Monthly Traffic Safety Analysis

16 CRASHES IN
WEST BOYLSTON, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, West Boylston experienced 16 crashes, a decrease of 11.1% compared to the 18 crashes recorded in November 2022. A notable improvement was observed in fatalities, with 0 reported in the current period compared to 1 in the prior year.

16

-11.1%was 18

Total Crash Events

0

-100.0%was 1

Persons Killed

5

66.7%was 3

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 · 2023-11-01 to 2023-11-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash incidents in West Boylston showed a downward trend year-over-year, decreasing by 11.1%. The total number of crashes fell from 18 in November 2022 to 16 in November 2023.

1

Hit-and-Run Crashes — November 2023

6.3% hit-and-run rate this period vs 0.0% prior. Prior period: 0.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 366.7%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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 Thursday (6 crashes) in November 2022 to Wednesday (4 crashes) in November 2023. The peak crash hour also changed, occurring at 10 PM (2 crashes) in the prior period but at 5 PM (4 crashes) in the current period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatal crashes decreased from 1 in November 2022 to 0 in November 2023, indicating an improvement in the most severe outcomes. However, total injuries increased from 3 to 5 year-over-year, with serious injuries appearing in the current period (1 crash, 6.3%) where none were recorded in the prior period.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.3%
Minor Injury2minor injury crashes12.5%
100.0%prior 1
Possible Injury1possible injury crashes6.3%
-50.0%prior 2
No Injury12no injury crashes75%
-14.3%prior 14

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Most severe injury per crash record

Top Contributing Factors

The most frequent contributing factor in November 2023 was "No improper driving," accounting for 8 crashes, a significant increase from 3 crashes in November 2022. Conversely, "Failed to yield right of way" decreased from 3 crashes in the prior period to 1 crash in the current period. Several factors present in the prior year, such as "Followed too closely" (2 crashes), were not observed in the current period.

Officer-Reported Primary Contributing Cause

No improper driving8 (50%)
Failure to keep in proper lane or running off road1 (6.3%)
Glare1 (6.3%)
Failed to yield right of way1 (6.3%)
Other improper action1 (6.3%)
Wrong side or wrong way1 (6.3%)
Distracted1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 17 in November 2022 to 13 in November 2023, while crashes on dry road surfaces also decreased from 17 to 13. Notably, the current period recorded crashes involving snow and ice conditions (1 crash each) which were not present in the prior year. Crashes in 'Dark - roadway not lighted' conditions increased from 2 to 4 year-over-year.

Weather

Clear13 (81.3%)
-23.5%prior 17
Cloudy1 (6.3%)
Cloudy/Rain1 (6.3%)
Snow1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Weather condition at time of crash

Lighting

Dark - lighted roadway6 (37.5%)
-25.0%prior 8
Daylight5 (31.3%)
-16.7%prior 6
Dark - roadway not lighted4 (25.0%)
Dusk1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Lighting condition field

Road Surface

Dry13 (81.3%)
-23.5%prior 17
Ice1 (6.3%)
Snow1 (6.3%)
Wet1 (6.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (28 vehicles)

1
TOYOTA6 (21.4%)
2
SUBARU3 (10.7%)
3
FORD3 (10.7%)
4
CHEVROLET2 (7.1%)
5
HONDA2 (7.1%)
6
JEEP2 (7.1%)
7
MAZDA1 (3.6%)
8
NISSAN1 (3.6%)
9
VOLKSWAGEN1 (3.6%)
10
ACURA1 (3.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Vehicle unit records

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

Sex Distribution (30 persons with recorded sex)

Female16 (53.3%)
6.7%prior 15
Male14 (46.7%)
-26.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes within the 40 mph speed zone decreased from 9 in November 2022 to 7 in November 2023, and crashes in the 30 mph zone also decreased from 5 to 2. A positive change was the elimination of fatal crashes in the 65 mph zone, which had 1 fatal crash in the prior period and 0 in the current period. Crashes in the 35 mph zone were recorded in the current period (3 crashes) but not in the prior.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-11-01 to 2023-11-30 · 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: 2023-11-01 through 2023-11-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-11-01 through 2023-11-30 (30 days)
  • Geographic scope: WEST BOYLSTON, MA
  • Total crash records analyzed: 16
  • Total persons involved: 32
  • Total vehicles involved: 28

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 2023." Published June 21, 2026. Reporting period: 2023-11-01 to 2023-11-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/west-boylston/november-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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West Boylston, MA Crash Report — November 2023 | ThatCarHitMe.com