Monthly Traffic Safety Analysis

20 CRASHES IN
WEST BOYLSTON, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

In November 2025, West Boylston experienced 20 crashes, a significant 66.67% increase compared to the 12 crashes recorded in November 2024. A notable shift is the emergence of hit-and-run incidents, with 2 crashes reported in the current period compared to none in the prior period. Total injuries also rose from 4 to 6 year-over-year.

20

66.7%was 12

Total Crash Events

0

Persons Killed

6

50.0%was 4

Persons Injured

2

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 · 2025-11-01 to 2025-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend indicates a substantial increase in crashes, with total incidents rising by 66.67% from 12 crashes in November 2024 to 20 crashes in November 2025. This represents an increase of 8 crashes year-over-year.

2

Hit-and-Run Crashes — November 2025

10.0% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 450.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Saturday in both periods, though the number of crashes on this day increased from 2 in November 2024 to 6 in November 2025. The peak crash hour shifted from 10 p.m. with 2 crashes in the prior period to 6 p.m. with 3 crashes in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While both periods reported zero fatalities, the total number of injured persons increased from 4 in November 2024 to 6 in November 2025. The prior period recorded 1 serious injury (Severity A), whereas the current period reported 4 minor injuries (Severity B) and 2 possible injuries (Severity C), with no serious injuries. The proportion of 'No Injury' crashes decreased from 91.7% to 70% year-over-year.

Outcome by Severity (Crash Events)

Minor Injury4minor injury crashes20%
Possible Injury2possible injury crashes10%
No Injury14no injury crashes70%
27.3%prior 11

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Most severe injury per crash record

Top Contributing Factors

The count of crashes attributed to 'No improper driving' increased significantly from 4 in November 2024 to 13 in November 2025, representing a 225% increase. Conversely, crashes attributed to 'Inattention' decreased by 50%, from 2 to 1. Factors such as 'Other improper action' and 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway', which accounted for 2 and 1 crashes respectively in the prior period, are not listed among the top factors for the current period.

Officer-Reported Primary Contributing Cause

No improper driving13 (65%)
Failed to yield right of way1 (5%)
Failure to keep in proper lane or running off road1 (5%)
Fatigued/asleep1 (5%)
Followed too closely1 (5%)
Inattention1 (5%)
Driving too fast for conditions1 (5%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 10 in November 2024 to 16 in November 2025, while crashes on dry road surfaces increased from 10 to 16. The number of crashes during daylight hours rose from 3 to 8. Notably, the current period recorded 1 crash in snowy conditions and 1 in cloudy conditions, which were not present in the prior period's data.

Weather

Clear13 (65.0%)
44.4%prior 9
Clear/Clear2 (10.0%)
Rain2 (10.0%)
Clear/Other1 (5.0%)
Cloudy1 (5.0%)
Snow1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Weather condition at time of crash

Lighting

Daylight8 (40.0%)
Dark - lighted roadway7 (35.0%)
16.7%prior 6
Dark - roadway not lighted4 (20.0%)
Dawn1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Lighting condition field

Road Surface

Dry16 (80.0%)
60.0%prior 10
Wet3 (15.0%)
Other1 (5.0%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (31 vehicles)

1
TOYOTA7 (22.6%)
2
NISSAN3 (9.7%)
3
HYUNDAI3 (9.7%)
4
HONDA3 (9.7%)
5
CHEVROLET2 (6.5%)
6
JEEP2 (6.5%)
7
GMC2 (6.5%)
8
VOLKSWAGEN1 (3.2%)
9
CHRYSLER1 (3.2%)
10
DODGE1 (3.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Vehicle unit records

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

Sex Distribution (29 persons with recorded sex)

Female15 (51.7%)
87.5%prior 8
Male14 (48.3%)
-33.3%prior 21

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones doubled from 3 in November 2024 to 6 in November 2025, and incidents in 40 mph zones increased from 6 to 8. The 65 mph zone maintained 1 crash in both periods. New speed zones with reported crashes in the current period include 25 mph (1 crash), 45 mph (1 crash), and 50 mph (2 crashes), while the 5 mph zone (1 crash) from the prior period is not present.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-11-01 to 2025-11-30 · 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: 2025-11-01 through 2025-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-11-01 through 2025-11-30 (30 days)
  • Geographic scope: WEST BOYLSTON, MA
  • Total crash records analyzed: 20
  • Total persons involved: 32
  • Total vehicles involved: 31

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). "WEST BOYLSTON, MA Crash Intelligence Report: November 2025." Published June 21, 2026. Reporting period: 2025-11-01 to 2025-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-boylston/november-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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West Boylston, MA Crash Report — November 2025 | ThatCarHitMe.com