Yearly Traffic Safety Analysis

107 CRASHES IN
STOWE, VT
2025

All metrics benchmarked against2024

Total crashes in Stowe increased by 20.22% year-over-year, rising from 89 in 2024 to 107 in 2025. This period saw a notable 240% increase in crashes occurring during freezing precipitation conditions, from 5 in 2024 to 17 in 2025.

107

20.2%was 89

Total Crash Events

0

Fatal Crashes

14

Injury Crashes

0

Fatal Crash Events

Note: "Fatal Crashes" and "Injury Crashes" count crash events — this source publishes crash-level counts only, not individual persons.

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash activity in Stowe increased, with total crashes rising by 20.22% from 89 in 2024 to 107 in 2025. Despite this increase in crash events, the number of total fatalities remained at 0 in both years, and total injuries held constant at 14.

When Crashes Happen

The peak hour for crashes shifted from 3 p.m. in 2024, with 12 crashes, to 5 p.m. in 2025, with 20 crashes. While Thursday remained the peak day for crashes in both periods, Tuesdays saw a significant increase from 8 crashes in 2024 to 17 crashes in 2025, and Wednesdays rose from 11 to 18 crashes.

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Total fatalities remained at 0 in both 2024 and 2025. The absolute number of injury crashes also remained constant at 14 for both years; however, as a proportion of total crashes, injury crashes decreased from 15.7% in 2024 to 13.1% in 2025.

Outcome by Severity (Crash Events)

Injury14minor injury crashes13.1%
0.0%prior 14
No Injury93no injury crashes86.9%
24.0%prior 75

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Severity derived from reported fatal/injury indicators (no KABCO A/B/C codes)

Severity Distribution (Crash Events)

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring during freezing precipitation conditions saw a substantial increase of 240%, rising from 5 in 2024 to 17 in 2025. Similarly, crashes on snowy roads increased by 266.7%, from 3 to 11, and on wet roads by 350%, from 2 to 9. Crashes occurring in dark conditions also rose by 40.9%, from 22 in 2024 to 31 in 2025.

Weather

Clear27 (47.4%)
50.0%prior 18
Freezing Precipitation17 (29.8%)
240.0%prior 5
Cloudy12 (21.1%)
100.0%prior 6
Rain1 (1.8%)

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight75 (70.8%)
11.9%prior 67
Dark31 (29.2%)
40.9%prior 22

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry20 (43.5%)
0.0%prior 20
Snow11 (23.9%)
Wet9 (19.6%)
Slush5 (10.9%)
Ice1 (2.2%)

Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Vermont Crash Data, accessed programmatically via the Arcgis 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 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: 2025-01-01 through 2025-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: Stowe, VT
  • Total crash records analyzed: 107

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). "Stowe, VT Crash Intelligence Report: 2025." Published July 5, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Vermont Crash Data, Arcgis Open Data. Available at: https://thatcarhitme.com/crash-data/vermont/stowe/2025-annual-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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Stowe, VT Crash Report — 2025 | ThatCarHitMe.com