Yearly Traffic Safety Analysis

2,259 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Erie County, total traffic crashes increased by 9.9% from 2,055 in 2024 to 2,259 in 2025. This rise in collisions was accompanied by an increase in fatalities, which grew from 10 to 13 year-over-year. The most notable shift was a significant increase in crashes occurring on snowy and icy roads, with the count of such incidents more than doubling.

2,259

9.9%was 2,055

Total Crash Events

13

30.0%was 10

Persons Killed

686

0.9%was 680

Persons Injured

240

Hit-and-Run Crashes

Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) 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 safety trends in the county worsened year-over-year. Total crashes rose by 9.9% from 2,055 to 2,259. The number of people killed in these incidents increased by 30% from 10 to 13, while total injuries saw a slight increase from 680 to 686.

240

Hit-and-Run Crashes — 2025

0.0% vs prior (240)

The absolute number of hit-and-run crashes remained unchanged at 240 incidents in both the current and prior periods. However, due to the overall increase in total crashes in the current year, the hit-and-run rate showed a downward trend. The rate decreased from 11.7% of all crashes in the prior period to 10.6% in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

12

Motorists Killed

Prior: 1020.0%

15

Pedestrians Injured

Prior: 1225.0%

671

Motorists Injured

Prior: 6680.4%

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 showed some changes between the two periods. While Friday remained the peak day for crashes in both years, the number of incidents on Fridays increased from 317 to 389. The peak hour for crashes shifted two hours earlier, moving from 5 p.m. in the prior period (150 crashes) to 3 p.m. in the current period (168 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 the total number of crashes increased, the distribution of severity shifted slightly. The number of fatal crashes increased from 10 to 11, though the fatal crash rate remained stable at 0.5% of all crashes. The proportion of crashes involving any type of injury (serious, minor, or possible) decreased from 23.1% in the prior year to 21.5% in the current year, despite a small increase in the absolute number of injury crashes from 475 to 485.

Severity is per crash event (most severe injury). 11 fatal crash events resulted in 13 persons killed.

Outcome by Severity (Crash Events)

Fatal11fatal crashes0.5%
10.0%prior 10
Serious Injury59serious injury crashes2.6%
-4.8%prior 62
Minor Injury248minor injury crashes11%
5.1%prior 236
Possible Injury178possible injury crashes7.9%
0.6%prior 177
No Injury1,763no injury crashes78%
12.3%prior 1,570

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 notable shift in crash conditions year-over-year, particularly related to winter weather. While crashes on dry roads still constituted the majority, incidents on snowy roads increased from 76 to 144, and crashes on icy roads rose from 27 to 53. Consequently, the proportion of crashes occurring on dry surfaces fell from 79.0% to 76.8%. Crashes in daylight conditions remained proportionally stable, accounting for about 60% of incidents in both periods.

Weather

Clear1,442 (63.8%)
3.7%prior 1,390
Cloudy435 (19.3%)
20.8%prior 360
Rain188 (8.3%)
-0.5%prior 189
Snow144 (6.4%)
89.5%prior 76
Freezing Rain or Freezing Drizzle14 (0.6%)
180.0%prior 5
Other/Unknown10 (0.4%)
-50.0%prior 20
Fog; Smog; Smoke9 (0.4%)
-10.0%prior 10
Sleet; Hail8 (0.4%)
60.0%prior 5
Blowing Sand; Soil; Dirt; Snow6 (0.3%)
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

Daylight1,341 (59.4%)
8.5%prior 1,236
Dark - Roadway Not Lighted469 (20.8%)
13.8%prior 412
Dark - Lighted Roadway259 (11.5%)
5.3%prior 246
Dawn/Dusk156 (6.9%)
20.9%prior 129
Other/Unknown22 (1.0%)
10.0%prior 20
Dark - Unknown Roadway Lighting12 (0.5%)
0.0%prior 12

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

Road Surface

Dry1,736 (76.8%)
7.0%prior 1,623
Wet306 (13.5%)
-7.0%prior 329
Snow140 (6.2%)
169.2%prior 52
Ice53 (2.3%)
96.3%prior 27
Slush15 (0.7%)
150.0%prior 6
Other/Unknown7 (0.3%)
-53.3%prior 15
Sand; Mud; Dirt; Oil; Gravel1 (0.0%)
Water (Standing; Moving)1 (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 involved in crashes remained consistent year-over-year, with Ford (693), Chevrolet (587), and Honda (241) being the most common in the current period, reflecting similar rankings from the prior year. When examining the age of persons involved in crashes, all age groups saw an increase in numbers. Notably, the 16-20 age group increased from 536 to 619 persons involved, and the 0-15 group increased from 414 to 534.

Top Vehicle Makes (3,671 vehicles)

1
FORD693 (18.9%)
9.3%prior 634
2
CHEVROLET587 (16%)
7.3%prior 547
3
HONDA241 (6.6%)
10.0%prior 219
4
TOYOTA215 (5.9%)
20.1%prior 179
5
JEEP187 (5.1%)
3.3%prior 181
6
KIA164 (4.5%)
1.2%prior 162
7
DODGE154 (4.2%)
-3.8%prior 160
8
GMC112 (3.1%)
1.8%prior 110
9
HYUNDAI108 (2.9%)
-3.6%prior 112
10
NISSAN93 (2.5%)
17.7%prior 79

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

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

Sex Distribution (4,657 persons with recorded sex)

Male2,627 (56.4%)
16.7%prior 2,251
Female2,030 (43.6%)
4.7%prior 1,939

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: 2,259
  • Total persons involved: 4,863
  • Total vehicles involved: 3,671

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