Yearly Traffic Safety Analysis

5,985 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In Lorain County, total traffic crashes increased by 11.1% from 5,387 in the prior year to 5,985 in the current year. While the number of crashes and injuries rose, the most notable shift was a 21.4% decrease in traffic fatalities, which fell from 28 to 22. The overall crash severity rate also declined, with a higher proportion of incidents resulting in no injuries compared to the previous year.

5,985

11.1%was 5,387

Total Crash Events

22

-21.4%was 28

Persons Killed

2,151

4.6%was 2,056

Persons Injured

746

5.7%was 706

Hit-and-Run Crashes

Note: "Persons Killed" (22) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) 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 crash trends in Lorain County show an increase year-over-year. Total crashes rose by 11.1%, from 5,387 to 5,985. The number of people injured also increased by 4.6% to 2,151, though the number of fatalities decreased from 28 to 22.

746

Hit-and-Run Crashes — 2025

5.7% vs prior (706)

The total number of hit-and-run crashes increased from 706 to 746 year-over-year. However, because total crashes increased at a faster pace, the hit-and-run rate as a percentage of all crashes trended downward, decreasing from 13.1% in the prior period to 12.5% in the current period.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 5-20.0%

18

Motorists Killed

Prior: 23-21.7%

37

Pedestrians Injured

Prior: 40-7.5%

2,114

Motorists Injured

Prior: 2,0164.9%

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

While the peak hour for crashes remained 3 p.m. in both periods, the peak day shifted from Friday (931 crashes) in the prior year to Thursday (983 crashes) in the current year. Weekday crash volumes, particularly on Mondays and Tuesdays, saw notable increases, while Friday's total remained relatively stable.

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 severity of crashes decreased year-over-year. The fatal crash rate fell from 0.5% to 0.4% of all incidents, with 21 fatal crashes in the current period compared to 27 in the prior. The proportion of crashes resulting in any type of injury also decreased from 26.8% to 24.4%, while no-injury crashes increased their share from 72.6% to 75.3% of the total.

Severity is per crash event (most severe injury). 21 fatal crash events resulted in 22 persons killed.

Outcome by Severity (Crash Events)

Fatal21fatal crashes0.4%
-22.2%prior 27
Serious Injury135serious injury crashes2.3%
-10.6%prior 151
Minor Injury724minor injury crashes12.1%
12.8%prior 642
Possible Injury599possible injury crashes10%
-8.4%prior 654
No Injury4,506no injury crashes75.3%
15.2%prior 3,913

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 distribution of crash conditions saw a notable shift toward more incidents in adverse winter weather. The proportion of crashes occurring on snowy or icy road surfaces increased from a combined 5.0% in the prior year to 9.7% in the current year. Correspondingly, crashes on dry roads decreased as a share of the total from 76.0% to 72.5%.

Weather

Clear3,462 (57.8%)
5.4%prior 3,286
Cloudy1,400 (23.4%)
18.2%prior 1,184
Rain516 (8.6%)
-10.1%prior 574
Snow513 (8.6%)
88.6%prior 272
Other/Unknown30 (0.5%)
87.5%prior 16
Sleet; Hail23 (0.4%)
21.1%prior 19
Freezing Rain or Freezing Drizzle21 (0.4%)
200.0%prior 7
Fog; Smog; Smoke14 (0.2%)
-46.2%prior 26
Blowing Sand; Soil; Dirt; Snow6 (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

Daylight3,905 (65.2%)
9.7%prior 3,559
Dark - Lighted Roadway1,005 (16.8%)
18.7%prior 847
Dark - Roadway Not Lighted663 (11.1%)
6.9%prior 620
Dawn/Dusk355 (5.9%)
10.9%prior 320
Dark - Unknown Roadway Lighting40 (0.7%)
90.5%prior 21
Other/Unknown17 (0.3%)
-15.0%prior 20

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

Road Surface

Dry4,339 (72.5%)
6.0%prior 4,093
Wet1,023 (17.1%)
2.9%prior 994
Snow459 (7.7%)
109.6%prior 219
Ice120 (2.0%)
140.0%prior 50
Slush25 (0.4%)
19.0%prior 21
Other/Unknown18 (0.3%)
100.0%prior 9
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 top five vehicle makes involved in crashes—Ford, Chevrolet, Honda, Toyota, and Kia—remained unchanged between the two periods, with counts for each increasing in line with the overall rise in collisions. Similarly, the age distribution of persons involved in crashes was stable, with the 26-34 age group representing the largest cohort in both years at approximately 15% of the total.

Top Vehicle Makes (10,646 vehicles)

1
FORD1,997 (18.8%)
6.7%prior 1,871
2
CHEVROLET1,431 (13.4%)
9.0%prior 1,313
3
HONDA758 (7.1%)
10.8%prior 684
4
TOYOTA711 (6.7%)
7.4%prior 662
5
KIA597 (5.6%)
17.5%prior 508
6
NISSAN486 (4.6%)
6.6%prior 456
7
JEEP463 (4.3%)
6.4%prior 435
8
DODGE423 (4%)
5.5%prior 401
9
HYUNDAI404 (3.8%)
21.3%prior 333
10
GMC331 (3.1%)
24.9%prior 265

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

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

Sex Distribution (13,355 persons with recorded sex)

Male7,232 (54.2%)
14.1%prior 6,339
Female6,123 (45.8%)
10.0%prior 5,565

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: 5,985
  • Total persons involved: 13,794
  • Total vehicles involved: 10,646

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