Yearly Traffic Safety Analysis

1,417 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Seneca County recorded 1,417 total crashes, a 3.6% increase from the 1,368 crashes documented in 2024. Despite the rise in overall collisions, the number of fatalities decreased from 13 in the prior year to 8 in the current year. This represents a 38.5% reduction in traffic-related deaths year-over-year.

1,417

3.6%was 1,368

Total Crash Events

8

-38.5%was 13

Persons Killed

421

-8.1%was 458

Persons Injured

81

9.5%was 74

Hit-and-Run Crashes

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 collisions in Seneca County saw a modest increase of 3.6% from 1,368 in 2024 to 1,417 in 2025. However, the severity of these crashes trended downward, with total injuries falling by 8.1% and fatalities decreasing by 38.5% compared to the previous year.

81

Hit-and-Run Crashes — 2025

9.5% vs prior (74)

The number of hit-and-run incidents increased from 74 in 2024 to 81 in 2025. This represents a rise in both the absolute count and the rate of such crashes. The hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, edged up from 5.4% to 5.7% year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

7

Motorists Killed

Prior: 13-46.2%

12

Pedestrians Injured

Prior: 5140.0%

409

Motorists Injured

Prior: 453-9.7%

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 pattern of crashes showed a notable shift in the peak hour of collisions year-over-year. While Friday remained the busiest day for crashes in both periods (243 in 2025 vs. 229 in 2024), the peak hour moved from 3 p.m. in 2024 to 7 a.m. in 2025. This indicates a change from an afternoon peak to a morning commute peak for crash frequency.

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 decreased from 2024 to 2025. The proportion of fatal crashes fell slightly from 0.7% to 0.6% of all incidents. More significantly, the share of crashes resulting in 'Possible Injury' dropped from 9.3% to 7.2%, while the proportion of 'No Injury' crashes increased from 77.0% to 79.0%. The count of serious injury crashes remained nearly unchanged, with 51 in the current period compared to 50 in the prior.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.6%
-11.1%prior 9
Serious Injury51serious injury crashes3.6%
2.0%prior 50
Minor Injury136minor injury crashes9.6%
6.3%prior 128
Possible Injury102possible injury crashes7.2%
-19.7%prior 127
No Injury1,120no injury crashes79%
6.3%prior 1,054

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 across different conditions remained largely consistent year-over-year, with the majority of incidents in both periods occurring in daylight and on dry roads. In 2025, 75.7% of crashes happened on dry surfaces, compared to 77.2% in 2024. There was a notable shift in precipitation-related crashes, with incidents during snowy conditions increasing from 49 to 122, while crashes in rainy conditions decreased from 139 to 75.

Weather

Clear835 (58.9%)
3.3%prior 808
Cloudy337 (23.8%)
-2.0%prior 344
Snow122 (8.6%)
149.0%prior 49
Rain75 (5.3%)
-46.0%prior 139
Other/Unknown16 (1.1%)
23.1%prior 13
Fog; Smog; Smoke14 (1.0%)
16.7%prior 12
Freezing Rain or Freezing Drizzle5 (0.4%)
Severe Crosswinds5 (0.4%)
Sleet; Hail5 (0.4%)
Blowing Sand; Soil; Dirt; Snow3 (0.2%)

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

Lighting

Daylight728 (51.4%)
2.0%prior 714
Dark - Roadway Not Lighted468 (33.0%)
8.8%prior 430
Dawn/Dusk109 (7.7%)
12.4%prior 97
Dark - Lighted Roadway89 (6.3%)
-16.0%prior 106
Other/Unknown18 (1.3%)
5.9%prior 17
Dark - Unknown Roadway Lighting5 (0.4%)

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

Road Surface

Dry1,072 (75.7%)
1.5%prior 1,056
Wet180 (12.7%)
-28.0%prior 250
Snow103 (7.3%)
123.9%prior 46
Ice53 (3.7%)
430.0%prior 10
Slush5 (0.4%)
Other/Unknown3 (0.2%)
Water (Standing; Moving)1 (0.1%)

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

Vehicles & Demographics

Passenger Cars, Sport Utility Vehicles, and Pick-up trucks were the three most common vehicle types involved in crashes in both years, though the number of SUVs in crashes increased from 601 to 678. Ford and Chevrolet remained the top two makes, with Ford's involvement decreasing from 401 to 385 and Chevrolet's increasing from 328 to 356. The most frequently involved age group of persons in crashes shifted from the 16-20 bracket in 2024 (378 people) to the 26-34 bracket in 2025 (368 people).

Top Vehicle Makes (2,086 vehicles)

1
FORD385 (18.5%)
-4.0%prior 401
2
CHEVROLET356 (17.1%)
8.5%prior 328
3
TOYOTA111 (5.3%)
76.2%prior 63
4
DODGE110 (5.3%)
-11.3%prior 124
5
HONDA109 (5.2%)
-24.8%prior 145
6
JEEP104 (5%)
-4.6%prior 109
7
KIA101 (4.8%)
31.2%prior 77
8
GMC91 (4.4%)
-2.2%prior 93
9
CHRYSLER85 (4.1%)
16.4%prior 73
10
HYUNDAI63 (3%)
-12.5%prior 72

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

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

Sex Distribution (2,562 persons with recorded sex)

Male1,393 (54.4%)
0.0%prior 1,393
Female1,169 (45.6%)
3.7%prior 1,127

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 5, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 1,417
  • Total persons involved: 2,631
  • Total vehicles involved: 2,086

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 5, 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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Seneca County, OH Crash Report — 2025 | ThatCarHitMe.com