Monthly Traffic Safety Analysis

8 CRASHES IN
BLACKSTONE, MA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

In October 2025, Blackstone experienced 8 crashes, a 20% decrease compared to the 10 crashes in October 2024. Total injuries also saw a significant reduction, falling by 50% from 2 injuries in the prior year to 1 injury in the current period.

8

-20.0%was 10

Total Crash Events

0

Persons Killed

1

-50.0%was 2

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

Trend Summary

Overall crash activity in Blackstone trended downward year-over-year, with total crashes decreasing by 20% from 10 in October 2024 to 8 in October 2025. This reduction was accompanied by a 50% decrease in total injuries, from 2 to 1, while fatalities remained at zero in both periods.

1

Hit-and-Run Crashes — October 2025

0.0% vs prior (1)

The number of hit-and-run crashes remained constant at 1 in both October 2024 and October 2025. However, due to a decrease in total crashes, the hit-and-run rate increased from 10% in the prior year to 12.5% in the current year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 2-50.0%

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

Thursday remained the day with the most crashes in both periods, though the count decreased from 5 in October 2024 to 4 in October 2025. The peak crash hour shifted from 7 AM with 3 crashes in the prior year to 3 PM with 2 crashes in the current year, indicating a change in peak traffic collision times.

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

Fatal crashes remained at zero in both October 2024 and October 2025. The number of serious injury crashes decreased from 1 in October 2024 to 0 in October 2025, contributing to an overall 50% reduction in total injuries from 2 to 1. Possible injury crashes remained constant at 1 in both periods.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes12.5%
0.0%prior 1
No Injury7no injury crashes87.5%
-12.5%prior 8

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

Crashes attributed to 'Inattention' decreased by one, from 4 in October 2024 to 3 in October 2025, representing a 25% reduction. 'Failed to yield right of way' crashes completely disappeared, dropping from 2 in the prior period to 0 in the current period. Conversely, 'Distracted' and 'Fatigued/asleep' each emerged as factors in one crash in October 2025, neither having been present in the prior year's data.

Officer-Reported Primary Contributing Cause

Inattention3 (37.5%)
No improper driving2 (25%)
Distracted1 (12.5%)
Fatigued/asleep1 (12.5%)
Other improper action1 (12.5%)

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

Daylight conditions accounted for 7 crashes in October 2025, an increase from 6 crashes in October 2024. Crashes occurring in 'Dark - lighted roadway' conditions decreased from 3 to 1 year-over-year. Additionally, the single crash that occurred during 'Dusk' in the prior period was not observed in the current period.

Lighting

Daylight7 (87.5%)
16.7%prior 6
Dark - lighted roadway1 (12.5%)

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

Vehicles & Demographics

Top Vehicle Makes (15 vehicles)

1
HONDA2 (13.3%)
2
HYUNDAI2 (13.3%)
3
FORD2 (13.3%)
4
MERCEDES-BENZ1 (6.7%)
5
NISSAN1 (6.7%)
6
SUBARU1 (6.7%)
7
TOYOTA1 (6.7%)
8
CHEVROLET1 (6.7%)
9
WRGT1 (6.7%)
10
GMC1 (6.7%)

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

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

Sex Distribution (15 persons with recorded sex)

Female8 (53.3%)
-20.0%prior 10
Male7 (46.7%)
-12.5%prior 8

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 25 mph speed zones increased from 1 in October 2024 to 4 in October 2025. Conversely, crashes in 30 mph zones decreased significantly, from 8 in the prior year to 3 in the current year. There were no fatal crashes reported in any speed zone during either 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: BLACKSTONE, MA
  • Total crash records analyzed: 8
  • Total persons involved: 17
  • Total vehicles involved: 15

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). "BLACKSTONE, 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/blackstone/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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Blackstone, MA Crash Report — October 2025 | ThatCarHitMe.com