ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · SPRINGFIELD, VT · 2025
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/vermont/springfield/2025-annual-report
Yearly Traffic Safety Analysis
211 CRASHES IN
SPRINGFIELD, VT
2025
Total crashes in 2025 were 211, a slight increase from 203 crashes in 2024, representing a 3.94% rise. The most notable year-over-year shift was the complete elimination of crash fatalities, decreasing from 1 in 2024 to 0 in 2025. Additionally, total injuries decreased by 20%, falling from 40 in 2024 to 32 in 2025.
211
▲ 3.9%was 203
Total Crash Events
0
▼ -100.0%was 1
Fatal Crashes
32
▼ -20.0%was 40
Injury Crashes
0
▼ -100.0%was 1
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
The overall trend indicates a slight increase in total crashes year-over-year, rising by 8 incidents from 203 in 2024 to 211 in 2025. Despite this increase in total crashes, there was a positive trend in crash severity, with a 100% reduction in fatalities and a 20% decrease in total injuries.
When Crashes Happen
The peak day for crashes shifted from Friday with 35 crashes in 2024 to Thursday with 40 crashes in 2025. The peak hour remained 12p in both years, though the number of crashes during this hour slightly decreased from 23 in 2024 to 22 in 2025. Monthly crash distribution also varied, with 2025 showing a high of 25 crashes in February and a low of 11 in August, compared to 2024's high of 23 in April and low of 12 in December.
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
Fatal crashes were eliminated in 2025, dropping from 1 fatal crash (0.5% of total crashes) in 2024 to 0 in 2025. Injury crashes also decreased, falling from 40 incidents (19.7% of total crashes) in 2024 to 32 incidents (15.2% of total crashes) in 2025. Consequently, the proportion of crashes resulting in no injuries increased from 79.8% in 2024 to 84.8% in 2025.
Outcome by Severity (Crash Events)
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 in clear weather conditions decreased from 130 in 2024 to 118 in 2025, while crashes in cloudy conditions increased from 31 to 40. Crashes on dry road surfaces slightly decreased from 143 in 2024 to 138 in 2025, but crashes on snow-covered roads significantly increased from 14 to 23. Daylight crashes rose from 152 in 2024 to 167 in 2025, whereas crashes in dark conditions decreased from 50 to 44.
Weather
Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Vermont Crash Data · Arcgis Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
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: Springfield, VT
- Total crash records analyzed: 211
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). "Springfield, 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/springfield/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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Vermont Crash Data · Arcgis
Period: 2025-01-01 – 2025-12-31
Generated: July 5, 2026 · All rights reserved