Yearly Traffic Safety Analysis

1,167 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Defiance County recorded 1,167 total vehicle crashes, a 3.6% increase from the 1,127 crashes reported in 2024. While total crashes rose, reported injuries decreased from 325 to 296, and fatalities remained unchanged at 6. The most significant year-over-year change was a 60% increase in crashes involving a driver under the influence (DUI), which rose from 30 incidents in 2024 to 48 in 2025.

1,167

▲ 3.5%was 1,127

Total Crash Events

Persons Killed

296

▼ -8.9%was 325

Persons Injured

▲ 8.3%was 60

Hit-and-Run Crashes

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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 Defiance County trended upward, increasing by 3.6% from 1,127 in 2024 to 1,167 in 2025. Despite this rise in total collisions, the number of people injured fell by 8.9% from 325 to 296. The number of fatalities remained stable at 6 in both periods.

Hit-and-Run Crashes — 2025

▲ 8.3% vs prior (60)

Hit-and-run incidents increased in both count and rate compared to the previous year. The number of hit-and-run crashes rose from 60 in 2024 to 65 in 2025. This corresponds to an increase in the hit-and-run rate, which climbed from 5.3% of all crashes in 2024 to 5.6% in 2025.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 0→0.0%

Motorists Killed

Prior: 6→0.0%

Pedestrians Injured

Prior: 3→0.0%

293

Motorists Injured

Prior: 322↓-9.0%

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 year-over-year. While Friday remained the peak day for crashes in both 2025 (191 crashes) and 2024 (186 crashes), the peak hour for incidents shifted significantly. In 2025, the 7 a.m. hour saw the most crashes with 106 incidents, a stark change from 2024 when the 4 p.m. hour was the peak with 82 crashes.

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. The number of fatal crashes (6) and total fatalities (6) was identical year-over-year, resulting in a marginal decrease in the fatal crash rate from 0.53% to 0.51% due to the higher total crash volume. The proportion of crashes resulting in no injury increased from 81.0% in 2024 to 82.3% in 2025. Correspondingly, crashes involving serious injuries decreased from 1.7% to 1.5% of all crashes, and minor injury crashes fell from 11.4% to 9.8%.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.5%

→0.0%prior 6

Serious Injury17serious injury crashes1.5%

↓-10.5%prior 19

Minor Injury114minor injury crashes9.8%

↓-10.9%prior 128

Possible Injury69possible injury crashes5.9%

↑13.1%prior 61

No Injury961no injury crashes82.3%

↑5.3%prior 913

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

Year-over-year, there was a significant increase in crashes occurring under adverse conditions. Collisions on roads with snow or ice increased from 57 in 2024 to 101 in 2025. Similarly, crashes during dawn or dusk lighting conditions rose from 74 to 111. Despite these increases, the majority of crashes in both years occurred in clear weather (65.0% in 2025 vs. 63.8% in 2024) and on dry roads (79.3% in 2025 vs. 79.7% in 2024).

Weather

Clear758 (65.0%)

↑5.4%prior 719

Cloudy249 (21.3%)

↓-5.0%prior 262

Snow67 (5.7%)

↑26.4%prior 53

Rain62 (5.3%)

↓-11.4%prior 70

Other/Unknown15 (1.3%)

Fog; Smog; Smoke7 (0.6%)

↓-56.3%prior 16

Freezing Rain or Freezing Drizzle4 (0.3%)

Sleet; Hail3 (0.3%)

Blowing Sand; Soil; Dirt; Snow2 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight616 (52.8%)

↑0.2%prior 615

Dark - Roadway Not Lighted359 (30.8%)

↑3.5%prior 347

Dawn/Dusk111 (9.5%)

↑50.0%prior 74

Dark - Lighted Roadway75 (6.4%)

↓-1.3%prior 76

Dark - Unknown Roadway Lighting4 (0.3%)

↓-60.0%prior 10

Other/Unknown2 (0.2%)

↓-60.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry925 (79.3%)

↑3.0%prior 898

Wet136 (11.7%)

↓-17.1%prior 164

Snow63 (5.4%)

↑61.5%prior 39

Ice38 (3.3%)

↑111.1%prior 18

Slush4 (0.3%)

Other/Unknown1 (0.1%)

↓-80.0%prior 5

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The types of vehicles involved in crashes saw some shifts between 2024 and 2025. Sport Utility Vehicles involved in crashes increased from 489 to 532, while Passenger Cars decreased from 646 to 610. The top vehicle makes remained consistent, with Chevrolet and Ford leading in both years. Among persons involved in crashes, the age distributions were largely stable, with no significant proportional shifts across age groups year-over-year.

Top Vehicle Makes (1,712 vehicles)

CHEVROLET472 (27.6%)

↑4.4%prior 452

FORD265 (15.5%)

↓-0.4%prior 266

GMC125 (7.3%)

↑9.6%prior 114

DODGE95 (5.5%)

↓-18.8%prior 117

HONDA77 (4.5%)

↑18.5%prior 65

BUICK71 (4.1%)

↓-6.6%prior 76

JEEP66 (3.9%)

↑3.1%prior 64

CHRYSLER64 (3.7%)

↑23.1%prior 52

TOYOTA59 (3.4%)

↑40.5%prior 42

FREIGHTLINER33 (1.9%)

↑73.7%prior 19

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

58 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (2,166 persons with recorded sex)

Male1,171 (54.1%)

↑7.4%prior 1,090

Female995 (45.9%)

↑6.8%prior 932

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 5, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: ohio, OH
Total crash records analyzed: 1,167
Total persons involved: 2,211
Total vehicles involved: 1,712

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 5, 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

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1,167 CRASHES INOHIO, OH2025