Monthly Traffic Safety Analysis

35 CRASHES IN
NORTHBOROUGH, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

Total crashes increased from 34 in December 2024 to 35 in December 2025, a rise of 2.9%. A notable shift was observed in DUI-related crashes, which doubled from 2 in the prior period to 4 in the current period.

35

2.9%was 34

Total Crash Events

0

Persons Killed

5

-16.7%was 6

Persons Injured

1

-66.7%was 3

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. 1 crash with unreported severity is 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, the total number of crashes saw a slight increase year-over-year, rising by 1 crash from 34 to 35, representing a 2.9% change. This indicates a relatively stable trend in total crash occurrences for the month of December.

1

Hit-and-Run Crashes — December 2025

-66.7% vs prior (3)

Hit-and-run crashes decreased from 3 in December 2024 to 1 in December 2025. The hit-and-run rate also declined from 8.8% in the prior period to 2.9% in the current period, representing a decrease of 5.9 percentage points.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

5

Motorists Injured

Prior: 6-16.7%

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 Thursday in December 2024 (10 crashes) to Tuesday in December 2025 (11 crashes). Similarly, the peak hour for crashes changed from 8 AM in the prior period (7 crashes) to 2 PM in the current period (5 crashes), indicating a shift in the most frequent times for crash incidents.

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 slightly from 6 in December 2024 to 5 in December 2025. The proportion of possible injury crashes increased from 5.9% (2 crashes) to 8.6% (3 crashes), while minor injury crashes remained constant at 2 incidents in both periods. No fatal crashes or fatalities were recorded in either December 2024 or December 2025.

Outcome by Severity (Crash Events)

Minor Injury2minor injury crashes5.7%
0.0%prior 2
Possible Injury3possible injury crashes8.6%
50.0%prior 2
No Injury29no injury crashes82.9%
0.0%prior 29

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

Crashes involving "Driving too fast for conditions" increased by 3, from 4 in December 2024 to 7 in December 2025, a 75% increase in count. Crashes attributed to "Followed too closely" also rose by 2, from 4 to 6, a 50% increase in count. Conversely, "No improper driving" was a top contributing factor in 5 crashes in the prior period but was not among the top factors in the current period.

Officer-Reported Primary Contributing Cause

Failure to keep in proper lane or running off road7 (20%)16.7%prior 6
Driving too fast for conditions7 (20%)
Followed too closely6 (17.1%)
Failed to yield right of way5 (14.3%)
Disregarded traffic signs, signals, road markings3 (8.6%)
Exceeded authorized speed limit2 (5.7%)
Physical impairment1 (2.9%)
Fatigued/asleep1 (2.9%)
Inattention1 (2.9%)
Operating defective equipment1 (2.9%)

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 6 in December 2024 to 11 in December 2025, while crashes in "Rain/Rain" conditions decreased from 3 to 1. Crashes on "Wet" road surfaces decreased by 3, from 8 to 5, and crashes on "Ice" decreased from 2 to 1. Notably, "Slush" appeared as a road surface condition in 4 crashes in December 2025, whereas it was not reported in the prior period.

Weather

Clear/Clear14 (40.0%)
7.7%prior 13
Clear11 (31.4%)
83.3%prior 6
Snow5 (14.3%)
Fog, smog, smoke1 (2.9%)
Rain/Rain1 (2.9%)
Rain/Sleet, hail (freezing rain or drizzle)1 (2.9%)
Rain/Snow1 (2.9%)
Cloudy1 (2.9%)

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

Lighting

Daylight24 (68.6%)
20.0%prior 20
Dark - lighted roadway5 (14.3%)
Dark - roadway not lighted5 (14.3%)
-28.6%prior 7
Dawn1 (2.9%)

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

Road Surface

Dry20 (57.1%)
5.3%prior 19
Wet5 (14.3%)
-37.5%prior 8
Slush4 (11.4%)
Snow4 (11.4%)
-20.0%prior 5
Ice1 (2.9%)
Sand, mud, dirt, oil, gravel1 (2.9%)

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 decreased from 59 in December 2024 to 56 in December 2025. Honda vehicles involved in crashes saw a significant increase, rising from 4 in the prior period to 12 in the current period. Conversely, Toyota vehicles involved in crashes decreased from 12 to 10.

Top Vehicle Makes (56 vehicles)

1
HONDA12 (21.4%)
2
TOYOTA10 (17.9%)
-16.7%prior 12
3
FORD8 (14.3%)
60.0%prior 5
4
NISSAN5 (8.9%)
5
HYUNDAI3 (5.4%)
6
CHEVROLET3 (5.4%)
7
GMC2 (3.6%)
8
SUBARU2 (3.6%)
9
MAZDA2 (3.6%)
10
JEEP2 (3.6%)

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

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

Sex Distribution (66 persons with recorded sex)

Male37 (56.1%)
-15.9%prior 44
Female29 (43.9%)
38.1%prior 21

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 occurring in 25 mph speed zones increased from 2 in December 2024 to 6 in December 2025, representing a 200% increase. Crashes in 30 mph zones decreased from 13 to 6, while those in 35 mph zones increased from 3 to 7, a 133.3% increase. No fatal crashes were recorded across any speed limit zone in 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: NORTHBOROUGH, MA
  • Total crash records analyzed: 35
  • Total persons involved: 67
  • Total vehicles involved: 56

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). "NORTHBOROUGH, 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/northborough/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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Northborough, MA Crash Report — December 2025 | ThatCarHitMe.com