ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · WINCHESTER, MA · 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/massachusetts/winchester/2025-annual-report
Yearly Traffic Safety Analysis
113 CRASHES IN
WINCHESTER, MA
2025
In Winchester, the total number of traffic crashes remained unchanged year-over-year, with 113 incidents recorded in both 2025 and 2024. Despite the stable volume of crashes, the most significant shift was in severity, with one fatal crash occurring in 2025 compared to none in the prior year. Total injuries saw a slight increase from 30 to 31.
113
Total Crash Events
1
Persons Killed
31
▲ 3.3%was 30
Persons Injured
4
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
The overall trend in crash frequency is stable, showing a 0% change with 113 total crashes in both the current and prior year. While the total number of crashes did not change, the severity of outcomes worsened, marked by the appearance of one fatality in 2025. The number of people injured increased slightly from 30 to 31.
4
Hit-and-Run Crashes — 2025
3.5% hit-and-run rate this period vs 0.0% prior. Prior period: 0.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Cyclists Killed
1
Motorists Killed
1
Pedestrians Injured
1
Cyclists Injured
29
Motorists Injured
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. The peak day for crashes moved from Wednesday (24 crashes) in 2024 to a tie between Monday and Tuesday (21 crashes each) in 2025. Similarly, the peak hour for incidents shifted two hours later, from 2 p.m. in 2024 to 4 p.m. in 2025, though both hours recorded 11 crashes in their respective years.
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity increased year-over-year, with the number of fatal crashes rising from zero in 2024 to one in 2025. Consequently, the fatal crash rate increased from 0 to 0.9%. While the overall proportion of crashes involving an injury was stable at roughly 23% for both periods, the composition changed; minor injury crashes increased from 11 to 16, while serious injury crashes dropped from two to zero.
Outcome by Severity (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Top Contributing Factors
The leading contributing factors for crashes shifted year-over-year. Crashes attributed to 'Failed to yield right of way' decreased by 37% in count, from 27 incidents in 2024 to 17 in 2025, moving it from the top-ranked factor to second. Conversely, crashes involving 'Inattention' increased in count from 5 to 9, and those involving 'Distracted' driving tripled from 2 to 6. 'No improper driving' was the most cited factor in 2025 with 30 crashes, up from 24 in the prior year.
Officer-Reported Primary Contributing Cause
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash
Road & Environmental Conditions
Crashes were more likely to occur on dry roads in 2025 compared to 2024, with the count increasing from 83 to 96. Correspondingly, crashes on adverse surfaces like wet, ice, or snow decreased from 29 to 17. The proportion of crashes happening in daylight remained consistent, accounting for 70% of incidents in 2025 and 71% in 2024.
Weather
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The most common vehicle makes involved in collisions, Toyota and Honda, remained the top two in both years. Toyota-involved vehicles increased from 34 to 40, while Honda-involved vehicles decreased from 32 to 24. A notable demographic shift occurred in the age of persons involved in crashes; the 16-20 age group saw its count nearly double from 24 individuals in 2024 to 46 in 2025.
Top Vehicle Makes (200 vehicles)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
14 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (232 persons with recorded sex)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Speed Limit Zones
The vast majority of crashes in both years occurred in 25 mph and 30 mph speed zones, with no significant shift in this distribution. In 2025, 54 crashes occurred in 30 mph zones and 47 in 25 mph zones, comparable to 55 and 53 crashes, respectively, in 2024. The single fatal crash recorded in 2025 took place in a 30 mph zone.
Fatal crashes by zone: 30 mph: 1 of 54 (1.852%)
Source: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly Open Data · 2025-01-01 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: 2025-01-01 through 2025-12-31
- Report generated: June 21, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: WINCHESTER, MA
- Total crash records analyzed: 113
- Total persons involved: 253
- Total vehicles involved: 200
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). "WINCHESTER, MA Crash Intelligence Report: 2025." Published June 21, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Massachusetts Crash Data (MassDOT CDV), Arcgis_yearly Open Data. Available at: https://thatcarhitme.com/crash-data/massachusetts/winchester/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: Massachusetts Crash Data (MassDOT CDV) · Arcgis_yearly
Period: 2025-01-01 – 2025-12-31
Generated: June 21, 2026 · All rights reserved