Monthly Traffic Safety Analysis

15 CRASHES IN
WINCHENDON, MA
FEBRUARY 2025

All metrics benchmarked againstFebruary 2024

WINCHENDON experienced an increase in total crashes from 14 in February 2024 to 15 in February 2025, representing a 7.14% rise. Concurrently, total injuries saw a significant increase, rising from 2 to 6, a 200% change year-over-year. This notable increase in injuries suggests a shift towards more severe outcomes in crashes during the current period.

15

7.1%was 14

Total Crash Events

0

Persons Killed

6

200.0%was 2

Persons Injured

0

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 · 2025-02-01 to 2025-02-28 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, crash activity in WINCHENDON shows an upward trend in February 2025 compared to February 2024. Total crashes increased by 7.14%, from 14 to 15. More significantly, the number of persons injured in crashes rose by 200%, from 2 to 6.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

6

Motorists Injured

Prior: 2200.0%

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 temporal patterns of crashes shifted year-over-year, with the peak day moving from Thursday in February 2024 (6 crashes) to Saturday in February 2025 (4 crashes). Similarly, the peak hour for crashes changed from 7 AM (3 crashes) in the prior period to 7 PM (3 crashes) in the current period. This indicates a shift in high-crash times from morning commute to evening hours and weekends.

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 zero in both February 2024 and February 2025. However, the number of total injuries increased from 2 to 6 year-over-year. Crashes resulting in serious injury (code 'A') increased from 0 in the prior period to 1 in the current period, while minor injury crashes (code 'B') rose from 1 to 3.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes6.7%
Minor Injury3minor injury crashes20%
200.0%prior 1
No Injury11no injury crashes73.3%
-8.3%prior 12

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

Analysis of contributing factors reveals shifts in crash causation. Crashes attributed to 'Driving too fast for conditions' increased significantly from 1 in February 2024 to 4 in February 2025, a 300% increase in count. Conversely, crashes where 'Failed to yield right of way' was a factor decreased from 5 to 1, an 80% reduction in count, causing it to drop from a top factor in the prior period.

Officer-Reported Primary Contributing Cause

No improper driving6 (40%)20.0%prior 5
Driving too fast for conditions4 (26.7%)
Operating vehicle in erratic, reckless, careless, negligent or aggressive manner2 (13.3%)
Disregarded traffic signs, signals, road markings1 (6.7%)
Failed to yield right of way1 (6.7%)-80.0%prior 5
Other improper action1 (6.7%)

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

Road conditions show a notable shift from predominantly dry surfaces in February 2024 (12 crashes) to a more diverse distribution in February 2025, with 4 crashes on snow, 3 on ice, and 3 on wet surfaces. Weather conditions also reflect this change, with 'Clear' conditions accounting for 11 crashes in the prior period but only 4 in the current period, alongside increases in crashes during 'Snow' and 'Cloudy' weather. Daylight crashes increased from 8 to 11, while crashes in dark-lighted conditions decreased from 3 to 2.

Weather

Clear4 (26.7%)
-63.6%prior 11
Clear/Cloudy3 (20.0%)
Snow2 (13.3%)
Cloudy2 (13.3%)
Cloudy/Sleet, hail (freezing rain or drizzle)1 (6.7%)
Cloudy/Snow1 (6.7%)
Sleet, hail (freezing rain or drizzle)1 (6.7%)
Clear/Blowing sand, snow1 (6.7%)

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

Lighting

Daylight11 (73.3%)
37.5%prior 8
Dark - lighted roadway2 (13.3%)
Dark - roadway not lighted1 (6.7%)
Dawn1 (6.7%)

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

Road Surface

Dry4 (26.7%)
-66.7%prior 12
Snow4 (26.7%)
Ice3 (20.0%)
Wet3 (20.0%)
Slush1 (6.7%)

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

Vehicles & Demographics

Top Vehicle Makes (21 vehicles)

1
NISSAN4 (19%)
2
TOYOTA3 (14.3%)
-40.0%prior 5
3
FORD3 (14.3%)
4
DODGE2 (9.5%)
5
HONDA1 (4.8%)
6
HYUNDAI1 (4.8%)
7
INTE1 (4.8%)
8
SUBARU1 (4.8%)
-80.0%prior 5
9
BMW1 (4.8%)
10
VOLVO1 (4.8%)

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

Sex Distribution (25 persons with recorded sex)

Female13 (52.0%)
-7.1%prior 14
Male12 (48.0%)
0.0%prior 12

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

The distribution of crashes across speed zones saw some changes year-over-year. Crashes in 35 mph zones increased from 3 in February 2024 to 4 in February 2025, and crashes in 50 mph zones increased from 2 to 3. There was also an introduction of 1 crash in a 45 mph zone in the current period, which had no crashes in the prior period. No fatalities were recorded in any speed zone during either period.

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: WINCHENDON, MA
  • Total crash records analyzed: 15
  • Total persons involved: 26
  • Total vehicles involved: 21

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: 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/winchendon/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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Winchendon, MA Crash Report — February 2025 | ThatCarHitMe.com