Monthly Traffic Safety Analysis

25,562 CRASHES IN
OHIO, OH
OCTOBER 2025

All metrics benchmarked againstOctober 2024

In October 2025, Ohio recorded 25,562 traffic crashes, a 4.5% increase from the 24,469 crashes reported in October 2024. Despite the rise in total incidents, the number of fatalities saw a notable year-over-year decrease, falling 16.4% from 116 to 97. Total injuries remained nearly unchanged, declining by a marginal 0.5%.

25,562

4.5%was 24,469

Total Crash Events

97

-16.4%was 116

Persons Killed

8,649

-0.5%was 8,689

Persons Injured

3,785

4.2%was 3,631

Hit-and-Run Crashes

Note: "Persons Killed" (97) counts individual fatalities across all crash events. "Fatal" in the severity table below (91) 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 · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends show an increase in volume from October 2024 to October 2025, with total crashes rising by 4.5%. However, this increase in incidents did not correlate with a rise in severity. Fatalities decreased by 16.4% (from 116 to 97), and total injuries remained stable (8,689 vs. 8,649), suggesting a year-over-year shift toward less severe outcomes despite more frequent crashes.

3,785

Hit-and-Run Crashes — October 2025

4.2% vs prior (3,631)

The number of hit-and-run crashes increased by 4.2%, from 3,631 in October 2024 to 3,785 in October 2025. However, this rise was proportional to the overall increase in total crashes. As a result, the hit-and-run rate remained stable and unchanged at 14.8% for both periods.

Vulnerable Road User Casualties

16

Pedestrians Killed

Prior: 1145.5%

81

Motorists Killed

Prior: 105-22.9%

285

Pedestrians Injured

Prior: 312-8.7%

8,364

Motorists Injured

Prior: 8,377-0.2%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · 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. Thursday was the peak day for crashes in both October 2025 (4,675 crashes) and October 2024 (4,462 crashes). The peak time for incidents shifted slightly from the 3 PM hour in 2024 (2,000 crashes) to the 4 PM hour in 2025 (1,997 crashes), keeping the afternoon commute as the highest-risk period.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the severity of those crashes decreased year-over-year. The fatal crash rate fell from 0.42 per 100 crashes in October 2024 to 0.36 in October 2025. The proportion of crashes resulting in any injury also declined slightly, from 24.7% in the prior period to 23.9% in the current period.

Severity is per crash event (most severe injury). 91 fatal crash events resulted in 97 persons killed.

Outcome by Severity (Crash Events)

Fatal91fatal crashes0.4%
-11.7%prior 103
Serious Injury590serious injury crashes2.3%
2.4%prior 576
Minor Injury3,116minor injury crashes12.2%
-1.0%prior 3,147
Possible Injury2,403possible injury crashes9.4%
3.2%prior 2,329
No Injury19,362no injury crashes75.7%
5.7%prior 18,314

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record

Road & Environmental Conditions

A significant shift occurred in the environmental conditions under which crashes happened. In October 2025, crashes during rain accounted for 13.6% of the total (3,481 incidents), a substantial increase from 4.6% (1,132 incidents) in the prior year. Consequently, the proportion of crashes on wet road surfaces also rose sharply from 7.8% to 17.2%, indicating that adverse weather was a more prominent factor in the current period.

Weather

Clear18,173 (71.1%)
-9.0%prior 19,965
Cloudy3,589 (14.0%)
15.6%prior 3,106
Rain3,481 (13.6%)
207.5%prior 1,132
Other/Unknown189 (0.7%)
38.0%prior 137
Fog; Smog; Smoke120 (0.5%)
31.9%prior 91
Freezing Rain or Freezing Drizzle4 (0.0%)
-33.3%prior 6
Severe Crosswinds2 (0.0%)
Blowing Sand; Soil; Dirt; Snow2 (0.0%)
Sleet; Hail1 (0.0%)
-96.7%prior 30
Snow1 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash

Lighting

Daylight15,566 (60.9%)
3.0%prior 15,117
Dark - Roadway Not Lighted3,982 (15.6%)
1.9%prior 3,908
Dark - Lighted Roadway3,823 (15.0%)
8.0%prior 3,541
Dawn/Dusk1,874 (7.3%)
14.3%prior 1,640
Dark - Unknown Roadway Lighting166 (0.6%)
29.7%prior 128
Other/Unknown151 (0.6%)
11.9%prior 135

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field

Road Surface

Dry21,025 (82.3%)
-6.3%prior 22,427
Wet4,404 (17.2%)
131.7%prior 1,901
Other/Unknown105 (0.4%)
2.9%prior 102
Sand; Mud; Dirt; Oil; Gravel14 (0.1%)
0.0%prior 14
Water (Standing; Moving)11 (0.0%)
Snow3 (0.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained unchanged year-over-year, with Chevrolet, Ford, and Honda leading in both periods. Similarly, the primary vehicle types involved were consistent, led by Passenger Cars and Sport Utility Vehicles. The age distribution of all persons involved in crashes also showed little variation, with no significant shifts in representation among groups like 16-20 year-olds or those aged 65 and over.

Top Vehicle Makes (45,507 vehicles)

1
CHEVROLET6,347 (13.9%)
2.6%prior 6,185
2
FORD6,057 (13.3%)
2.7%prior 5,899
3
HONDA4,484 (9.9%)
7.7%prior 4,165
4
TOYOTA3,795 (8.3%)
7.7%prior 3,524
5
NISSAN1,971 (4.3%)
-1.0%prior 1,990
6
KIA1,952 (4.3%)
10.0%prior 1,774
7
JEEP1,949 (4.3%)
6.5%prior 1,830
8
DODGE1,824 (4%)
-4.4%prior 1,907
9
HYUNDAI1,782 (3.9%)
6.8%prior 1,669
10
GMC1,335 (2.9%)
11.4%prior 1,198

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records

3,445 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (55,097 persons with recorded sex)

Male30,253 (54.9%)
5.4%prior 28,696
Female24,844 (45.1%)
4.2%prior 23,844

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2025-10-01 through 2025-10-31 (31 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 25,562
  • Total persons involved: 57,837
  • Total vehicles involved: 45,507

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: October 2025." Published July 5, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/october-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

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