42.3%prior 26

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 30 mph speed zone decreased significantly from 12 in October 2024 to 4 in October 2025. Conversely, crashes in higher speed zones such as 35 mph increased from 1 to 4, and 40 mph zones increased from 1 to 3. The 60 mph zone saw a decrease from 2 crashes to 1, and notably, the single fatal crash in the prior period occurred in a 60 mph zone, with no fatalities reported in any speed zone in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-10-01 through 2025-10-31 (31 days)
  • Geographic scope: KINGSTON, MA
  • Total crash records analyzed: 20
  • Total persons involved: 44
  • Total vehicles involved: 36

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). "KINGSTON, MA Crash Intelligence Report: October 2025." Published June 21, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/kingston/october-2025-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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Kingston, MA Crash Report — October 2025 | ThatCarHitMe.com