Monthly Traffic Safety Analysis

16 CRASHES IN
HOLBROOK, MA
NOVEMBER 2025

All metrics benchmarked againstNovember 2024

HOLBROOK experienced a significant decrease in total crashes, falling from 24 in November 2024 to 16 in November 2025, representing a 33.33% reduction year-over-year. A notable shift includes the emergence of crashes related to 'Exceeded authorized speed limit' and 'Distracted' driving, which were not reported in the prior period. Additionally, DUI-related crashes increased from 0 to 1 during this period.

16

▼ -33.3%was 24

Total Crash Events

0

Persons Killed

8

Persons Injured

0

▼ -100.0%was 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

Overall, crashes in HOLBROOK show a downward trend year-over-year, decreasing by 8 crashes from 24 in November 2024 to 16 in November 2025. This represents a substantial 33.33% reduction in total crash incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 0→0.0%

8

Motorists Injured

Prior: 8→0.0%

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 shifted from Saturday with 7 crashes in November 2024 to Friday with 5 crashes in November 2025. Similarly, the peak hour changed from 11 AM with 5 crashes in the prior period to 12 PM with 4 crashes in the current period, indicating a shift in peak activity times.

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

Total fatalities remained at 0 in both November 2024 and November 2025, and the total number of injured persons also remained stable at 8. However, the proportion of crashes involving any injury (Serious, Minor, or Possible) increased from 29.17% (7 of 24 crashes) in the prior period to 43.75% (7 of 16 crashes) in the current period, with one crash resulting in serious injury in November 2025 compared to none in the prior year.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.3%
Minor Injury3minor injury crashes18.8%
↓-25.0%prior 4
Possible Injury3possible injury crashes18.8%
→0.0%prior 3
No Injury9no injury crashes56.3%
↓-47.1%prior 17

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 contributing factor 'Inattention' saw a significant decrease, falling from 9 crashes in November 2024 to 2 crashes in November 2025, a 77.8% reduction. 'No improper driving' also decreased from 7 crashes to 5 crashes, a 28.6% reduction. Conversely, factors like 'Exceeded authorized speed limit' and 'Followed too closely' emerged in November 2025 with 2 crashes each, where they were not reported in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving5 (31.3%)↓-28.6%prior 7
Exceeded authorized speed limit2 (12.5%)
Inattention2 (12.5%)↓-77.8%prior 9
Followed too closely2 (12.5%)
Distracted1 (6.3%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (6.3%)
Failed to yield right of way1 (6.3%)
Failure to keep in proper lane or running off road1 (6.3%)
Glare1 (6.3%)

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

Regarding lighting conditions, crashes occurring in daylight decreased from 16 in November 2024 to 10 in November 2025, while their share of total crashes remained relatively stable at 66.7% and 62.5% respectively. Crashes in 'Dark - lighted roadway' conditions decreased from 7 to 4, and one crash in November 2025 occurred in 'Dark - roadway not lighted' conditions, which was not reported in the prior period.

Lighting

Daylight10 (62.5%)
↓-37.5%prior 16
Dark - lighted roadway4 (25.0%)
↓-42.9%prior 7
Dark - roadway not lighted1 (6.3%)
Dawn1 (6.3%)

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

Vehicles & Demographics

Top Vehicle Makes (30 vehicles)

1
HONDA6 (20%)
→0.0%prior 6
2
FORD4 (13.3%)
3
CHEVROLET4 (13.3%)
↓-20.0%prior 5
4
HYUNDAI3 (10%)
5
TOYOTA2 (6.7%)
↓-66.7%prior 6
6
DODGE2 (6.7%)
7
JEEP2 (6.7%)
8
NISSAN2 (6.7%)
9
SUBARU2 (6.7%)
↓-60.0%prior 5
10
GMC1 (3.3%)

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)

Male17 (58.6%)
↓-43.3%prior 30
Female12 (41.4%)
↓-40.0%prior 20

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 occurring in 35 mph speed zones decreased from 20 in November 2024 to 11 in November 2025, a 45% reduction. Conversely, crashes in 25 mph speed zones increased from 1 in the prior period to 4 in the current period, a 300% increase. No fatalities were reported in any speed zone for either period.

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: HOLBROOK, MA
  • Total crash records analyzed: 16
  • Total persons involved: 31
  • Total vehicles involved: 30

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). "HOLBROOK, 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/holbrook/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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Holbrook, MA Crash Report — November 2025 | ThatCarHitMe.com