Yearly Traffic Safety Analysis

11,356 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Lucas County recorded 11,356 total traffic crashes, a slight decrease of 0.6% from the 11,426 crashes reported in 2024. Despite the minor drop in overall collisions, the number of fatalities increased significantly, rising 25% from 36 in the prior year to 45 in the current year. This increase in fatalities occurred within a larger context of fewer total injuries and a stable overall crash volume.

11,356

▼ -0.6%was 11,426

Total Crash Events

▲ 25.0%was 36

Persons Killed

4,034

▼ -3.9%was 4,197

Persons Injured

2,706

▲ 0.8%was 2,684

Hit-and-Run Crashes

Note: "Persons Killed" (45) counts individual fatalities across all crash events. "Fatal" in the severity table below (41) 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 crash volume in Lucas County remained relatively stable year-over-year, with a minor 0.6% decrease from 11,426 crashes in 2024 to 11,356 in 2025. While total crashes saw a slight decline, the number of resulting fatalities rose by 25%, from 36 to 45. Conversely, the total number of injuries decreased by 3.9% over the same period.

2,706

Hit-and-Run Crashes — 2025

▲ 0.8% vs prior (2,684)

Hit-and-run incidents saw a slight increase in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes rose from 2,684 in 2024 to 2,706 in 2025. Consequently, the hit-and-run rate edged up from 23.5% to 23.8% of all crashes, indicating a marginal upward trend for this crash type.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 5↑140.0%

Motorists Killed

Prior: 31↑6.5%

133

Pedestrians Injured

Prior: 120↑10.8%

3,901

Motorists Injured

Prior: 4,077↓-4.3%

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 some year-over-year shifts. The peak day for collisions moved from Friday (1,958 crashes) in 2024 to Wednesday (1,785 crashes) in 2025. The afternoon rush hour remained the most frequent time for crashes, with the 3 PM hour being the peak in both years, although the number of crashes during this hour decreased from 1,024 to 983.

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

While the total number of crashes remained stable, their severity distribution shifted. The number of fatal crashes increased from 30 in 2024 to 41 in 2025, raising the fatal crash rate from 0.26% to 0.36%. Conversely, crashes resulting in injuries all saw decreases, with serious injury crashes dropping from 210 to 206 and minor injury crashes falling from 1,454 to 1,369.

Severity is per crash event (most severe injury). 41 fatal crash events resulted in 45 persons killed.

Outcome by Severity (Crash Events)

Fatal41fatal crashes0.4%

↑36.7%prior 30

Serious Injury206serious injury crashes1.8%

↓-1.9%prior 210

Minor Injury1,369minor injury crashes12.1%

↓-5.8%prior 1,454

Possible Injury1,127possible injury crashes9.9%

↓-3.9%prior 1,173

No Injury8,613no injury crashes75.8%

↑0.6%prior 8,559

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 by environmental conditions remained largely consistent year-over-year, with the majority occurring in clear weather (7,692 in 2025 vs. 7,671 in 2024) and during daylight hours (7,555 vs. 7,656). There was a notable shift in crashes related to precipitation, with snow-related incidents increasing from 371 to 573, while rain-related crashes decreased from 1,170 to 926. This change is mirrored in road surface conditions, where crashes on snowy surfaces rose from 247 to 507.

Weather

Clear7,692 (67.7%)

↑0.3%prior 7,671

Cloudy1,891 (16.7%)

↓-5.1%prior 1,993

Rain926 (8.2%)

↓-20.9%prior 1,170

Snow573 (5.0%)

↑54.4%prior 371

Other/Unknown136 (1.2%)

↑11.5%prior 122

Freezing Rain or Freezing Drizzle66 (0.6%)

↑127.6%prior 29

Sleet; Hail30 (0.3%)

↑233.3%prior 9

Fog; Smog; Smoke29 (0.3%)

↓-50.0%prior 58

Blowing Sand; Soil; Dirt; Snow9 (0.1%)

Severe Crosswinds4 (0.0%)

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

Lighting

Daylight7,555 (66.5%)

↓-1.3%prior 7,656

Dark - Lighted Roadway2,504 (22.1%)

↑3.9%prior 2,409

Dawn/Dusk687 (6.0%)

↑1.5%prior 677

Dark - Roadway Not Lighted448 (3.9%)

↓-9.1%prior 493

Other/Unknown86 (0.8%)

↑8.9%prior 79

Dark - Unknown Roadway Lighting76 (0.7%)

↓-32.1%prior 112

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

Road Surface

Dry8,626 (76.0%)

↓-1.9%prior 8,797

Wet1,873 (16.5%)

↓-9.4%prior 2,068

Snow507 (4.5%)

↑105.3%prior 247

Ice211 (1.9%)

↑8.2%prior 195

Other/Unknown112 (1.0%)

↑7.7%prior 104

Slush19 (0.2%)

Sand; Mud; Dirt; Oil; Gravel5 (0.0%)

↓-54.5%prior 11

Water (Standing; Moving)3 (0.0%)

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

Vehicles & Demographics

The top vehicle makes involved in collisions were consistent across both years, with Chevrolet and Ford leading in both periods. In 2025, Chevrolet was involved in 3,442 crashes and Ford in 3,185, compared to 3,366 and 3,262 respectively in 2024. The demographic profile of individuals involved in crashes also remained stable, with the proportional representation of different age groups showing no significant year-over-year shifts.

Top Vehicle Makes (21,702 vehicles)

CHEVROLET3,442 (15.9%)

↑2.3%prior 3,366

FORD3,185 (14.7%)

↓-2.4%prior 3,262

JEEP1,613 (7.4%)

↑6.5%prior 1,514

DODGE1,560 (7.2%)

↓-7.4%prior 1,685

HONDA1,415 (6.5%)

↓-1.9%prior 1,442

TOYOTA1,111 (5.1%)

↑3.0%prior 1,079

KIA819 (3.8%)

↓-3.0%prior 844

CHRYSLER776 (3.6%)

↓-0.1%prior 777

GMC739 (3.4%)

↑2.2%prior 723

NISSAN724 (3.3%)

↑8.1%prior 670

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

2,745 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (25,302 persons with recorded sex)

Male13,220 (52.2%)

↓-1.6%prior 13,431

Female12,082 (47.8%)

→0.0%prior 12,080

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: 11,356
Total persons involved: 27,232
Total vehicles involved: 21,702

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

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11,356 CRASHES INOHIO, OH2025