Yearly Traffic Safety Analysis

755 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Logan County recorded 755 total vehicle crashes, a 13.3% decrease from the 871 crashes reported in 2022. While total crashes and injuries (243 in 2023 vs. 287 in 2022) saw a decline, the number of fatalities increased slightly from 8 to 9. The most notable shift was the overall reduction in crash volume across most categories.

755

▼ -13.3%was 871

Total Crash Events

9

▲ 12.5%was 8

Persons Killed

243

▼ -15.3%was 287

Persons Injured

70

▼ -33.3%was 105

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety data for Logan County shows a downward trend in the overall number of crashes and related injuries year-over-year. Total crashes fell by 116 from 871 in 2022 to 755 in 2023, and total injuries decreased by 15.3% from 287 to 243. However, total fatalities saw a slight increase, rising from 8 to 9 over the same period.

70

Hit-and-Run Crashes — 2023

▼ -33.3% vs prior (105)

Hit-and-run incidents saw a notable decrease in both volume and rate. The total number of hit-and-run crashes fell from 105 in 2022 to 70 in 2023. This corresponds to a downward trend in the hit-and-run rate, which decreased from 12.1% of all crashes in 2022 to 9.3% in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

9

Motorists Killed

Prior: 8↑12.5%

6

Pedestrians Injured

Prior: 5↑20.0%

237

Motorists Injured

Prior: 282↓-16.0%

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 temporal patterns of crashes shifted between the two periods. In 2023, the peak day for crashes was Monday with 121 incidents, a change from 2022 when Thursday and Friday were the peak days with 141 crashes each. The peak hour for crashes remained consistent at 3 p.m. in both years, though the number of crashes during that hour dropped from 94 in 2022 to 68 in 2023.

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

While total crashes decreased, the severity profile showed mixed changes. The fatal crash rate increased from 0.92% in 2022 to 1.06% in 2023, with total fatalities rising from 8 to 9. The proportion of crashes resulting in serious injuries grew from 3.3% to 5.0% year-over-year. Conversely, crashes resulting in minor injuries decreased as a percentage of the total, from 13.2% in 2022 to 12.1% in 2023.

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

Outcome by Severity (Crash Events)

Fatal8fatal crashes1.1%
→0.0%prior 8
Serious Injury38serious injury crashes5%
↑31.0%prior 29
Minor Injury91minor injury crashes12.1%
↓-20.9%prior 115
Possible Injury41possible injury crashes5.4%
↓-12.8%prior 47
No Injury577no injury crashes76.4%
↓-14.1%prior 672

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

Year-over-year analysis indicates a shift in crash conditions. While the total number of crashes decreased, the proportion of incidents occurring in adverse weather increased; crashes in rain grew from 6.9% of the total in 2022 to 12.1% in 2023. Similarly, crashes on wet road surfaces accounted for 19.3% of all incidents in 2023, up from 16.0% in the prior year. The percentage of crashes occurring in daylight decreased from 65.8% in 2022 to 63.0% in 2023.

Weather

Clear449 (59.5%)
↓-18.1%prior 548
Cloudy135 (17.9%)
↓-15.1%prior 159
Rain91 (12.1%)
↑51.7%prior 60
Snow52 (6.9%)
↓-14.8%prior 61
Other/Unknown9 (1.2%)
↓-43.8%prior 16
Freezing Rain or Freezing Drizzle8 (1.1%)
↑60.0%prior 5
Fog; Smog; Smoke7 (0.9%)
↑16.7%prior 6
Sleet; Hail3 (0.4%)
↓-57.1%prior 7
Blowing Sand; Soil; Dirt; Snow1 (0.1%)
↓-83.3%prior 6

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

Lighting

Daylight476 (63.0%)
↓-16.9%prior 573
Dark - Roadway Not Lighted165 (21.9%)
↓-6.3%prior 176
Dark - Lighted Roadway60 (7.9%)
↑17.6%prior 51
Dawn/Dusk48 (6.4%)
↓-5.9%prior 51
Other/Unknown5 (0.7%)
↓-70.6%prior 17
Dark - Unknown Roadway Lighting1 (0.1%)

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

Road Surface

Dry546 (72.3%)
↓-14.3%prior 637
Wet146 (19.3%)
↑5.0%prior 139
Ice37 (4.9%)
↑12.1%prior 33
Snow25 (3.3%)
↓-56.1%prior 57
Other/Unknown1 (0.1%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes—Honda, Ford, and Chevrolet—remained the same in 2023 as in 2022, with counts for each decreasing in line with the overall trend. An analysis of persons involved shows a demographic shift; the 16-20 age group's representation increased from 12.3% of all persons in 2022 to 14.6% in 2023, even as the raw count remained stable at 220. In contrast, the 26-34 age group's share decreased from 15.7% to 14.4%.

Top Vehicle Makes (1,180 vehicles)

1
HONDA250 (21.2%)
↓-23.1%prior 325
2
FORD185 (15.7%)
↓-8.4%prior 202
3
CHEVROLET170 (14.4%)
↓-2.9%prior 175
4
TOYOTA70 (5.9%)
↑12.9%prior 62
5
DODGE46 (3.9%)
↓-29.2%prior 65
6
NISSAN40 (3.4%)
↓-4.8%prior 42
7
GMC34 (2.9%)
↓-24.4%prior 45
8
HYUNDAI33 (2.8%)
↓-31.3%prior 48
9
KIA29 (2.5%)
↓-21.6%prior 37
10
JEEP27 (2.3%)
↓-30.8%prior 39

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

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

Sex Distribution (1,460 persons with recorded sex)

Male854 (58.5%)
↓-11.0%prior 960
Female606 (41.5%)
↓-19.6%prior 754

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: 755
  • Total persons involved: 1,504
  • Total vehicles involved: 1,180

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

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