ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · OCTOBER 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/october-2025-report
Monthly Traffic Safety Analysis
314 CRASHES IN
OHIO, OH
OCTOBER 2025
In October 2025, Allen County recorded 314 vehicle crashes, a 2% increase from the 308 crashes documented in October 2024. While total injuries decreased from 102 to 67, the most notable year-over-year change was the occurrence of 3 fatalities in the current period, compared to zero in the prior year.
314
▲ 1.9%was 308
Total Crash Events
3
Persons Killed
67
▼ -34.3%was 102
Persons Injured
28
▼ -33.3%was 42
Hit-and-Run Crashes
Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Overall crash volume in Allen County saw a minor increase, rising from 308 incidents in October 2024 to 314 in October 2025. This period saw a mixed trend in outcomes, with total reported injuries falling by 34.3% from 102 to 67. However, this was contrasted by a rise in fatalities from zero to 3.
28
Hit-and-Run Crashes — October 2025
▼ -33.3% vs prior (42)
Hit-and-run incidents showed a downward trend in October 2025. The total count of such crashes fell to 28 from 42 in October 2024, a 33.3% decrease. Consequently, the hit-and-run rate, as a percentage of all crashes, dropped from 13.6% in the prior year to 8.9% in the current period.
Vulnerable Road User Casualties
1
Pedestrians Killed
2
Motorists Killed
2
Pedestrians Injured
65
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The peak time for crashes shifted year-over-year. In October 2025, Friday was the busiest day with 60 crashes and the 2 p.m. hour was the peak time with 27 crashes. This contrasts with October 2024, when Thursday was the peak day with 65 crashes and the 5 p.m. hour was the peak time with 27 crashes.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
October 2025 saw a significant shift in crash severity, with 2 fatal crashes resulting in 3 deaths, whereas none were recorded in October 2024. Despite this, the proportion of crashes involving any level of injury decreased from 23.1% to 15.3% year-over-year. Correspondingly, crashes with no reported injuries increased, making up 84.1% of all incidents compared to 76.9% in the previous year.
Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes in adverse conditions showed a proportional increase in October 2025 compared to the previous year. The share of crashes on wet roads rose from 8.4% to 17.2%, and incidents during rain increased from 3.6% to 12.1%. Additionally, crashes in daylight decreased as a percentage of the total from 59.1% to 54.1%, while crashes in dark, unlighted conditions increased from 23.4% to 29.9%.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes shifted slightly, with Chevrolet (83) and Ford (81) leading in October 2025, reversing their positions from October 2024 when Ford (89) was first. The age distribution of persons involved in crashes remained relatively stable, with the 26-34 age group being one of the largest in both periods (103 in 2025 vs. 102 in 2024). The number of persons in the 16-20 age group increased from 97 to 102.
Top Vehicle Makes (505 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records
24 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (631 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
- Report generated: July 6, 2026
Data Coverage
- Reporting period: 2025-10-01 through 2025-10-31 (31 days)
- Geographic scope: ohio, OH
- Total crash records analyzed: 314
- Total persons involved: 651
- Total vehicles involved: 505
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: October 2025." Published July 6, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/october-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
ThatCarHitMe.com · An Injuria.ai Company
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Ohio Crash Data (ODOT TIMS) · Csv
Period: 2025-10-01 – 2025-10-31
Generated: July 6, 2026 · All rights reserved