Monthly Traffic Safety Analysis

20,621 CRASHES IN
OHIO, OH
AUGUST 2025

All metrics benchmarked againstAugust 2024

In August 2025, Ohio recorded 20,621 traffic crashes, a 0.7% increase from the 20,475 crashes documented in August 2024. Total fatalities rose from 130 to 133 year-over-year, while total injuries increased from 8,162 to 8,273. One of the most notable year-over-year shifts was a 34.8% increase in bicycle-involved crashes, which grew from 158 to 213 incidents.

20,621

0.7%was 20,475

Total Crash Events

133

2.3%was 130

Persons Killed

8,273

1.4%was 8,162

Persons Injured

3,623

0.8%was 3,595

Hit-and-Run Crashes

Note: "Persons Killed" (133) counts individual fatalities across all crash events. "Fatal" in the severity table below (122) 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 · 2025-08-01 to 2025-08-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Year-over-year data indicates a slight upward trend in traffic incidents for August. Total crashes increased by 0.7%, from 20,475 in August 2024 to 20,621 in August 2025. Similarly, total injuries rose by 1.4% and fatalities increased by 2.3% over the same period.

3,623

Hit-and-Run Crashes — August 2025

0.8% vs prior (3,595)

The rate of hit-and-run crashes remained stable year-over-year. In both August 2025 and August 2024, hit-and-runs accounted for 17.6% of all crashes. The absolute number of hit-and-run incidents saw a minimal increase, rising from 3,595 to 3,623.

Vulnerable Road User Casualties

6

Pedestrians Killed

Prior: 13-53.8%

127

Motorists Killed

Prior: 1178.5%

234

Pedestrians Injured

Prior: 19718.8%

8,039

Motorists Injured

Prior: 7,9650.9%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes remained largely consistent year-over-year, with Friday being the peak day for crashes in both August 2025 (3,785 crashes) and August 2024 (3,848 crashes). The 4 p.m. hour was also the peak hour in both periods, with 1,796 crashes in the current month compared to 1,763 in the prior year. While the overall daily distribution was similar, Tuesday (2,947 crashes) replaced Thursday (2,933 crashes) as the second-busiest day for crashes in August 2025.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity saw minimal changes year-over-year. Fatal crashes accounted for 0.6% of all incidents in both August 2025 (122 crashes) and August 2024 (118 crashes). Crashes resulting in minor injuries saw a slight proportional increase from 14.1% to 14.4% of all crashes. Correspondingly, the proportion of no-injury crashes decreased slightly from 72.3% to 71.9%.

Severity is per crash event (most severe injury). 122 fatal crash events resulted in 133 persons killed.

Outcome by Severity (Crash Events)

Fatal122fatal crashes0.6%
3.4%prior 118
Serious Injury642serious injury crashes3.1%
1.6%prior 632
Minor Injury2,961minor injury crashes14.4%
2.8%prior 2,879
Possible Injury2,071possible injury crashes10%
1.0%prior 2,050
No Injury14,825no injury crashes71.9%
0.2%prior 14,796

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Most severe injury per crash record

Road & Environmental Conditions

Environmental conditions during crashes shifted between the two periods. In August 2025, crashes in clear weather constituted 79.9% of the total, up from 76.1% in the prior year. Correspondingly, crashes occurring in the rain dropped from 5.9% to 3.1% of all incidents. This pattern is reflected in road surface conditions, where crashes on dry roads increased from 90.3% to 94.3% of the total, while crashes on wet surfaces decreased from 9.1% to 5.2%.

Weather

Clear16,481 (79.9%)
5.8%prior 15,579
Cloudy3,233 (15.7%)
-7.6%prior 3,500
Rain648 (3.1%)
-46.0%prior 1,201
Other/Unknown186 (0.9%)
35.8%prior 137
Fog; Smog; Smoke66 (0.3%)
37.5%prior 48
Sleet; Hail3 (0.0%)
Severe Crosswinds2 (0.0%)
-71.4%prior 7
Freezing Rain or Freezing Drizzle1 (0.0%)
Blowing Sand; Soil; Dirt; Snow1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Weather condition at time of crash

Lighting

Daylight15,706 (76.2%)
1.5%prior 15,476
Dark - Lighted Roadway2,176 (10.6%)
-2.4%prior 2,229
Dark - Roadway Not Lighted1,565 (7.6%)
-5.8%prior 1,661
Dawn/Dusk933 (4.5%)
3.1%prior 905
Other/Unknown151 (0.7%)
24.8%prior 121
Dark - Unknown Roadway Lighting90 (0.4%)
8.4%prior 83

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Lighting condition field

Road Surface

Dry19,439 (94.3%)
5.1%prior 18,488
Wet1,064 (5.2%)
-42.6%prior 1,854
Other/Unknown110 (0.5%)
14.6%prior 96
Sand; Mud; Dirt; Oil; Gravel6 (0.0%)
-50.0%prior 12
Water (Standing; Moving)1 (0.0%)
-95.5%prior 22
Snow1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent year-over-year: Chevrolet, Ford, and Honda, with all three seeing a minor increase in total counts. An analysis of persons involved in crashes shows a slight demographic shift. The proportion of individuals aged 16-20 decreased from 12.0% to 11.5% of all persons involved, while the proportion of those aged 65 and older increased from 11.7% to 12.2%.

Top Vehicle Makes (38,204 vehicles)

1
CHEVROLET5,355 (14%)
1.2%prior 5,294
2
FORD5,082 (13.3%)
0.5%prior 5,056
3
HONDA3,649 (9.6%)
5.6%prior 3,455
4
TOYOTA3,006 (7.9%)
-0.6%prior 3,024
5
NISSAN1,668 (4.4%)
-1.9%prior 1,701
6
KIA1,625 (4.3%)
16.1%prior 1,400
7
JEEP1,577 (4.1%)
0.2%prior 1,574
8
DODGE1,478 (3.9%)
-10.9%prior 1,658
9
HYUNDAI1,388 (3.6%)
-4.3%prior 1,450
10
OTHER/UNKNOWN1,211 (3.2%)
3.9%prior 1,166

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · Vehicle unit records

3,047 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (45,700 persons with recorded sex)

Male25,377 (55.5%)
1.4%prior 25,034
Female20,323 (44.5%)
0.3%prior 20,259

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-08-01 to 2025-08-31 · 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: 2025-08-01 through 2025-08-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2025-08-01 through 2025-08-31 (31 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 20,621
  • Total persons involved: 48,258
  • Total vehicles involved: 38,204

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: August 2025." Published July 5, 2026. Reporting period: 2025-08-01 to 2025-08-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/august-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

Ohio (Statewide) Crash Report — August 2025 | ThatCarHitMe.com