Yearly Traffic Safety Analysis

641 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Hardin County recorded 641 total crashes, a 5.7% decrease from the 680 crashes reported in 2024. Despite the overall decline in collisions, the number of fatalities doubled, increasing from 2 in the prior year to 4 in the current year.

641

-5.7%was 680

Total Crash Events

4

100.0%was 2

Persons Killed

149

-19.0%was 184

Persons Injured

42

-25.0%was 56

Hit-and-Run Crashes

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

The overall trend in traffic collisions in Hardin County shows a year-over-year decrease. Total crashes fell by 5.7%, from 680 in 2024 to 641 in 2025. This decline was also reflected in the number of people injured, which decreased by 19.0% from 184 to 149.

42

Hit-and-Run Crashes — 2025

-25.0% vs prior (56)

The number of hit-and-run incidents in Hardin County saw a notable decrease in 2025. There were 42 hit-and-run crashes, down from 56 in the previous year. This represents a decline in the hit-and-run rate from 8.2% of all crashes in 2024 to 6.6% in 2025.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

4

Motorists Killed

Prior: 2100.0%

4

Pedestrians Injured

Prior: 333.3%

145

Motorists Injured

Prior: 181-19.9%

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 showed a notable shift between the two periods. While Friday remained the peak day for crashes in both 2025 (129 crashes) and 2024 (126 crashes), the peak hour changed significantly. In 2025, the highest number of crashes occurred at 7a with 48 incidents, shifting from the prior year's peak at 3p which saw 52 incidents.

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 decreased, the severity of crashes worsened in 2025. The number of fatal crashes doubled from 2 to 4, and the corresponding fatality rate rose from 0.29% to 0.62%. The proportion of serious injury crashes also declined from 2.9% to 1.9% of all incidents. Conversely, crashes resulting in no injury comprised a larger share of the total, increasing from 81.5% in 2024 to 84.6% in 2025.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.6%
100.0%prior 2
Serious Injury12serious injury crashes1.9%
-40.0%prior 20
Minor Injury46minor injury crashes7.2%
-37.0%prior 73
Possible Injury37possible injury crashes5.8%
19.4%prior 31
No Injury542no injury crashes84.6%
-2.2%prior 554

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 adverse weather and road conditions increased in 2025 compared to the previous year. Crashes in snowy weather rose from 32 to 53 incidents, and crashes on snowy or icy road surfaces increased from a combined 43 incidents in 2024 to 84 in 2025. Conversely, crashes on dry roads decreased from 532 to 473. Lighting conditions remained relatively consistent, with about half of all crashes in both years occurring during daylight.

Weather

Clear441 (68.8%)
-10.9%prior 495
Cloudy97 (15.1%)
18.3%prior 82
Snow53 (8.3%)
65.6%prior 32
Rain34 (5.3%)
-34.6%prior 52
Fog; Smog; Smoke10 (1.6%)
-16.7%prior 12
Freezing Rain or Freezing Drizzle2 (0.3%)
Severe Crosswinds2 (0.3%)
Sleet; Hail1 (0.2%)
Blowing Sand; Soil; Dirt; Snow1 (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

Daylight325 (50.7%)
-7.1%prior 350
Dark - Roadway Not Lighted210 (32.8%)
-1.9%prior 214
Dawn/Dusk64 (10.0%)
42.2%prior 45
Dark - Lighted Roadway33 (5.1%)
-19.5%prior 41
Dark - Unknown Roadway Lighting8 (1.2%)
-65.2%prior 23
Other/Unknown1 (0.2%)
-85.7%prior 7

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

Road Surface

Dry473 (73.8%)
-11.1%prior 532
Wet81 (12.6%)
-20.6%prior 102
Snow47 (7.3%)
88.0%prior 25
Ice37 (5.8%)
105.6%prior 18
Slush2 (0.3%)
Sand; Mud; Dirt; Oil; Gravel1 (0.2%)

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

Vehicles & Demographics

The types of vehicles involved in crashes remained stable year-over-year, with Chevrolet and Ford tied as the most common makes in 2025 (148 vehicles each), followed by Honda (133 vehicles). This ranking is similar to 2024, where Ford led with 154 vehicles. Analysis of persons involved shows a shift in age demographics, with a notable decrease in the proportion of individuals aged 0-15 (from 9.3% to 5.1%) and an increase in the proportion of those aged 26-34 (from 12.9% to 17.0%).

Top Vehicle Makes (957 vehicles)

1
CHEVROLET148 (15.5%)
0.0%prior 148
2
FORD148 (15.5%)
-3.9%prior 154
3
HONDA133 (13.9%)
0.0%prior 133
4
TOYOTA60 (6.3%)
7.1%prior 56
5
DODGE48 (5%)
-36.0%prior 75
6
KIA42 (4.4%)
13.5%prior 37
7
GMC40 (4.2%)
0.0%prior 40
8
JEEP35 (3.7%)
-2.8%prior 36
9
NISSAN29 (3%)
-17.1%prior 35
10
CHRYSLER26 (2.7%)
23.8%prior 21

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

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

Sex Distribution (1,084 persons with recorded sex)

Male650 (60.0%)
-2.0%prior 663
Female434 (40.0%)
-17.0%prior 523

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: 641
  • Total persons involved: 1,103
  • Total vehicles involved: 957

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