Yearly Traffic Safety Analysis

589 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Holmes County recorded 589 total crashes, an 11.2% decrease from the 663 crashes reported in 2022. The most significant year-over-year change was a substantial reduction in traffic fatalities, which fell from 11 in 2022 to 4 in 2023. Total injuries also saw a decline, from 261 to 226.

589

-11.2%was 663

Total Crash Events

4

-63.6%was 11

Persons Killed

226

-13.4%was 261

Persons Injured

32

-20.0%was 40

Hit-and-Run Crashes

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Holmes County showed improvement from 2022 to 2023. Total crashes decreased by 11.2%, from 663 to 589. This downward trend was also reflected in crash outcomes, with total injuries declining by 13.4% and fatalities decreasing by 63.6%.

32

Hit-and-Run Crashes — 2023

-20.0% vs prior (40)

The number of hit-and-run incidents in Holmes County decreased from 40 in 2022 to 32 in 2023. The hit-and-run rate, which measures these incidents as a percentage of total crashes, also saw a slight decline. In 2023, hit-and-runs accounted for 5.4% of all crashes, down from 6.0% in the previous year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

4

Motorists Killed

Prior: 11-63.6%

1

Pedestrians Injured

Prior: 3-66.7%

225

Motorists Injured

Prior: 258-12.8%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak time for crashes in Holmes County remained consistent, with the 3 p.m. hour being the most frequent in both 2023 (50 crashes) and 2022 (63 crashes). However, the peak day for crashes shifted from Friday in 2022, which saw 123 incidents, to Thursday in 2023, with 103 incidents. Crash volumes were generally lower across all days of the week in 2023 compared to the prior year.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity decreased from 2022 to 2023. The number of fatal crashes fell from 9 to 3, and their proportion of all crashes dropped from 1.4% to 0.5%. Similarly, serious injury crashes decreased from 28 (4.2% of total) to 20 (3.4% of total). The proportion of crashes resulting in minor or possible injuries remained relatively stable, accounting for a combined 23.6% of crashes in 2023 compared to 22.4% in 2022.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.5%
-66.7%prior 9
Serious Injury20serious injury crashes3.4%
-28.6%prior 28
Minor Injury83minor injury crashes14.1%
-10.8%prior 93
Possible Injury56possible injury crashes9.5%
0.0%prior 56
No Injury427no injury crashes72.5%
-10.5%prior 477

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely consistent between 2022 and 2023. In both years, the vast majority of crashes occurred in daylight (66.4% in 2023 vs. 68.0% in 2022) and on dry roads (79.6% in 2023 vs. 77.4% in 2022). There were no significant shifts in the proportion of crashes occurring in adverse lighting or road surface conditions.

Weather

Clear362 (61.5%)
-8.8%prior 397
Cloudy137 (23.3%)
-14.4%prior 160
Rain52 (8.8%)
-16.1%prior 62
Snow23 (3.9%)
-17.9%prior 28
Fog; Smog; Smoke10 (1.7%)
-9.1%prior 11
Other/Unknown2 (0.3%)
Severe Crosswinds2 (0.3%)
Freezing Rain or Freezing Drizzle1 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight391 (66.4%)
-13.3%prior 451
Dark - Roadway Not Lighted156 (26.5%)
-3.1%prior 161
Dawn/Dusk21 (3.6%)
-8.7%prior 23
Dark - Lighted Roadway18 (3.1%)
-30.8%prior 26
Dark - Unknown Roadway Lighting3 (0.5%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry469 (79.6%)
-8.6%prior 513
Wet91 (15.4%)
-9.0%prior 100
Snow19 (3.2%)
-36.7%prior 30
Ice4 (0.7%)
-77.8%prior 18
Slush4 (0.7%)
Other/Unknown2 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

The types of vehicles involved in crashes were similar year-over-year, with Passenger Cars, Sport Utility Vehicles, and Pick-ups being the most common in both periods. The top five vehicle makes—Ford, Chevrolet, Honda, Dodge, and Toyota—also remained unchanged, though counts for each decreased in 2023, consistent with the overall drop in crashes. The age distribution of persons involved in crashes was also stable, with the 65+ and 16-20 age groups being the most represented in both 2022 and 2023.

Top Vehicle Makes (955 vehicles)

1
FORD182 (19.1%)
-6.7%prior 195
2
CHEVROLET141 (14.8%)
-18.0%prior 172
3
HONDA84 (8.8%)
-13.4%prior 97
4
DODGE73 (7.6%)
1.4%prior 72
5
TOYOTA51 (5.3%)
-15.0%prior 60
6
JEEP39 (4.1%)
-25.0%prior 52
7
GMC38 (4%)
-5.0%prior 40
8
NISSAN30 (3.1%)
-21.1%prior 38
9
KIA26 (2.7%)
-7.1%prior 28
10
HYUNDAI25 (2.6%)
47.1%prior 17

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (1,392 persons with recorded sex)

Male819 (58.8%)
-4.3%prior 856
Female573 (41.2%)
-3.0%prior 591

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 589
  • Total persons involved: 1,415
  • Total vehicles involved: 955

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: 2023." Published July 5, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2023-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

ThatCarHitMe.com · An Injuria.ai Company

Holmes County, OH Crash Report — 2023 | ThatCarHitMe.com