Yearly Traffic Safety Analysis

371 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Carroll County recorded 371 total vehicle crashes, a 4.6% decrease from the 389 crashes reported in 2024. While overall crashes and injuries declined, the number of hit-and-run crashes saw a notable increase, rising from 22 to 32. Conversely, crashes involving a driver under the influence fell from 22 in the prior period to 12 in the current period.

371

-4.6%was 389

Total Crash Events

3

Persons Killed

142

-12.3%was 162

Persons Injured

32

45.5%was 22

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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

Traffic crashes in Carroll County showed a downward trend in 2025 compared to the previous year. Total crashes decreased by 4.6%, from 389 to 371, and the number of people injured fell by 12.3%, from 162 to 142. The number of fatalities remained unchanged at three for both periods.

32

Hit-and-Run Crashes — 2025

45.5% vs prior (22)

Hit-and-run incidents increased notably in 2025 compared to the previous year. The total number of hit-and-run crashes rose from 22 to 32, representing a 45.5% increase. This trend is also reflected in the hit-and-run rate, which climbed from 5.7% of all crashes in 2024 to 8.6% in 2025.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

3

Motorists Killed

Prior: 30.0%

1

Pedestrians Injured

Prior: 3-66.7%

141

Motorists Injured

Prior: 159-11.3%

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 shifted between the two periods. In 2025, the peak day for crashes was Tuesday with 65 incidents, a change from Thursday (68 incidents) in 2024. The single hour with the most crashes moved from 3 p.m. in the prior year to 4 p.m. in the current year, though the afternoon hours consistently saw the highest crash volumes in both periods.

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

While the number of fatal crashes remained constant at three in both 2024 and 2025, the overall severity of crashes decreased. The proportion of crashes resulting in either a serious or minor injury fell from a combined 23.7% in 2024 to 18.9% in 2025. Correspondingly, no-injury crashes increased their share of the total, rising from 69.4% to 74.4% of all incidents.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.8%
0.0%prior 3
Serious Injury17serious injury crashes4.6%
-19.0%prior 21
Minor Injury53minor injury crashes14.3%
-25.4%prior 71
Possible Injury22possible injury crashes5.9%
-8.3%prior 24
No Injury276no injury crashes74.4%
2.2%prior 270

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 majority of crashes in both 2025 and 2024 occurred in daylight and on dry roads, with proportions remaining nearly identical year-over-year. A significant shift was observed in adverse road surface conditions, with crashes on snow-covered roads increasing from 15 in 2024 to 37 in 2025. Crashes on dry surfaces decreased from 295 to 255 over the same period.

Weather

Clear230 (62.0%)
-6.5%prior 246
Cloudy52 (14.0%)
-35.0%prior 80
Rain39 (10.5%)
0.0%prior 39
Snow36 (9.7%)
140.0%prior 15
Other/Unknown3 (0.8%)
Fog; Smog; Smoke3 (0.8%)
-40.0%prior 5
Freezing Rain or Freezing Drizzle3 (0.8%)
Blowing Sand; Soil; Dirt; Snow3 (0.8%)
Sleet; Hail1 (0.3%)
Severe Crosswinds1 (0.3%)

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

Lighting

Daylight241 (65.0%)
-5.1%prior 254
Dark - Roadway Not Lighted87 (23.5%)
4.8%prior 83
Dark - Lighted Roadway18 (4.9%)
-10.0%prior 20
Dawn/Dusk17 (4.6%)
-37.0%prior 27
Other/Unknown5 (1.3%)
Dark - Unknown Roadway Lighting3 (0.8%)

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

Road Surface

Dry255 (68.7%)
-13.6%prior 295
Wet65 (17.5%)
-4.4%prior 68
Snow37 (10.0%)
208.3%prior 12
Slush6 (1.6%)
Ice4 (1.1%)
-42.9%prior 7
Other/Unknown4 (1.1%)

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

Vehicles & Demographics

A shift occurred in the types of vehicles most frequently involved in crashes, with Sport Utility Vehicles (160) slightly outnumbering Passenger Cars (157) in 2025, reversing the order from 2024. The top vehicle makes also changed, as Ford became the most common make with 115 vehicles involved, while Chevrolet moved to second with 96 vehicles. The total number of vehicles involved in collisions decreased from 616 to 563, reflecting the overall reduction in crashes.

Top Vehicle Makes (563 vehicles)

1
FORD115 (20.4%)
11.7%prior 103
2
CHEVROLET96 (17.1%)
-13.5%prior 111
3
DODGE42 (7.5%)
13.5%prior 37
4
JEEP30 (5.3%)
-14.3%prior 35
5
HONDA28 (5%)
-28.2%prior 39
6
GMC26 (4.6%)
-31.6%prior 38
7
SUBARU26 (4.6%)
-3.7%prior 27
8
TOYOTA20 (3.6%)
-33.3%prior 30
9
RAM20 (3.6%)
122.2%prior 9
10
NISSAN16 (2.8%)
-23.8%prior 21

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

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

Sex Distribution (736 persons with recorded sex)

Male450 (61.1%)
-3.8%prior 468
Female286 (38.9%)
-5.9%prior 304

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: 371
  • Total persons involved: 754
  • Total vehicles involved: 563

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