Monthly Traffic Safety Analysis

75 CRASHES IN
MARLBOROUGH, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

In February 2025, MARLBOROUGH experienced 75 total crashes, a slight increase from the 73 crashes reported in February 2024, representing a 2.74% rise. A notable shift was the 100% increase in crashes attributed to 'Followed too closely,' rising from 6 incidents in the prior year to 12 in the current period.

75

2.7%was 73

Total Crash Events

0

Persons Killed

15

25.0%was 12

Persons Injured

8

14.3%was 7

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

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, total crashes in MARLBOROUGH showed a slight upward trend, increasing from 73 in February 2024 to 75 in February 2025. This represents a 2.74% increase year-over-year. Fatalities remained at zero in both periods.

8

Hit-and-Run Crashes — February 2025

14.3% vs prior (7)

Hit-and-run crashes increased from 7 in February 2024 to 8 in February 2025. The hit-and-run rate also saw an increase, rising from 9.6% in the prior period to 10.7% in the current period, indicating an upward trend.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

0

Motorists Killed

Prior: 00.0%

1

Pedestrians Injured

Prior: 10.0%

14

Motorists Injured

Prior: 1127.3%

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak day for crashes remained Thursday in both periods, with 17 crashes in February 2025 and 16 in February 2024. However, the peak hour shifted from 4 p.m. with 9 crashes in February 2024 to 12 p.m. with 7 crashes in February 2025.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash date field aggregated by weekday

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Fatalities remained at 0 in both February 2024 and February 2025. Total injuries increased from 12 in the prior period to 15 in the current period, a 25% rise. Minor injuries (severity B) increased from 7 to 9, while possible injuries (severity C) increased from 4 to 5.

Outcome by Severity (Crash Events)

Minor Injury9minor injury crashes12%
28.6%prior 7
Possible Injury5possible injury crashes6.7%
25.0%prior 4
No Injury59no injury crashes78.7%
-3.3%prior 61

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor, 'No improper driving,' increased by 5 incidents, from 19 in February 2024 to 24 in February 2025. Crashes attributed to 'Followed too closely' doubled, rising from 6 to 12 incidents, making it the second most frequent factor in the current period. Conversely, 'Inattention' decreased by 3 incidents (from 10 to 7), and 'Failed to yield right of way' decreased by 4 incidents (from 8 to 4).

Officer-Reported Primary Contributing Cause

No improper driving24 (32%)26.3%prior 19
Followed too closely12 (16%)100.0%prior 6
Inattention7 (9.3%)-30.0%prior 10
Failed to yield right of way4 (5.3%)-50.0%prior 8
Driving too fast for conditions4 (5.3%)
Visibility obstructed3 (4%)
Failure to keep in proper lane or running off road3 (4%)-50.0%prior 6
Disregarded traffic signs, signals, road markings2 (2.7%)
Other improper action2 (2.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes occurring in clear weather conditions decreased from 61 in February 2024 to 52 in February 2025, while crashes in snow conditions increased from 3 to 11. Incidents during daylight hours rose from 45 to 53, and crashes on dry road surfaces decreased from 61 to 49. Notably, crashes on icy road surfaces were recorded at 9 in February 2025, compared to 0 in February 2024.

Weather

Clear52 (69.3%)
-14.8%prior 61
Snow11 (14.7%)
Cloudy6 (8.0%)
Sleet, hail (freezing rain or drizzle)1 (1.3%)
Sleet, hail (freezing rain or drizzle)/Rain1 (1.3%)
Snow/Sleet, hail (freezing rain or drizzle)1 (1.3%)
Snow/Snow1 (1.3%)
Rain1 (1.3%)
Rain/Rain1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Weather condition at time of crash

Lighting

Daylight53 (70.7%)
17.8%prior 45
Dark - lighted roadway12 (16.0%)
-36.8%prior 19
Dark - roadway not lighted6 (8.0%)
Dark - unknown roadway lighting2 (2.7%)
Dawn1 (1.3%)
Dusk1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Lighting condition field

Road Surface

Dry49 (65.3%)
-19.7%prior 61
Snow11 (14.7%)
Ice9 (12.0%)
Wet4 (5.3%)
-50.0%prior 8
Sand, mud, dirt, oil, gravel1 (1.3%)
Slush1 (1.3%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 134 in February 2024 to 139 in February 2025. Toyota became the top vehicle make involved with 24 incidents, surpassing Honda which had 20 incidents in the current period, down from 23. The 26-34 age group continued to be the most represented, increasing from 31 persons in February 2024 to 35 in February 2025, while male persons involved increased from 72 to 86.

Top Vehicle Makes (139 vehicles)

1
TOYOTA24 (17.3%)
14.3%prior 21
2
HONDA20 (14.4%)
-13.0%prior 23
3
FORD19 (13.7%)
5.6%prior 18
4
SUBARU10 (7.2%)
42.9%prior 7
5
CHEVROLET9 (6.5%)
0.0%prior 9
6
NISSAN6 (4.3%)
-50.0%prior 12
7
BMW5 (3.6%)
8
JEEP5 (3.6%)
-16.7%prior 6
9
KIA5 (3.6%)
10
MAZDA4 (2.9%)

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Vehicle unit records

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

Sex Distribution (140 persons with recorded sex)

Male86 (61.4%)
19.4%prior 72
Female54 (38.6%)
-18.2%prior 66

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · Person-level records linked to crash events

Speed Limit Zones

Crashes in 30 mph zones decreased from 21 in February 2024 to 18 in February 2025, while crashes in 40 mph zones increased from 8 to 14. There was also an increase in crashes in 25 mph zones, rising from 9 to 13. All speed zones reported 0 fatal crashes in both periods.

Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-02-01 to 2025-02-28 · 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: 2025-02-01 through 2025-02-28
  • Report generated: June 21, 2026

Data Coverage

  • Reporting period: 2025-02-01 through 2025-02-28 (28 days)
  • Geographic scope: MARLBOROUGH, MA
  • Total crash records analyzed: 75
  • Total persons involved: 158
  • Total vehicles involved: 139

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). "MARLBOROUGH, MA Crash Intelligence Report: February 2025." Published June 21, 2026. Reporting period: 2025-02-01 to 2025-02-28. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/marlborough/february-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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Marlborough, MA Crash Report — February 2025 | ThatCarHitMe.com