Monthly Traffic Safety Analysis

11 CRASHES IN
HOLLISTON, MA
JUNE 2025

All metrics benchmarked againstJune 2024

Total crashes in Holliston decreased from 19 in June 2024 to 11 in June 2025, representing a 42.1% reduction. The most notable year-over-year shift was the substantial decrease in total injuries, which fell from 6 in the prior year to 1 in the current year.

11

-42.1%was 19

Total Crash Events

0

Persons Killed

1

-83.3%was 6

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.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash trends in Holliston show a significant decline year-over-year. Total crashes decreased by 42.1%, from 19 in June 2024 to 11 in June 2025. This reduction was accompanied by an 83.3% decrease in total injuries, from 6 to 1.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

1

Motorists Injured

Prior: 4-75.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The distribution of crashes across the week shifted, with the peak crash day moving from Saturday (4 crashes) in June 2024 to Thursday (3 crashes) in June 2025. While the peak hour remained 5 PM in both periods, the number of crashes at that hour decreased from 5 in June 2024 to 2 in June 2025. Notably, Saturday crashes dropped from 4 to 0, and Monday crashes dropped from 3 to 0.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

No fatal crashes were reported in either June 2024 or June 2025. Total injuries decreased significantly from 6 in June 2024 to 1 in June 2025. The proportion of crashes resulting in "No Injury" increased from 63.2% in the prior period to 90.9% in the current period, while "Minor Injury" crashes, which accounted for 26.3% of crashes in June 2024, were absent in June 2025.

Outcome by Severity (Crash Events)

Possible Injury1possible injury crashes9.1%
0.0%prior 1
No Injury10no injury crashes90.9%
-16.7%prior 12

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

Crashes attributed to "Failed to yield right of way" decreased from 4 incidents in June 2024 to 0 in June 2025. "No improper driving" crashes decreased from 4 to 3, and "Inattention" crashes decreased from 3 to 1. "Followed too closely" crashes also saw a reduction, from 2 to 1.

Officer-Reported Primary Contributing Cause

No improper driving3 (27.3%)
Followed too closely1 (9.1%)
Visibility obstructed1 (9.1%)
Wrong side or wrong way1 (9.1%)
Other improper action1 (9.1%)
Inattention1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in "Clear" weather decreased from 13 in June 2024 to 8 in June 2025. Similarly, crashes on "Wet" road surfaces decreased from 3 to 2 year-over-year. Data for lighting conditions was only available for the prior period, preventing a comparative analysis for this factor.

Weather

Clear8 (72.7%)
-38.5%prior 13
Cloudy1 (9.1%)
Cloudy/Rain1 (9.1%)
Rain/Cloudy1 (9.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Road Surface

Dry9 (81.8%)
-43.8%prior 16
Wet2 (18.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (19 vehicles)

1
MERCEDES-BENZ2 (10.5%)
2
HONDA2 (10.5%)
3
FORD2 (10.5%)
4
FL1 (5.3%)
5
FRHT1 (5.3%)
6
HYUNDAI1 (5.3%)
7
KIA1 (5.3%)
8
MAZDA1 (5.3%)
9
NISSAN1 (5.3%)
10
PTRB1 (5.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

Sex Distribution (23 persons with recorded sex)

Male14 (60.9%)
-39.1%prior 23
Female9 (39.1%)
0.0%prior 9

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · Person-level records linked to crash events

Speed Limit Zones

Crashes in the 25 mph speed zone decreased from 9 in June 2024 to 4 in June 2025. Conversely, crashes in the 35 mph zone increased from 2 to 5, and in the 40 mph zone from 1 to 2. This indicates a shift in the distribution of crashes towards higher posted speed limits in the current period, with no fatal crashes reported in any speed zone for either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: HOLLISTON, MA
  • Total crash records analyzed: 11
  • Total persons involved: 23
  • Total vehicles involved: 19

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: June 2025." Published June 21, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/holliston/june-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

ThatCarHitMe.com · An Injuria.ai Company

Holliston, MA Crash Report — June 2025 | ThatCarHitMe.com