Yearly Traffic Safety Analysis

2,185 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Wayne County recorded 2,185 total crashes, a 14.6% increase from the 1,906 crashes reported in 2024. Despite the rise in total collisions, the number of fatalities decreased from 10 to 8, and total injuries fell from 862 to 776. The most notable shift was a significant increase in the volume of no-injury crashes, which rose from 1,306 in the prior year to 1,653 in the current year.

2,185

14.6%was 1,906

Total Crash Events

8

-20.0%was 10

Persons Killed

776

-10.0%was 862

Persons Injured

174

16.8%was 149

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

Traffic crashes in Wayne County trended upward, with total collisions increasing by 14.6% from 1,906 in 2024 to 2,185 in 2025. This represents an increase of 279 crashes year-over-year. In contrast to the rising crash volume, outcomes became less severe, with total fatalities declining from 10 to 8 and injuries dropping from 862 to 776.

174

Hit-and-Run Crashes — 2025

16.8% vs prior (149)

Hit-and-run incidents increased in both count and rate from the previous year. The total number of hit-and-run crashes rose from 149 in 2024 to 174 in 2025. This corresponds to a slight increase in the hit-and-run rate, which edged up from 7.8% to 8.0% of all crashes.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1100.0%

6

Motorists Killed

Prior: 9-33.3%

5

Pedestrians Injured

Prior: 18-72.2%

771

Motorists Injured

Prior: 844-8.6%

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 remained consistent year-over-year, with Friday being the peak day and 3 PM the peak hour in both 2025 and 2024. In 2025, 364 crashes occurred on Friday and 192 happened during the 3 PM hour. This compares to 355 crashes on Friday and 167 during the 3 PM hour in the previous year, indicating a higher volume of collisions during these peak times.

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, the severity of those crashes decreased in 2025 compared to 2024. The proportion of fatal crashes fell slightly from 0.5% to 0.4%, and serious injury crashes dropped from 3.7% to 2.6% of the total. The most significant change was the increase in no-injury crashes, which grew from representing 68.5% of all incidents in 2024 to 75.7% in 2025.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.4%
-20.0%prior 10
Serious Injury56serious injury crashes2.6%
-20.0%prior 70
Minor Injury313minor injury crashes14.3%
-15.2%prior 369
Possible Injury155possible injury crashes7.1%
2.6%prior 151
No Injury1,653no injury crashes75.7%
26.6%prior 1,306

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

There was a significant shift in the conditions under which crashes occurred, with a notable increase in incidents during adverse weather. Crashes in snow more than doubled, from 97 in 2024 to 221 in 2025, and collisions on snowy road surfaces more than tripled from 69 to 224. Consequently, the proportion of crashes on dry roads decreased from 77.0% in 2024 to 71.4% in 2025.

Weather

Clear1,129 (51.7%)
5.7%prior 1,068
Cloudy626 (28.6%)
19.0%prior 526
Snow221 (10.1%)
127.8%prior 97
Rain172 (7.9%)
-9.0%prior 189
Fog; Smog; Smoke11 (0.5%)
-21.4%prior 14
Sleet; Hail10 (0.5%)
66.7%prior 6
Other/Unknown7 (0.3%)
40.0%prior 5
Freezing Rain or Freezing Drizzle5 (0.2%)
Blowing Sand; Soil; Dirt; Snow4 (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

Daylight1,424 (65.2%)
12.4%prior 1,267
Dark - Roadway Not Lighted502 (23.0%)
17.6%prior 427
Dark - Lighted Roadway125 (5.7%)
0.8%prior 124
Dawn/Dusk124 (5.7%)
51.2%prior 82
Other/Unknown6 (0.3%)
Dark - Unknown Roadway Lighting4 (0.2%)

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

Road Surface

Dry1,560 (71.4%)
6.3%prior 1,467
Wet337 (15.4%)
-1.5%prior 342
Snow224 (10.3%)
224.6%prior 69
Ice47 (2.2%)
176.5%prior 17
Slush16 (0.7%)
77.8%prior 9
Other/Unknown1 (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 makes of vehicles most frequently involved in crashes remained stable, with Ford (595), Chevrolet (506), and Honda (333) being the top three in 2025, consistent with the prior year's rankings. Analysis of person demographics shows an increase in crash involvement for most adult age groups, particularly the 26-34 and 35-44 brackets. Conversely, the number of individuals aged 16-20 involved in crashes saw a slight decrease from 638 to 627.

Top Vehicle Makes (3,526 vehicles)

1
FORD595 (16.9%)
12.9%prior 527
2
CHEVROLET506 (14.4%)
7.4%prior 471
3
HONDA333 (9.4%)
23.3%prior 270
4
TOYOTA275 (7.8%)
9.1%prior 252
5
DODGE176 (5%)
-9.7%prior 195
6
JEEP162 (4.6%)
7.3%prior 151
7
GMC131 (3.7%)
65.8%prior 79
8
KIA127 (3.6%)
10.4%prior 115
9
NISSAN113 (3.2%)
5.6%prior 107
10
HYUNDAI108 (3.1%)
31.7%prior 82

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

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

Sex Distribution (4,498 persons with recorded sex)

Male2,613 (58.1%)
13.9%prior 2,294
Female1,885 (41.9%)
4.7%prior 1,800

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: 2,185
  • Total persons involved: 4,599
  • Total vehicles involved: 3,526

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