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Yearly Traffic Safety Analysis

13,196 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Summit County, total traffic crashes increased by 4.0% from 12,683 in 2024 to 13,196 in 2025. While total collisions rose, fatalities decreased from 37 to 33 over the same period. The most significant year-over-year change was a 21.5% increase in crashes involving speeding, which rose from 1,096 incidents in 2024 to 1,332 in 2025.

13,196

▲ 4.0%was 12,683

Total Crash Events

▼ -10.8%was 37

Persons Killed

3,951

▲ 1.7%was 3,886

Persons Injured

2,230

▼ -3.5%was 2,311

Hit-and-Run Crashes

Note: "Persons Killed" (33) counts individual fatalities across all crash events. "Fatal" in the severity table below (33) 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 safety trends in Summit County show a rise in total crashes, which increased by 4.0% from 12,683 in 2024 to 13,196 in 2025. This increase was accompanied by a 1.7% rise in injuries, from 3,886 to 3,951. Conversely, the number of fatalities saw a 10.8% decrease, falling from 37 to 33 year-over-year.

2,230

Hit-and-Run Crashes — 2025

▼ -3.5% vs prior (2,311)

Hit-and-run incidents showed a downward trend in Summit County. The total number of hit-and-run crashes decreased from 2,311 in 2024 to 2,230 in 2025. The corresponding hit-and-run rate, which measures the proportion of all crashes that are hit-and-runs, also declined from 18.2% to 16.9% over the same period.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 6↓-33.3%

Motorists Killed

Prior: 31↓-6.5%

Pedestrians Injured

Prior: 103↓-16.5%

3,865

Motorists Injured

Prior: 3,783↑2.2%

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 shifted slightly between the two periods. In 2025, the peak day for crashes was Friday with 2,225 incidents, a change from Thursday (2,124 incidents) in the prior year. The peak hour also shifted one hour earlier, moving from the 5 p.m. hour in 2024 (1,118 crashes) to the 4 p.m. hour in 2025 (1,171 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 showed a mixed trend year-over-year. The fatal crash rate decreased from 0.29% in 2024 to 0.25% in 2025, with fatal crashes dropping from 37 to 33. The proportion of serious injury crashes also declined from 1.9% to 1.7%. However, crashes resulting in minor injuries increased as a share of the total, rising from 10.1% (1,287 crashes) in 2024 to 10.7% (1,418 crashes) in 2025.

Outcome by Severity (Crash Events)

Fatal33fatal crashes0.3%

↓-10.8%prior 37

Serious Injury224serious injury crashes1.7%

↓-5.9%prior 238

Minor Injury1,418minor injury crashes10.7%

↑10.2%prior 1,287

Possible Injury1,213possible injury crashes9.2%

↓-1.1%prior 1,227

No Injury10,308no injury crashes78.1%

↑4.2%prior 9,894

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

There was a notable shift in the conditions under which crashes occurred. Collisions on snowy roads more than doubled, increasing from 398 in 2024 to 1,143 in 2025, while crashes on icy roads nearly tripled from 114 to 326. Consequently, the share of crashes on dry roads decreased from 74.6% to 70.1%. Lighting conditions remained relatively stable, with daylight crashes accounting for 68.6% of incidents in 2025, compared to 67.6% in 2024.

Weather

Clear7,457 (56.5%)

↑1.0%prior 7,383

Cloudy2,923 (22.2%)

↓-1.6%prior 2,970

Snow1,381 (10.5%)

↑140.2%prior 575

Rain1,185 (9.0%)

↓-23.2%prior 1,543

Other/Unknown117 (0.9%)

↓-9.3%prior 129

Freezing Rain or Freezing Drizzle63 (0.5%)

↑110.0%prior 30

Sleet; Hail28 (0.2%)

↑55.6%prior 18

Fog; Smog; Smoke22 (0.2%)

↓-12.0%prior 25

Blowing Sand; Soil; Dirt; Snow15 (0.1%)

↑200.0%prior 5

Severe Crosswinds5 (0.0%)

→0.0%prior 5

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

Lighting

Daylight9,058 (68.6%)

↑5.7%prior 8,571

Dark - Lighted Roadway2,491 (18.9%)

↑1.7%prior 2,450

Dark - Roadway Not Lighted781 (5.9%)

↑0.6%prior 776

Dawn/Dusk710 (5.4%)

↑0.6%prior 706

Other/Unknown93 (0.7%)

↓-14.7%prior 109

Dark - Unknown Roadway Lighting63 (0.5%)

↓-11.3%prior 71

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

Road Surface

Dry9,244 (70.1%)

↓-2.2%prior 9,456

Wet2,340 (17.7%)

↓-9.3%prior 2,581

Snow1,143 (8.7%)

↑187.2%prior 398

Ice326 (2.5%)

↑186.0%prior 114

Other/Unknown90 (0.7%)

↓-19.6%prior 112

Slush48 (0.4%)

↑336.4%prior 11

Water (Standing; Moving)5 (0.0%)

↓-37.5%prior 8

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 remained consistent year-over-year. The top five makes—Ford, Chevrolet, Honda, Toyota, and Kia—retained their rankings in both 2024 and 2025, with Ford vehicles involved in 3,150 crashes in the current period compared to 3,129 in the prior. The age distribution of persons involved in crashes also showed little change, with the 26-34 age group representing the largest cohort in both years (15.6% in 2025 vs. 15.9% in 2024).

Top Vehicle Makes (24,453 vehicles)

FORD3,150 (12.9%)

↑0.7%prior 3,129

CHEVROLET2,991 (12.2%)

↑4.2%prior 2,871

HONDA2,013 (8.2%)

↑5.1%prior 1,916

TOYOTA1,991 (8.1%)

↑7.4%prior 1,853

KIA1,378 (5.6%)

↑4.3%prior 1,321

JEEP1,198 (4.9%)

↑2.0%prior 1,174

HYUNDAI1,191 (4.9%)

↑6.3%prior 1,120

NISSAN1,153 (4.7%)

↑2.7%prior 1,123

DODGE904 (3.7%)

↓-9.5%prior 999

SUBARU697 (2.9%)

↑17.3%prior 594

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

2,147 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (28,478 persons with recorded sex)

Male15,439 (54.2%)

↑3.6%prior 14,909

Female13,039 (45.8%)

↑0.5%prior 12,979

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: August 22, 2026

Data Coverage

Reporting period: 2025-01-01 through 2025-12-31 (365 days)
Geographic scope: ohio, OH
Total crash records analyzed: 13,196
Total persons involved: 30,481
Total vehicles involved: 24,453

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 August 22, 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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