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
5,616 CRASHES IN
OHIO, OH
2025
In Mahoning County, total traffic crashes increased by 5.3% from 5,336 in 2024 to 5,616 in 2025. Despite the rise in overall collisions, the number of people injured decreased by 3.3% from 2,016 to 1,950. The most notable year-over-year change was the number of pedestrian fatalities, which fell by 50% from 6 in the prior year to 3 in the current year.
5,616
▲ 5.2%was 5,336
Total Crash Events
18
Persons Killed
1,950
▼ -3.3%was 2,016
Persons Injured
725
▲ 4.8%was 692
Hit-and-Run Crashes
Note: "Persons Killed" (18) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) 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, traffic crashes in Mahoning County are on an upward trend, increasing by 280 incidents (5.3%) from 2024 to 2025. However, the outcomes of these crashes have become slightly less severe. While total fatalities remained constant at 18, the number of total injuries declined from 2,016 to 1,950.
725
Hit-and-Run Crashes — 2025
▲ 4.8% vs prior (692)
The number of hit-and-run crashes increased from 692 in the prior year to 725 in the current year. However, because total crashes also increased, the hit-and-run rate as a percentage of all crashes remained nearly flat. The rate showed a slight downward trend, decreasing from 13.0% in the prior period to 12.9% in the current period.
Vulnerable Road User Casualties
3
Pedestrians Killed
15
Motorists Killed
34
Pedestrians Injured
1,916
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 shift in the peak day of the week. In the current period, Wednesday was the most frequent day for crashes with 902 incidents, a change from the prior period when Friday was the peak day with 988 crashes. The peak hour for collisions remained consistent year-over-year, with the 3 p.m. hour seeing the highest volume in both periods (476 crashes in 2025 and 446 in 2024).
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 showed a slight decrease year-over-year. The proportion of crashes involving any injury (Serious, Minor, or Possible) fell from 25.2% in the prior period to 23.6% in the current period. Similarly, the fatal crash rate saw a marginal reduction from 0.32% to 0.30%, even as the absolute number of fatal crashes and total fatalities remained unchanged at 17 and 18, respectively.
Severity is per crash event (most severe injury). 17 fatal crash events resulted in 18 persons killed.
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
The distribution of crashes across different conditions remained largely stable, with most incidents in both years occurring in daylight (66.7% vs 64.6%) and on dry roads (69.7% vs 71.8%). There was a notable shift in crashes occurring during specific adverse weather. The proportion of crashes in snow conditions increased from 5.8% of all crashes in the prior year to 8.2% in the current year, while the share of crashes in rain decreased from 11.8% to 9.8%.
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 top two vehicle makes involved in crashes, Chevrolet and Ford, maintained their rankings with increased counts year-over-year. Honda (608 vehicles) replaced Toyota (584 vehicles) as the third most-involved make compared to the prior period. Regarding persons involved, the 26-34 age group remained the largest cohort in both periods. However, the 65+ age group saw its representation increase, becoming the second-largest group of people involved in crashes in the current year with 1,881 individuals.
Top Vehicle Makes (9,894 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records
723 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (12,670 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: 5,616
- Total persons involved: 13,139
- Total vehicles involved: 9,894
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