Yearly Traffic Safety Analysis

1,769 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Columbiana County, total traffic crashes increased by 5.2% from 1,681 in 2024 to 1,769 in 2025. While total fatalities decreased from 11 to 9, the number of reported injuries rose from 584 to 627. One of the most significant changes was a 21.2% increase in crashes attributed to speeding, which rose from 189 incidents in the prior year to 229 in the current year.

1,769

5.2%was 1,681

Total Crash Events

9

-18.2%was 11

Persons Killed

627

7.4%was 584

Persons Injured

97

-20.5%was 122

Hit-and-Run Crashes

Note: "Persons Killed" (9) counts individual fatalities across all crash events. "Fatal" in the severity table below (9) 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, Columbiana County experienced an upward trend in traffic incidents in 2025 compared to the previous year, with total crashes increasing by 5.2% from 1,681 to 1,769. This increase was accompanied by a 7.4% rise in total injuries, from 584 to 627. However, the number of fatalities saw a decrease, falling from 11 in 2024 to 9 in 2025.

97

Hit-and-Run Crashes — 2025

-20.5% vs prior (122)

Hit-and-run incidents in Columbiana County showed a significant downward trend in 2025 compared to the previous year. The total number of hit-and-run crashes decreased by 20.5%, from 122 in 2024 to 97 in 2025. This decline was also reflected in the hit-and-run rate, which fell from 7.3% of all crashes in the prior period to 5.5% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

9

Motorists Killed

Prior: 11-18.2%

6

Pedestrians Injured

Prior: 7-14.3%

621

Motorists Injured

Prior: 5777.6%

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 in Columbiana County showed some shifts between 2024 and 2025. While Friday remained the peak day for crashes in both years, the number of incidents on that day decreased from 322 to 290. The peak hour for crashes shifted from the 3 p.m. hour in 2024 (125 crashes) to the 4 p.m. hour in 2025 (131 crashes). Notably, Wednesday saw a significant increase in crashes, rising from 214 in the prior year to 271 in the current year.

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 overall severity distribution of crashes in Columbiana County remained relatively stable year-over-year. The number of fatal crashes was unchanged at 9 for both 2024 and 2025, with the fatal crash rate holding steady at approximately 0.5% of all incidents. The proportion of crashes resulting in any type of injury was also consistent, accounting for 25.7% of crashes in 2025 compared to 25.6% in 2024.

Outcome by Severity (Crash Events)

Fatal9fatal crashes0.5%
0.0%prior 9
Serious Injury53serious injury crashes3%
-14.5%prior 62
Minor Injury278minor injury crashes15.7%
4.9%prior 265
Possible Injury124possible injury crashes7%
20.4%prior 103
No Injury1,305no injury crashes73.8%
5.1%prior 1,242

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 conditions under which crashes occurred showed a notable shift year-over-year, particularly concerning weather. While the majority of crashes in both periods happened in daylight on dry roads, the number of incidents during snowy conditions more than doubled, rising from 93 in 2024 to 194 in 2025. Consequently, the share of crashes on dry roads decreased from 72.1% to 68.7%, while crashes on snowy roads increased from 4.5% to 11.0% of the total.

Weather

Clear824 (46.6%)
-7.1%prior 887
Cloudy572 (32.3%)
17.2%prior 488
Snow194 (11.0%)
108.6%prior 93
Rain149 (8.4%)
-18.1%prior 182
Fog; Smog; Smoke16 (0.9%)
-20.0%prior 20
Sleet; Hail5 (0.3%)
Freezing Rain or Freezing Drizzle4 (0.2%)
Other/Unknown3 (0.2%)
Severe Crosswinds1 (0.1%)
Blowing Sand; Soil; Dirt; Snow1 (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

Daylight1,041 (58.8%)
6.9%prior 974
Dark - Roadway Not Lighted460 (26.0%)
-3.8%prior 478
Dawn/Dusk130 (7.3%)
26.2%prior 103
Dark - Lighted Roadway122 (6.9%)
10.9%prior 110
Dark - Unknown Roadway Lighting12 (0.7%)
-7.7%prior 13
Other/Unknown4 (0.2%)

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

Road Surface

Dry1,215 (68.7%)
0.2%prior 1,212
Wet315 (17.8%)
-13.0%prior 362
Snow194 (11.0%)
155.3%prior 76
Ice33 (1.9%)
22.2%prior 27
Slush10 (0.6%)
Sand; Mud; Dirt; Oil; Gravel1 (0.1%)
Other/Unknown1 (0.1%)

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

Vehicles & Demographics

The composition of vehicles and persons involved in crashes remained broadly consistent, with minor shifts. Passenger cars, sport utility vehicles, and pick-up trucks were the three most common vehicle types in both years. Among vehicle makes, Chevrolet and Ford continued to be the most frequently involved, with Chevrolet increasing its count from 486 to 534. An analysis of persons involved shows a slight increase in the representation of the 16-20 age group, which accounted for 13.6% of individuals in 2025, up from 12.2% in the prior year.

Top Vehicle Makes (2,636 vehicles)

1
CHEVROLET534 (20.3%)
9.9%prior 486
2
FORD433 (16.4%)
-4.8%prior 455
3
JEEP176 (6.7%)
17.3%prior 150
4
TOYOTA140 (5.3%)
29.6%prior 108
5
DODGE140 (5.3%)
-19.5%prior 174
6
KIA137 (5.2%)
39.8%prior 98
7
HONDA126 (4.8%)
-6.7%prior 135
8
NISSAN120 (4.6%)
16.5%prior 103
9
GMC108 (4.1%)
6.9%prior 101
10
SUBARU86 (3.3%)
10.3%prior 78

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

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

Sex Distribution (3,335 persons with recorded sex)

Male1,909 (57.2%)
2.0%prior 1,871
Female1,426 (42.8%)
-0.7%prior 1,436

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: 1,769
  • Total persons involved: 3,386
  • Total vehicles involved: 2,636

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