Monthly Traffic Safety Analysis

21 CRASHES IN
HOLLISTON, MA
NOVEMBER 2023

All metrics benchmarked againstNovember 2022

In November 2023, Holliston experienced 21 crashes, marking a 50% increase from the 14 crashes reported in November 2022. A notable shift was the increase in total injuries, which rose from 0 in the prior period to 5 in the current period.

21

50.0%was 14

Total Crash Events

0

Persons Killed

5

Persons Injured

0

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. 1 crash with unreported severity is not shown in the severity breakdown.

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 activity in Holliston is on an upward trend year-over-year. Total crashes increased by 50%, rising from 14 in November 2022 to 21 in November 2023. This increase was accompanied by a rise in total injuries from 0 to 5.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 0%

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 peak day for crashes shifted from Friday with 4 crashes in November 2022 to Thursday with 6 crashes in November 2023. The peak hour for crashes remained consistent at 6p in both periods, with the count increasing from 3 crashes to 4 crashes at that hour.

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

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes9.5%
Possible Injury2possible injury crashes9.5%
No Injury16no injury crashes76.2%

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 count of crashes attributed to 'No improper driving' decreased by 20%, from 10 in November 2022 to 8 in November 2023. 'Inattention' crashes also decreased by 50% in count, from 2 to 1. 'Failed to yield right of way' emerged as a contributing factor in November 2023 with 4 crashes, while it was not present in the prior period's listed factors.

Officer-Reported Primary Contributing Cause

No improper driving8 (38.1%)-20.0%prior 10
Failed to yield right of way4 (19%)
Inattention1 (4.8%)
History heart/epilepsy/fainting1 (4.8%)
Followed too closely1 (4.8%)
Distracted1 (4.8%)

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 increased from 10 in November 2022 to 17 in November 2023. Crashes during 'Daylight' conditions doubled, rising from 6 to 12, while crashes in 'Dark - lighted roadway' conditions decreased from 6 to 4. Crashes on 'Dry' road surfaces increased from 11 to 18, and those on 'Wet' surfaces increased from 2 to 3, with 'Ice' conditions reported in the prior period but not the current.

Weather

Clear17 (81.0%)
70.0%prior 10
Cloudy2 (9.5%)
Clear/Other1 (4.8%)
Rain/Cloudy1 (4.8%)

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

Lighting

Daylight12 (60.0%)
100.0%prior 6
Dark - lighted roadway4 (20.0%)
-33.3%prior 6
Dark - roadway not lighted2 (10.0%)
Dawn1 (5.0%)
Dusk1 (5.0%)

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

Road Surface

Dry18 (85.7%)
63.6%prior 11
Wet3 (14.3%)

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 (38 vehicles)

1
TOYOTA6 (15.8%)
20.0%prior 5
2
HONDA6 (15.8%)
3
HYUNDAI3 (7.9%)
4
AUDI3 (7.9%)
5
NISSAN3 (7.9%)
6
SUBARU3 (7.9%)
7
CHEVROLET2 (5.3%)
8
JEEP2 (5.3%)
9
FORD2 (5.3%)
10
GMC1 (2.6%)

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

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

Sex Distribution (46 persons with recorded sex)

Female28 (60.9%)
366.7%prior 6
Male18 (39.1%)
5.9%prior 17

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 in the 30 mph speed zone increased from 3 to 7, while those in the 35 mph zone rose from 5 to 8. Crashes in the 40 mph zone also increased from 1 to 3. The 45 mph speed zone, which accounted for 2 crashes in November 2022, reported no crashes in November 2023, and no fatalities were recorded in any speed zone during either period.

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: HOLLISTON, MA
  • Total crash records analyzed: 21
  • Total persons involved: 47
  • Total vehicles involved: 38

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). "HOLLISTON, 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/holliston/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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Holliston, MA Crash Report — November 2023 | ThatCarHitMe.com