Yearly Traffic Safety Analysis

2,458 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Tuscarawas County, total traffic crashes increased by 3.8%, rising from 2,367 in the prior year to 2,458 in the current period. While total injuries saw a slight decrease, the number of fatalities grew from 12 to 14. The most notable shift was a decrease in serious injury crashes, which fell from 55 to 40, even as total crashes increased.

2,458

3.8%was 2,367

Total Crash Events

14

16.7%was 12

Persons Killed

680

-3.4%was 704

Persons Injured

233

-1.7%was 237

Hit-and-Run Crashes

Note: "Persons Killed" (14) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) 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, Tuscarawas County experienced a rising trend in traffic collisions, with total crashes increasing by 3.8% year-over-year. This increase was accompanied by a 16.7% rise in fatalities, from 12 to 14. However, the number of people injured in crashes declined by 3.4%, from 704 to 680.

233

Hit-and-Run Crashes — 2025

-1.7% vs prior (237)

Hit-and-run incidents showed a slight downward trend in Tuscarawas County. The total number of hit-and-run crashes decreased from 237 in the prior year to 233 in the current year. Correspondingly, the hit-and-run rate as a percentage of all crashes also declined, moving from 10.0% to 9.5%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

13

Motorists Killed

Prior: 128.3%

13

Pedestrians Injured

Prior: 14-7.1%

667

Motorists Injured

Prior: 690-3.3%

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 remained largely consistent between the two periods. Friday continued to be the peak day for crashes, with 411 incidents in the current year compared to 415 in the prior year. The 3 p.m. hour was the peak time in both years, with crash volume during this hour increasing from 180 to 200.

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 shifted slightly year-over-year, with a notable decrease in serious injury collisions, which fell from 2.3% to 1.6% of all crashes. Fatal crashes increased from 12 to 13, but their proportion of total crashes remained stable at 0.5%. Crashes resulting in no injury increased from 77.9% to 79.0% of the total, indicating a higher volume of lower-severity incidents in the current period.

Severity is per crash event (most severe injury). 13 fatal crash events resulted in 14 persons killed.

Outcome by Severity (Crash Events)

Fatal13fatal crashes0.5%
8.3%prior 12
Serious Injury40serious injury crashes1.6%
-27.3%prior 55
Minor Injury327minor injury crashes13.3%
5.5%prior 310
Possible Injury135possible injury crashes5.5%
-6.9%prior 145
No Injury1,943no injury crashes79%
5.3%prior 1,845

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

Crash conditions saw a notable shift related to adverse weather year-over-year. While crashes on dry roads remained most common, their count was nearly identical (1,852 vs 1,860), making them a smaller proportion of the increased total. Crashes occurring in snow increased from 87 to 156, and those on snowy road surfaces rose from 66 to 144. The proportion of crashes in daylight was stable at approximately 61% for both periods.

Weather

Clear1,360 (55.3%)
-4.3%prior 1,421
Cloudy685 (27.9%)
17.7%prior 582
Rain204 (8.3%)
-18.7%prior 251
Snow156 (6.3%)
79.3%prior 87
Fog; Smog; Smoke24 (1.0%)
84.6%prior 13
Freezing Rain or Freezing Drizzle14 (0.6%)
Other/Unknown7 (0.3%)
Sleet; Hail5 (0.2%)
-28.6%prior 7
Severe Crosswinds3 (0.1%)

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

Lighting

Daylight1,505 (61.2%)
4.4%prior 1,441
Dark - Roadway Not Lighted626 (25.5%)
12.4%prior 557
Dark - Lighted Roadway221 (9.0%)
-6.4%prior 236
Dawn/Dusk87 (3.5%)
-29.3%prior 123
Dark - Unknown Roadway Lighting12 (0.5%)
71.4%prior 7
Other/Unknown7 (0.3%)

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

Road Surface

Dry1,852 (75.3%)
-0.4%prior 1,860
Wet404 (16.4%)
-1.0%prior 408
Snow144 (5.9%)
118.2%prior 66
Ice40 (1.6%)
73.9%prior 23
Slush14 (0.6%)
100.0%prior 7
Other/Unknown3 (0.1%)
Sand; Mud; Dirt; Oil; Gravel1 (0.0%)

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

Vehicles & Demographics

The primary vehicles involved in crashes remained consistent, with Passenger Cars, Sport Utility Vehicles, and Pick-ups comprising the top three types in both years. Ford and Chevrolet were the top two makes involved, swapping the first and second positions, with 573 and 572 vehicles respectively in the current year. Among persons involved, the 16-20 age group saw a slight increase in representation, becoming the largest cohort with 718 individuals, up from 690 in the prior year.

Top Vehicle Makes (3,831 vehicles)

1
FORD573 (15%)
-3.7%prior 595
2
CHEVROLET572 (14.9%)
-4.7%prior 600
3
HONDA435 (11.4%)
4.1%prior 418
4
TOYOTA270 (7%)
9.8%prior 246
5
NISSAN202 (5.3%)
5.2%prior 192
6
DODGE175 (4.6%)
-2.2%prior 179
7
JEEP166 (4.3%)
1.8%prior 163
8
GMC157 (4.1%)
25.6%prior 125
9
KIA127 (3.3%)
-6.6%prior 136
10
SUBARU113 (2.9%)
18.9%prior 95

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

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

Sex Distribution (4,826 persons with recorded sex)

Male2,725 (56.5%)
3.3%prior 2,639
Female2,101 (43.5%)
0.1%prior 2,099

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: 2,458
  • Total persons involved: 4,973
  • Total vehicles involved: 3,831

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