Monthly Traffic Safety Analysis

24 CRASHES IN
HOLLISTON, MA
JANUARY 2023

All metrics benchmarked againstJanuary 2022

In January 2023, Holliston recorded 24 crashes, a 20% increase compared to the 20 crashes in January 2022. The most significant year-over-year shift was a 200% increase in total injuries, rising from 3 injuries in the prior year to 9 injuries in the current period.

24

20.0%was 20

Total Crash Events

0

Persons Killed

9

200.0%was 3

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 · 2023-01-01 to 2023-01-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash data for Holliston shows an upward trend in January 2023 compared to January 2022, with total crashes increasing by 20% from 20 to 24. This period also saw a substantial rise in total injuries, which grew by 200% from 3 to 9, while fatalities remained at zero for both periods.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

9

Motorists Injured

Prior: 3200.0%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns for crashes shifted year-over-year; the peak day for crashes moved from Saturday with 7 crashes in January 2022 to Monday with 9 crashes in January 2023. Similarly, the peak crash hour changed from 4 PM with 3 crashes in the prior year to 7 AM with 4 crashes in the current year. Crashes on Sundays, Mondays, and Tuesdays increased, while crashes on Thursdays, Fridays, and Saturdays decreased.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While no fatal crashes occurred in either January 2022 or January 2023, the total number of injured persons increased substantially from 3 in January 2022 to 9 in January 2023. This represents a 200% increase in injuries, with 2 serious injuries, 5 minor injuries, and 2 possible injuries recorded in the current period compared to only 3 minor injuries in the prior year.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes8.3%
Minor Injury5minor injury crashes20.8%
66.7%prior 3
Possible Injury1possible injury crashes4.2%
No Injury16no injury crashes66.7%
-5.9%prior 17

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record

Top Contributing Factors

The most frequently cited contributing factor, 'No improper driving,' saw a 116.7% increase in crashes, rising from 6 in January 2022 to 13 in January 2023. Crashes attributed to 'Followed too closely' increased by 200%, from 1 to 3, while 'Driving too fast for conditions' decreased by 75%, from 4 crashes to 1. The factor 'Inattention' also saw a 50% decrease, from 2 crashes to 1.

Officer-Reported Primary Contributing Cause

No improper driving13 (54.2%)116.7%prior 6
Followed too closely3 (12.5%)
Driving too fast for conditions1 (4.2%)
Inattention1 (4.2%)
Failure to keep in proper lane or running off road1 (4.2%)
Failed to yield right of way1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in 'Daylight' conditions increased from 11 in January 2022 to 17 in January 2023, while those in 'Dark - lighted roadway' conditions decreased from 6 to 3. Regarding road surface, crashes on 'Wet' roads increased from 2 to 7, and 'Dry' road crashes remained constant at 9 for both periods. The number of crashes in 'Clear' weather conditions decreased from 11 to 8, and 'Snow' related crashes remained at 3.

Weather

Clear8 (33.3%)
-27.3%prior 11
Cloudy4 (16.7%)
Snow3 (12.5%)
Snow/Cloudy3 (12.5%)
Snow/Sleet, hail (freezing rain or drizzle)2 (8.3%)
Rain2 (8.3%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (4.2%)
Cloudy/Rain1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash

Lighting

Daylight17 (70.8%)
54.5%prior 11
Dark - lighted roadway3 (12.5%)
-50.0%prior 6
Dark - roadway not lighted2 (8.3%)
Dusk2 (8.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field

Road Surface

Dry9 (37.5%)
0.0%prior 9
Wet7 (29.2%)
Snow5 (20.8%)
0.0%prior 5
Slush2 (8.3%)
Sand, mud, dirt, oil, gravel1 (4.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (39 vehicles)

1
HONDA9 (23.1%)
80.0%prior 5
2
FORD6 (15.4%)
20.0%prior 5
3
TOYOTA4 (10.3%)
-20.0%prior 5
4
CADI3 (7.7%)
5
KIA2 (5.1%)
6
NISSAN2 (5.1%)
7
CHEVROLET2 (5.1%)
8
JEEP2 (5.1%)
9
BMW1 (2.6%)
10
VOLVO1 (2.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records

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

Sex Distribution (43 persons with recorded sex)

Male23 (53.5%)
4.5%prior 22
Female20 (46.5%)
5.3%prior 19

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 25 mph speed zones increased by 133.3%, rising from 3 crashes in January 2022 to 7 crashes in January 2023. Crashes in 30 mph zones also increased from 5 to 6, a 20% rise. Conversely, crashes in 35 mph zones saw a 10% decrease, from 10 to 9, and 40 mph zones remained constant with 2 crashes in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2023-01-01 to 2023-01-31 · 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: 2023-01-01 through 2023-01-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-01-31 (31 days)
  • Geographic scope: HOLLISTON, MA
  • Total crash records analyzed: 24
  • Total persons involved: 44
  • Total vehicles involved: 39

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: January 2023." Published June 21, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/holliston/january-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 — January 2023 | ThatCarHitMe.com