Yearly Traffic Safety Analysis

2,076 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Hancock County recorded 2,076 total crashes, a slight decrease of approximately 0.9% from the 2,095 crashes recorded in 2024. Despite the stable overall crash volume, the number of fatalities was halved, dropping from 14 in the prior year to 7 in the current year. This significant reduction in fatalities represents the most notable year-over-year shift in the data.

2,076

▼ -0.9%was 2,095

Total Crash Events

7

▼ -50.0%was 14

Persons Killed

606

▲ 3.9%was 583

Persons Injured

198

▼ -12.4%was 226

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) 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 Hancock County remained relatively stable, with total crashes decreasing by less than 1% from 2,095 in 2024 to 2,076 in 2025. However, outcomes saw significant shifts, with total injuries increasing by 3.9% to 606, while total fatalities saw a substantial 50% reduction from 14 to 7 year-over-year.

198

Hit-and-Run Crashes — 2025

▼ -12.4% vs prior (226)

Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. The count of hit-and-run crashes fell from 226 in 2024 to 198 in 2025. This represents a downward trend in the hit-and-run rate, which decreased from 10.8% of all crashes in the prior period to 9.5% in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 1→0.0%

6

Motorists Killed

Prior: 13↓-53.8%

15

Pedestrians Injured

Prior: 6↑150.0%

591

Motorists Injured

Prior: 577↑2.4%

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 year-over-year. The peak day for crashes moved from Friday (346 crashes) in 2024 to Thursday (331 crashes) in 2025. A more significant change occurred in the peak hour, which shifted from the 7 AM morning commute hour in the prior period (152 crashes) to the 3 PM afternoon hour in the current period (155 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 mixed changes year-over-year. The number of fatal crashes decreased from 12 in 2024 to 7 in 2025, lowering their share of total crashes from 0.6% to 0.3%. Conversely, serious injury crashes increased from 33 to 38, and possible injury crashes rose from 163 to 187. The proportion of crashes resulting in no injury remained stable at approximately 80% for both periods.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.3%
↓-41.7%prior 12
Serious Injury38serious injury crashes1.8%
↑15.2%prior 33
Minor Injury188minor injury crashes9.1%
↓-10.0%prior 209
Possible Injury187possible injury crashes9%
↑14.7%prior 163
No Injury1,656no injury crashes79.8%
↓-1.3%prior 1,678

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 proportion of crashes occurring in adverse road conditions increased significantly year-over-year. Crashes on snowy roads rose from 76 to 151, and crashes on icy roads increased from 16 to 63. This corresponds with a rise in crashes reported during snow weather conditions, from 92 to 147. Consequently, the share of crashes on dry roads decreased from 77.4% to 72.0% of the total.

Weather

Clear1,238 (59.6%)
↓-8.1%prior 1,347
Cloudy446 (21.5%)
↑14.1%prior 391
Rain194 (9.3%)
↓-12.2%prior 221
Snow147 (7.1%)
↑59.8%prior 92
Fog; Smog; Smoke18 (0.9%)
↑12.5%prior 16
Other/Unknown10 (0.5%)
↓-50.0%prior 20
Freezing Rain or Freezing Drizzle8 (0.4%)
Blowing Sand; Soil; Dirt; Snow7 (0.3%)
Sleet; Hail7 (0.3%)
Severe Crosswinds1 (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

Daylight1,242 (59.8%)
↑5.2%prior 1,181
Dark - Roadway Not Lighted483 (23.3%)
↓-7.8%prior 524
Dark - Lighted Roadway184 (8.9%)
↓-4.7%prior 193
Dawn/Dusk150 (7.2%)
↓-13.3%prior 173
Other/Unknown14 (0.7%)
↓-39.1%prior 23
Dark - Unknown Roadway Lighting3 (0.1%)

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

Road Surface

Dry1,495 (72.0%)
↓-7.8%prior 1,622
Wet353 (17.0%)
↓-1.9%prior 360
Snow151 (7.3%)
↑98.7%prior 76
Ice63 (3.0%)
↑293.8%prior 16
Slush8 (0.4%)
↓-33.3%prior 12
Other/Unknown6 (0.3%)
→0.0%prior 6

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 crashes remained consistent, with Ford (530 vehicles), Chevrolet (484), and Honda (295) leading in both periods. However, the composition of vehicle types shifted; involvement of passenger cars decreased from 1,601 to 1,495, while SUVs (727 to 752), pickups (423 to 474), and semi-tractors (134 to 163) saw increased involvement. Analysis of persons involved shows a notable decrease in the 0-15 age group, from 483 individuals in the prior year to 354 in the current year.

Top Vehicle Makes (3,267 vehicles)

1
FORD530 (16.2%)
↑3.5%prior 512
2
CHEVROLET484 (14.8%)
↑3.0%prior 470
3
HONDA295 (9%)
↓-2.3%prior 302
4
TOYOTA207 (6.3%)
↓-1.4%prior 210
5
KIA158 (4.8%)
↑6.0%prior 149
6
JEEP148 (4.5%)
↑8.0%prior 137
7
DODGE147 (4.5%)
↓-25.0%prior 196
8
GMC128 (3.9%)
↑3.2%prior 124
9
HYUNDAI128 (3.9%)
↑9.4%prior 117
10
NISSAN114 (3.5%)
↓-6.6%prior 122

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

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

Sex Distribution (4,070 persons with recorded sex)

Male2,314 (56.9%)
↓-4.2%prior 2,415
Female1,756 (43.1%)
↓-5.1%prior 1,851

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: 2,076
  • Total persons involved: 4,217
  • Total vehicles involved: 3,267

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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Hancock County, OH Crash Report — 2025 | ThatCarHitMe.com