ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · 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/ohio/statewide/2025-annual-report
Yearly Traffic Safety Analysis
3,590 CRASHES IN
OHIO, OH
2025
In 2025, Wood County recorded 3,590 total vehicle crashes, a 5.7% increase from the 3,397 crashes reported in 2024. Despite the rise in total incidents, the number of fatalities remained constant at 19, and total injuries decreased by 7.2% from 1,062 to 985. The most notable year-over-year shift was the increase in the proportion of crashes resulting in no injuries, which rose from 78.1% to 80.5% of all incidents.
3,590
▲ 5.7%was 3,397
Total Crash Events
19
Persons Killed
985
▼ -7.3%was 1,062
Persons Injured
343
▼ -0.3%was 344
Hit-and-Run Crashes
Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall, the total number of crashes in Wood County trended upward, increasing by 5.7% from 3,397 in 2024 to 3,590 in 2025. In contrast, the number of people injured in these crashes decreased by 7.2%, from 1,062 to 985. The number of fatalities was unchanged at 19 for both years, indicating a stable trend in the most severe outcomes despite an increase in overall crash volume.
343
Hit-and-Run Crashes — 2025
▼ -0.3% vs prior (344)
The number of hit-and-run crashes remained nearly constant, with 343 incidents in 2025 compared to 344 in 2024. However, due to the overall increase in total crashes, the hit-and-run rate trended downward. The rate of hit-and-runs as a percentage of all crashes decreased from 10.1% in the prior year to 9.6% in the current year.
Vulnerable Road User Casualties
1
Pedestrians Killed
18
Motorists Killed
21
Pedestrians Injured
964
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv 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 temporal patterns of crashes showed a notable shift in the peak day of the week, moving from Friday (631 crashes) in 2024 to Wednesday (582 crashes) in 2025. The peak hour for collisions remained the 5 p.m. hour in both periods, although the number of crashes during this hour saw a slight decrease from 306 to 278. This suggests a change in weekly traffic patterns but consistency in the daily evening commute peak.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
The severity of crashes shifted slightly between the two periods, with the proportion of fatal crashes decreasing from 0.6% to 0.5% of the total, though the absolute number remained at 19. The share of crashes resulting in minor or possible injuries also declined, from a combined 19.2% in 2024 to 16.8% in 2025. Consequently, the proportion of crashes with no injuries increased from 78.1% to 80.5%, accounting for the overall rise in crashes alongside a decrease in total injuries.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record
Road & Environmental Conditions
Analysis of crash conditions reveals a significant change in the role of adverse weather. While the proportion of crashes in daylight versus dark conditions remained stable, the share of crashes occurring in snow increased from 5.7% in 2024 to 8.6% in 2025. This was mirrored in road surface conditions, where crashes on snow or ice accounted for 11.8% of all incidents, nearly double the 6.2% reported in the prior year. Conversely, crashes on wet roads and in rainy weather decreased as a percentage of the total.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field
Vehicles & Demographics
The demographics of persons involved in crashes saw a shift, with the 16-20 age group's representation increasing from 13.0% of all persons in 2024 to 14.3% in 2025. The top four vehicle makes involved in crashes—Ford, Chevrolet, Honda, and Toyota—remained consistent across both years, with their counts increasing in line with the overall rise in crash volume. Jeep replaced Dodge as the fifth most common make, with 333 vehicles involved in 2025 compared to 278 in the previous year.
Top Vehicle Makes (5,953 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
295 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (7,510 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events
Data Sources & Methodology
Primary Data Source
All crash data in this report is sourced from Ohio Crash Data (ODOT TIMS), accessed programmatically via the Csv 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: Csv 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 6, 2026
Data Coverage
- Reporting period: 2025-01-01 through 2025-12-31 (365 days)
- Geographic scope: ohio, OH
- Total crash records analyzed: 3,590
- Total persons involved: 7,762
- Total vehicles involved: 5,953
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). "ohio, OH Crash Intelligence Report: 2025." Published July 6, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/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: Ohio Crash Data (ODOT TIMS) · Csv
Period: 2025-01-01 – 2025-12-31
Generated: July 6, 2026 · All rights reserved