ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · MAY 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/may-2025-report
Monthly Traffic Safety Analysis
271 CRASHES IN
OHIO, OH
MAY 2025
In May 2025, Allen County recorded 271 traffic crashes, a 16.3% increase from the 233 crashes in May 2024. While total collisions and injuries (93, up from 85) rose, the most significant year-over-year change was a reduction in fatalities from two to zero.
271
▲ 16.3%was 233
Total Crash Events
0
▼ -100.0%was 2
Persons Killed
93
▲ 9.4%was 85
Persons Injured
50
▲ 22.0%was 41
Hit-and-Run Crashes
Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Crash data for May shows an upward trend in collisions compared to the previous year, with total crashes rising by 16.3% from 233 to 271. This increase was accompanied by a 9.4% rise in persons injured, from 85 to 93. However, the period saw a positive development with zero traffic fatalities, compared to two in the same month last year.
50
Hit-and-Run Crashes — May 2025
▲ 22.0% vs prior (41)
Hit-and-run incidents increased in both count and as a percentage of total crashes. The number of hit-and-run crashes rose from 41 in May 2024 to 50 in May 2025. This represents a slight increase in the hit-and-run rate from 17.6% to 18.5% of all collisions.
Vulnerable Road User Casualties
0
Pedestrians Killed
0
Motorists Killed
2
Pedestrians Injured
91
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · 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 some shifts year-over-year. While Friday remained the peak day for crashes in both May 2025 and May 2024 with 45 incidents each, the peak hour moved later in the day from 1 p.m. (19 crashes) in the prior year to 3 p.m. (26 crashes) in the current period. Weekday afternoons continue to be the time with the highest concentration of collisions.
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
While total crashes increased, their overall severity profile shifted. May 2025 saw no fatal crashes, a notable improvement from the two fatal crashes recorded in May 2024. The proportion of crashes resulting in any injury decreased from 26.2% to 22.5% year-over-year, and crashes with no injuries increased from 73.0% to 77.5% of the total.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record
Road & Environmental Conditions
Crashes during adverse conditions increased compared to the previous year. The number of collisions on wet roads more than doubled, from 34 to 70, representing 25.8% of all crashes in May 2025 versus 14.6% in May 2024. Similarly, crashes in the rain rose from 24 to 49, and collisions in dark, unlighted conditions increased from 25 to 42.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field
Vehicles & Demographics
The top vehicle makes involved in crashes shifted, with Chevrolet (80 vehicles) overtaking Ford (76 vehicles) for the highest count, a reversal from the prior year when Ford led with 86 vehicles to Chevrolet's 59. Among persons involved in crashes, the 16-20 age group saw the largest increase in representation, growing from 82 individuals to 89, making it the most frequently involved age bracket in May 2025.
Top Vehicle Makes (468 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records
44 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (569 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
- Report generated: July 6, 2026
Data Coverage
- Reporting period: 2025-05-01 through 2025-05-31 (31 days)
- Geographic scope: ohio, OH
- Total crash records analyzed: 271
- Total persons involved: 610
- Total vehicles involved: 468
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: May 2025." Published July 6, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/may-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: 2025-05-01 – 2025-05-31
Generated: July 6, 2026 · All rights reserved