Monthly Traffic Safety Analysis

26 CRASHES IN
WINCHENDON, MA
DECEMBER 2025

All metrics benchmarked againstDecember 2024

WINCHENDON experienced a decrease in total crashes, from 33 in December 2024 to 26 in December 2025, representing a 21.21% reduction. The most notable year-over-year shift was the absence of fatalities in December 2025, compared to one fatality recorded in December 2024.

26

▼ -21.2%was 33

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

5

Persons Injured

0

▼ -100.0%was 1

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

Trend Summary

Overall, crash incidents in WINCHENDON showed a declining trend year-over-year, with total crashes decreasing by 21.21% from 33 in December 2024 to 26 in December 2025. Fatalities also decreased, from 1 to 0, while the total number of injuries remained stable at 5.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

5

Motorists Injured

Prior: 5→0.0%

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, which recorded 8 incidents, to Tuesday in December 2025 with 6 incidents. Similarly, the peak hour for crashes moved from 6 p.m. with 6 incidents in December 2024 to 2 p.m. with 4 incidents 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

Fatalities decreased from 1 in December 2024 to 0 in December 2025, indicating an improvement in crash outcomes. The total number of injuries remained consistent at 5 across both periods. The proportion of crashes resulting in no injuries was nearly identical, at 84.8% in December 2024 and 84.6% in December 2025.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes3.8%
Minor Injury3minor injury crashes11.5%
→0.0%prior 3
No Injury22no injury crashes84.6%
↓-21.4%prior 28

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 attributed to 'No improper driving' decreased from 11 in December 2024 to 9 in December 2025, an 18.18% reduction in count. Conversely, 'Inattention' as a contributing factor saw an increase in count from 3 to 5 crashes, a 66.67% rise. Several factors, including 'Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway', 'Failed to yield right of way', 'Driving too fast for conditions', and 'Operating vehicle in erratic, reckless, careless, negligent or aggressive manner', each decreased by 2 crashes year-over-year.

Officer-Reported Primary Contributing Cause

No improper driving9 (34.6%)↓-18.2%prior 11
Inattention5 (19.2%)
Swerving or avoiding due to wind, slippery surface, vehicle, object, vulnerable user in roadway2 (7.7%)
Failed to yield right of way1 (3.8%)
Exceeded authorized speed limit1 (3.8%)
Failure to keep in proper lane or running off road1 (3.8%)
Visibility obstructed1 (3.8%)
Driving too fast for conditions1 (3.8%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner1 (3.8%)

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 'Snow' weather conditions increased from 2 in December 2024 to 7 in December 2025. Correspondingly, incidents on 'Snow' road surfaces rose from 6 to 10 over the same period. There was a notable decrease in crashes on 'Dry' road surfaces, which fell from 12 to 7 year-over-year.

Weather

Clear11 (42.3%)
↓-15.4%prior 13
Snow7 (26.9%)
Cloudy3 (11.5%)
↓-57.1%prior 7
Clear/Cloudy2 (7.7%)
Cloudy/Snow1 (3.8%)
Severe crosswinds1 (3.8%)
Snow/Cloudy1 (3.8%)

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

Lighting

Daylight13 (50.0%)
↓-27.8%prior 18
Dark - lighted roadway7 (26.9%)
↓-30.0%prior 10
Dark - roadway not lighted4 (15.4%)
Dawn2 (7.7%)

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

Road Surface

Snow10 (38.5%)
↑66.7%prior 6
Wet8 (30.8%)
↓-27.3%prior 11
Dry7 (26.9%)
↓-41.7%prior 12
Ice1 (3.8%)

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

Vehicles & Demographics

Top Vehicle Makes (41 vehicles)

1
FORD11 (26.8%)
↓-8.3%prior 12
2
NISSAN4 (9.8%)
3
CHEVROLET4 (9.8%)
4
SUBARU4 (9.8%)
↓-20.0%prior 5
5
HONDA3 (7.3%)
6
TOYOTA3 (7.3%)
↓-62.5%prior 8
7
KIA2 (4.9%)
8
HYUNDAI2 (4.9%)
9
LEXUS2 (4.9%)
10
MITS1 (2.4%)

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

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

Sex Distribution (42 persons with recorded sex)

Male23 (54.8%)
↓-34.3%prior 35
Female19 (45.2%)
↓-29.6%prior 27

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 the 30 MPH speed zone significantly decreased from 13 in December 2024 to 6 in December 2025. Conversely, crashes in the 50 MPH speed zone saw a slight increase from 3 to 4 incidents. Notably, the single fatality in December 2024 occurred in a 40 MPH zone, while December 2025 recorded no fatalities across all speed zones.

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: WINCHENDON, MA
  • Total crash records analyzed: 26
  • Total persons involved: 47
  • Total vehicles involved: 41

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). "WINCHENDON, 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/winchendon/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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Winchendon, MA Crash Report — December 2025 | ThatCarHitMe.com