Yearly Traffic Safety Analysis

175 CRASHES IN
HOLBROOK, MA
2025

All metrics benchmarked against2024

In Holbrook, total traffic crashes decreased by 21.5% from 223 incidents in 2024 to 175 in 2025. This downward trend was accompanied by a 32.4% reduction in total injuries, which fell from 74 to 50. The most notable year-over-year shift was the overall reduction in crash volume across most categories, though crashes attributed to exceeding the speed limit increased from 2 to 5.

175

-21.5%was 223

Total Crash Events

0

Persons Killed

50

-32.4%was 74

Persons Injured

13

-27.8%was 18

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. 11 crashes with unreported severity are not shown in the severity breakdown.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Holbrook indicates a significant downward trend year-over-year. The total number of crashes fell from 223 to 175, a 21.5% decrease. Similarly, the number of individuals injured in these incidents dropped by 32.4%, from 74 to 50, while fatalities remained at zero in both periods.

13

Hit-and-Run Crashes — 2025

-27.8% vs prior (18)

Hit-and-run incidents decreased both in absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes fell from 18 in 2024 to 13 in 2025. Correspondingly, the hit-and-run rate declined from 8.1% to 7.4% year-over-year, indicating a downward trend for this type of incident.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Cyclists Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

3

Pedestrians Injured

Prior: 1200.0%

1

Cyclists Injured

Prior: 0%

46

Motorists Injured

Prior: 71-35.2%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed a shift between the two periods. In 2025, the peak day for crashes was Thursday with 32 incidents, and the peak hour was 2 PM with 19 incidents. This contrasts with 2024, when the peak day was Wednesday (41 crashes) and the peak hour was later in the afternoon at 4 PM (25 crashes).

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity saw a positive shift, with zero fatal crashes recorded in either 2024 or 2025. While the number of serious injury crashes remained stable at 4, crashes involving possible injuries were halved, dropping from 18 in 2024 to 9 in 2025. Overall, the total number of persons injured decreased from 74 to 50 year-over-year.

Outcome by Severity (Crash Events)

Serious Injury4serious injury crashes2.3%
0.0%prior 4
Minor Injury28minor injury crashes16%
-15.2%prior 33
Possible Injury9possible injury crashes5.1%
-50.0%prior 18
No Injury123no injury crashes70.3%
-22.6%prior 159

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes remained consistent in ranking, with 'No improper driving' and 'Inattention' being the top two in both years. However, the count for nearly all top factors decreased; for instance, crashes attributed to 'Inattention' fell from 33 to 31. A notable exception was crashes involving 'Exceeded authorized speed limit,' which saw its count increase by 150%, from 2 incidents in 2024 to 5 in 2025.

Officer-Reported Primary Contributing Cause

No improper driving67 (38.3%)-32.3%prior 99
Inattention31 (17.7%)-6.1%prior 33
Failed to yield right of way9 (5.1%)-10.0%prior 10
Followed too closely7 (4%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner6 (3.4%)20.0%prior 5
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway6 (3.4%)
Fatigued/asleep6 (3.4%)
Exceeded authorized speed limit5 (2.9%)
Failure to keep in proper lane or running off road4 (2.3%)-50.0%prior 8
Other improper action3 (1.7%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes by environmental conditions remained largely consistent year-over-year. In both 2025 and 2024, the majority of incidents occurred in clear weather on dry roads during daylight hours. Crashes on wet roads saw a notable decrease from 43 to 24, mirroring the overall reduction in total crashes, while the proportion of crashes under different lighting and weather conditions did not change significantly.

Weather

Clear133 (76.4%)
-21.3%prior 169
Rain16 (9.2%)
-20.0%prior 20
Cloudy10 (5.7%)
42.9%prior 7
Snow5 (2.9%)
Snow/Sleet, hail (freezing rain or drizzle)3 (1.7%)
Cloudy/Rain2 (1.1%)
-77.8%prior 9
Clear/Cloudy1 (0.6%)
Snow/Blowing sand, snow1 (0.6%)
Snow/Clear1 (0.6%)
Snow/Cloudy1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight118 (67.8%)
-20.3%prior 148
Dark - lighted roadway42 (24.1%)
-33.3%prior 63
Dark - roadway not lighted7 (4.0%)
Dawn4 (2.3%)
-20.0%prior 5
Dusk2 (1.1%)
-60.0%prior 5
Other1 (0.6%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry137 (78.7%)
-18.9%prior 169
Wet24 (13.8%)
-44.2%prior 43
Snow9 (5.2%)
Ice2 (1.1%)
-60.0%prior 5
Slush2 (1.1%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Toyota, Honda, and Ford were the top three vehicle makes involved in crashes in 2025, with Toyota (56) and Honda (33) seeing a decrease in counts from the prior year. In 2024, the top makes were Toyota (71), Honda (55), and Chevrolet (45). The age distribution of persons involved in crashes showed a slight shift, with a higher proportion of individuals in the 26-34 and 35-44 age groups in 2025 compared to 2024.

Top Vehicle Makes (314 vehicles)

1
TOYOTA56 (17.8%)
-21.1%prior 71
2
FORD35 (11.1%)
-2.8%prior 36
3
HONDA33 (10.5%)
-40.0%prior 55
4
NISSAN26 (8.3%)
52.9%prior 17
5
JEEP25 (8%)
19.0%prior 21
6
CHEVROLET25 (8%)
-44.4%prior 45
7
HYUNDAI10 (3.2%)
0.0%prior 10
8
SUBARU8 (2.5%)
-11.1%prior 9
9
KIA7 (2.2%)
-12.5%prior 8
10
LEXUS7 (2.2%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (325 persons with recorded sex)

Male175 (53.8%)
-27.4%prior 241
Female150 (46.2%)
-25.4%prior 201

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Speed Limit Zones

The 35 mph speed zone was the site of the most crashes in both periods, accounting for 121 crashes in 2025 and 165 in 2024. While the number of crashes in this zone decreased, it still represented 69.1% of all crashes in the current year. No fatal crashes were recorded in any speed zone during either period.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: HOLBROOK, MA
  • Total crash records analyzed: 175
  • Total persons involved: 359
  • Total vehicles involved: 314

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: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/holbrook/2025-annual-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 — 2025 | ThatCarHitMe.com