Yearly Traffic Safety Analysis

1,074 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Auglaize County recorded 1,074 total crashes, a 5.0% increase from the 1,023 crashes reported in 2024. While total crashes increased, the most significant year-over-year change was the rise in crash severity. The number of fatal crashes increased from 6 to 8, and serious injury crashes rose from 16 to 30.

1,074

▲ 5.0%was 1,023

Total Crash Events

9

▲ 50.0%was 6

Persons Killed

269

▼ -10.9%was 302

Persons Injured

109

▲ 28.2%was 85

Hit-and-Run Crashes

Note: "Persons Killed" (9) 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

Overall, traffic crashes in Auglaize County trended upward in 2025 compared to the previous year, with the total number of incidents increasing by 5.0% from 1,023 to 1,074. Despite a 10.9% decrease in the total number of people injured (from 302 to 269), the number of people killed in crashes rose by 50% from 6 to 9.

109

Hit-and-Run Crashes — 2025

▲ 28.2% vs prior (85)

Hit-and-run crashes increased in both absolute numbers and as a percentage of total crashes. The number of incidents rose from 85 in 2024 to 109 in 2025, a 28.2% increase. This pushed the hit-and-run rate up from 8.3% of all crashes in the prior year to 10.1% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

9

Motorists Killed

Prior: 6↑50.0%

4

Pedestrians Injured

Prior: 6↓-33.3%

265

Motorists Injured

Prior: 296↓-10.5%

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

Temporal crash patterns shifted between the two periods. In 2025, the peak day for crashes was Monday with 166 incidents, a change from Friday, which was the peak day with 198 incidents in 2024. The peak hour for collisions also shifted later in the day, from 3 p.m. in the prior year (88 crashes) to 6 p.m. in the current year (80 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

Crash severity increased in 2025 compared to the prior year. The number of fatal crashes rose from 6 to 8, and the corresponding fatal crash rate increased from 0.59% to 0.74%. The proportion of serious injury crashes also grew substantially, accounting for 30 incidents (2.8% of all crashes) in 2025, up from 16 incidents (1.6% of all crashes) in 2024.

Severity is per crash event (most severe injury). 8 fatal crash events resulted in 9 persons killed.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.7%
↑33.3%prior 6
Serious Injury30serious injury crashes2.8%
↑87.5%prior 16
Minor Injury90minor injury crashes8.4%
↓-23.1%prior 117
Possible Injury64possible injury crashes6%
↓-13.5%prior 74
No Injury882no injury crashes82.1%
↑8.9%prior 810

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 conditions surrounding crashes showed notable changes year-over-year. The proportion of crashes occurring in daylight decreased from 54.9% to 51.4%, while crashes in unlit dark conditions increased from 27.8% to 32.3% of the total. Collisions on snowy roads more than doubled from 29 to 87, and crashes on icy surfaces also doubled from 15 to 30, indicating a greater impact from winter conditions in 2025.

Weather

Clear640 (59.6%)
↓-1.4%prior 649
Cloudy264 (24.6%)
↑9.1%prior 242
Snow77 (7.2%)
↑126.5%prior 34
Rain69 (6.4%)
↓-2.8%prior 71
Fog; Smog; Smoke10 (0.9%)
↓-16.7%prior 12
Other/Unknown9 (0.8%)
↑80.0%prior 5
Freezing Rain or Freezing Drizzle2 (0.2%)
Severe Crosswinds2 (0.2%)
Sleet; Hail1 (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

Daylight552 (51.4%)
↓-1.8%prior 562
Dark - Roadway Not Lighted347 (32.3%)
↑22.2%prior 284
Dark - Lighted Roadway84 (7.8%)
↓-1.2%prior 85
Dawn/Dusk76 (7.1%)
↓-5.0%prior 80
Other/Unknown11 (1.0%)
↑83.3%prior 6
Dark - Unknown Roadway Lighting4 (0.4%)
↓-33.3%prior 6

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

Road Surface

Dry801 (74.6%)
↓-1.8%prior 816
Wet149 (13.9%)
↓-2.6%prior 153
Snow87 (8.1%)
↑200.0%prior 29
Ice30 (2.8%)
↑100.0%prior 15
Other/Unknown5 (0.5%)
→0.0%prior 5
Slush2 (0.2%)
↓-60.0%prior 5

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

Vehicles & Demographics

The rankings of the most frequently involved vehicle makes shifted, with Ford (266 vehicles) becoming the most common in 2025, surpassing Chevrolet (226 vehicles), which held the top spot in 2024. In terms of person demographics, the proportion of individuals aged 26-34 involved in crashes increased from 12.0% in 2024 to 14.0% in 2025. The 65+ age group also saw a proportional increase, rising from 14.0% to 15.1% of all persons involved.

Top Vehicle Makes (1,603 vehicles)

1
FORD266 (16.6%)
↑14.7%prior 232
2
CHEVROLET226 (14.1%)
↓-11.4%prior 255
3
HONDA172 (10.7%)
↓-5.5%prior 182
4
DODGE87 (5.4%)
↓-1.1%prior 88
5
TOYOTA87 (5.4%)
↑6.1%prior 82
6
GMC78 (4.9%)
→0.0%prior 78
7
JEEP72 (4.5%)
↑10.8%prior 65
8
NISSAN53 (3.3%)
↑35.9%prior 39
9
HYUNDAI51 (3.2%)
↑6.3%prior 48
10
KIA45 (2.8%)
↓-10.0%prior 50

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

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

Sex Distribution (1,927 persons with recorded sex)

Male1,112 (57.7%)
↓-3.6%prior 1,153
Female815 (42.3%)
↓-4.2%prior 851

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: 1,074
  • Total persons involved: 2,005
  • Total vehicles involved: 1,603

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