Yearly Traffic Safety Analysis

3,539 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Richland County recorded 3,539 total crashes, a 14.6% increase from the 3,089 crashes reported in 2024. Despite the rise in total collisions, the most notable year-over-year shift was a significant decrease in traffic fatalities, which fell from 16 in the prior period to 7 in the current period. This was accompanied by a substantial increase in the number of hit-and-run incidents.

3,539

14.6%was 3,089

Total Crash Events

7

-56.3%was 16

Persons Killed

1,194

8.0%was 1,106

Persons Injured

516

34.4%was 384

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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 crash trends in Richland County are rising year-over-year. Total collisions increased by 14.6%, from 3,089 in 2024 to 3,539 in 2025. This was accompanied by a 7.9% increase in the number of people injured, which rose from 1,106 to 1,194.

516

Hit-and-Run Crashes — 2025

34.4% vs prior (384)

Hit-and-run crashes showed a significant upward trend, increasing by 34.4% from 384 incidents in 2024 to 516 in 2025. This growth outpaced the overall rise in total crashes. As a result, the hit-and-run rate increased, accounting for 14.6% of all crashes in the current period, up from 12.4% in the prior period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 3-100.0%

7

Motorists Killed

Prior: 13-46.2%

18

Pedestrians Injured

Prior: 26-30.8%

1,176

Motorists Injured

Prior: 1,0808.9%

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 was the peak day for crashes in both 2024 (544 crashes) and 2025 (622 crashes). The peak hour for collisions shifted slightly later in the day, from the 3 p.m. hour in the prior period (237 crashes) to the 4 p.m. hour in the current period (273 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

While total crashes increased, their overall severity decreased year-over-year. The fatal crash rate fell from 0.49% in 2024 to 0.17% in 2025, with the number of fatal crashes dropping from 15 to 6. The proportion of crashes resulting in any type of injury (fatal, serious, minor, or possible) also declined, from 25.5% of all crashes in the prior period to 23.1% in the current period, while no-injury crashes increased from 74.5% to 76.9% of the total.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes0.2%
-60.0%prior 15
Serious Injury63serious injury crashes1.8%
1.6%prior 62
Minor Injury465minor injury crashes13.1%
5.0%prior 443
Possible Injury282possible injury crashes8%
5.6%prior 267
No Injury2,723no injury crashes76.9%
18.3%prior 2,302

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 daylight was stable, accounting for 62.3% of crashes in 2025 versus 60.7% in 2024. There was a notable increase in crashes occurring in adverse conditions, with the share of crashes in rain or snow rising from 18.5% to 23.0% year-over-year. Similarly, collisions on wet, snowy, or icy road surfaces increased from 26.4% of all crashes in the prior period to 32.7% in the current period.

Weather

Clear1,878 (53.1%)
7.3%prior 1,751
Cloudy823 (23.3%)
9.3%prior 753
Snow411 (11.6%)
140.4%prior 171
Rain355 (10.0%)
-3.0%prior 366
Fog; Smog; Smoke23 (0.6%)
15.0%prior 20
Other/Unknown22 (0.6%)
69.2%prior 13
Freezing Rain or Freezing Drizzle15 (0.4%)
114.3%prior 7
Sleet; Hail11 (0.3%)
57.1%prior 7
Blowing Sand; Soil; Dirt; Snow1 (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

Daylight2,204 (62.3%)
17.6%prior 1,874
Dark - Roadway Not Lighted732 (20.7%)
12.1%prior 653
Dark - Lighted Roadway355 (10.0%)
-3.3%prior 367
Dawn/Dusk214 (6.0%)
22.3%prior 175
Other/Unknown18 (0.5%)
38.5%prior 13
Dark - Unknown Roadway Lighting16 (0.5%)
128.6%prior 7

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

Road Surface

Dry2,331 (65.9%)
2.9%prior 2,266
Wet691 (19.5%)
9.0%prior 634
Snow353 (10.0%)
178.0%prior 127
Ice115 (3.2%)
202.6%prior 38
Slush34 (1.0%)
88.9%prior 18
Other/Unknown12 (0.3%)
100.0%prior 6
Water (Standing; Moving)2 (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 top vehicle makes involved in crashes remained consistent, led by Chevrolet (1,024 vehicles), Ford (766), and Honda (449) in 2025, mirroring the rankings from 2024. The most common vehicle types were Passenger Cars (2,352), Sport Utility Vehicles (1,641), and Pick-ups (808). The number of SUVs involved in crashes saw a marked increase from 1,224 in the prior year to 1,641 in the current year.

Top Vehicle Makes (5,649 vehicles)

1
CHEVROLET1,024 (18.1%)
20.3%prior 851
2
FORD766 (13.6%)
14.7%prior 668
3
HONDA449 (7.9%)
16.9%prior 384
4
TOYOTA363 (6.4%)
3.7%prior 350
5
JEEP299 (5.3%)
34.7%prior 222
6
DODGE289 (5.1%)
5.1%prior 275
7
KIA264 (4.7%)
14.8%prior 230
8
NISSAN234 (4.1%)
17.0%prior 200
9
HYUNDAI181 (3.2%)
4.6%prior 173
10
GMC180 (3.2%)
0.0%prior 180

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

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

Sex Distribution (6,985 persons with recorded sex)

Male3,876 (55.5%)
13.1%prior 3,427
Female3,109 (44.5%)
9.9%prior 2,828

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: 3,539
  • Total persons involved: 7,297
  • Total vehicles involved: 5,649

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