Monthly Traffic Safety Analysis

126 CRASHES IN
MARLBOROUGH, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

Total crashes increased from 110 in December 2024 to 126 in December 2025, a 14.5% increase. Despite this rise in overall crashes, total injuries decreased by 33.3%, from 24 to 16. The most notable shift was the decrease in serious injuries, with two reported in the prior period and none in the current period.

126

14.5%was 110

Total Crash Events

0

Persons Killed

16

-33.3%was 24

Persons Injured

8

-27.3%was 11

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 · 2025-12-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crashes in MARLBOROUGH, MA increased by 14.5% year-over-year, rising from 110 crashes in December 2024 to 126 crashes in December 2025. Despite the increase in crash events, the total number of injuries decreased from 24 to 16, representing a 33.3% reduction.

8

Hit-and-Run Crashes — December 2025

-27.3% vs prior (11)

Hit-and-run crashes decreased from 11 in December 2024 to 8 in December 2025. The hit-and-run rate also decreased from 10% to 6.3% year-over-year.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

16

Motorists Injured

Prior: 24-33.3%

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

When Crashes Happen

The peak day for crashes shifted from Friday with 22 crashes in December 2024 to Tuesday with 29 crashes in December 2025. Wednesday also saw a significant increase, rising from 10 crashes to 24 crashes year-over-year. The peak hour for crashes remained in the afternoon, shifting from 5 p.m. with 13 crashes in December 2024 to 4 p.m. with 14 crashes in December 2025.

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

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

Crash Severity Breakdown

Total injuries decreased from 24 in December 2024 to 16 in December 2025, a 33.3% reduction. The prior period reported 2 serious injuries, which were absent in the current period. Minor injuries remained stable, with 12 in December 2024 and 13 in December 2025, while possible injuries decreased from 4 to 2.

Outcome by Severity (Crash Events)

Minor Injury13minor injury crashes10.3%
8.3%prior 12
Possible Injury2possible injury crashes1.6%
-50.0%prior 4
No Injury109no injury crashes86.5%
26.7%prior 86

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

Severity Distribution (Crash Events)

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

Top Contributing Factors

"No improper driving" increased by 8 counts, from 29 to 37, while "Inattention" also increased by 8 counts, from 13 to 21. "Driving too fast for conditions" saw a significant increase in count, rising from 2 in the prior period to 8 in the current period, a 300% increase. Conversely, "Failure to keep in proper lane or running off road" decreased by 4 counts, from 5 to 1.

Officer-Reported Primary Contributing Cause

No improper driving37 (29.4%)27.6%prior 29
Inattention21 (16.7%)61.5%prior 13
Followed too closely13 (10.3%)18.2%prior 11
Failed to yield right of way12 (9.5%)20.0%prior 10
Driving too fast for conditions8 (6.3%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway6 (4.8%)
Other improper action4 (3.2%)
Disregarded traffic signs, signals, road markings3 (2.4%)
History heart/epilepsy/fainting2 (1.6%)
Made an improper turn2 (1.6%)

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

Road & Environmental Conditions

Crashes occurring in "Clear" weather conditions increased from 58 to 74 year-over-year, while crashes during "Snow" conditions decreased from 16 to 9. For road surface conditions, crashes on "Dry" roads increased from 66 to 82, and those on "Ice" increased from 5 to 10. Crashes on "Snow" covered roads decreased from 21 to 13.

Weather

Clear74 (59.2%)
27.6%prior 58
Snow9 (7.2%)
-43.8%prior 16
Rain8 (6.4%)
0.0%prior 8
Clear/Clear8 (6.4%)
0.0%prior 8
Snow/Sleet, hail (freezing rain or drizzle)8 (6.4%)
Cloudy6 (4.8%)
0.0%prior 6
Clear/Cloudy4 (3.2%)
Sleet, hail (freezing rain or drizzle)2 (1.6%)
Clear/Rain1 (0.8%)
Cloudy/Cloudy1 (0.8%)

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

Lighting

Daylight65 (52.0%)
22.6%prior 53
Dark - lighted roadway40 (32.0%)
14.3%prior 35
Dusk10 (8.0%)
100.0%prior 5
Dark - roadway not lighted8 (6.4%)
-33.3%prior 12
Dawn1 (0.8%)
Other1 (0.8%)

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

Road Surface

Dry82 (65.6%)
24.2%prior 66
Wet19 (15.2%)
18.8%prior 16
Snow13 (10.4%)
-38.1%prior 21
Ice10 (8.0%)
100.0%prior 5
Sand, mud, dirt, oil, gravel1 (0.8%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 216 to 232. Among vehicle makes, MAZDA and KIA saw notable increases in involvement, with MAZDA rising from 2 to 11 and KIA from 2 to 10. In terms of age distribution, the 16-20 age group saw a decrease from 31 to 17 persons involved, while the 35-44 age group increased from 35 to 47 persons involved.

Top Vehicle Makes (232 vehicles)

1
TOYOTA38 (16.4%)
8.6%prior 35
2
HONDA30 (12.9%)
0.0%prior 30
3
FORD29 (12.5%)
3.6%prior 28
4
CHEVROLET15 (6.5%)
25.0%prior 12
5
JEEP12 (5.2%)
0.0%prior 12
6
MAZDA11 (4.7%)
7
KIA10 (4.3%)
8
VOLKSWAGEN9 (3.9%)
80.0%prior 5
9
NISSAN9 (3.9%)
-18.2%prior 11
10
HYUNDAI9 (3.9%)
12.5%prior 8

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

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

Sex Distribution (235 persons with recorded sex)

Male149 (63.4%)
8.0%prior 138
Female86 (36.6%)
-3.4%prior 89

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

Speed Limit Zones

Crashes in 35 mph zones increased by 10, from 14 in December 2024 to 24 in December 2025. Conversely, crashes in 30 mph zones decreased by 7, from 37 to 30. No fatal crashes were recorded in any speed zone during either period.

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

Data Coverage

  • Reporting period: 2025-12-01 through 2025-12-31 (31 days)
  • Geographic scope: MARLBOROUGH, MA
  • Total crash records analyzed: 126
  • Total persons involved: 262
  • Total vehicles involved: 232

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