Yearly Traffic Safety Analysis

1,071 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Shelby County recorded 1,071 total crashes, a 19.4% decrease from the 1,329 crashes reported in 2022. During this period, total fatalities also decreased from 8 to 5. A notable change was the significant reduction in speeding-related crashes, which fell from 239 in the prior period to 142 in the current period.

1,071

▼ -19.4%was 1,329

Total Crash Events

5

▼ -37.5%was 8

Persons Killed

262

▼ -12.7%was 300

Persons Injured

160

▲ 26.0%was 127

Hit-and-Run Crashes

Note: "Persons Killed" (5) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Shelby County showed a significant downward trend year-over-year. Total crashes fell by 19.4%, from 1,329 in 2022 to 1,071 in 2023. This trend was consistent across severity, with total injuries decreasing by 12.7% (from 300 to 262) and fatalities dropping from 8 to 5.

160

Hit-and-Run Crashes — 2023

▲ 26.0% vs prior (127)

Hit-and-run incidents increased notably in Shelby County year-over-year, both in absolute numbers and as a percentage of total crashes. The number of hit-and-run crashes rose from 127 in 2022 to 160 in 2023. This represents a substantial increase in the hit-and-run rate, which climbed from 9.6% of all crashes in the prior period to 14.9% in the current period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 8↓-37.5%

2

Pedestrians Injured

Prior: 7↓-71.4%

260

Motorists Injured

Prior: 293↓-11.3%

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 in Shelby County remained consistent year-over-year, though the volume of incidents decreased. Friday continued to be the peak day for crashes in 2023 with 189 incidents, down from 263 on Fridays in the prior year. Similarly, the 3 p.m. hour remained the peak time for crashes in both periods, with 100 crashes in 2023 compared to 114 in 2022.

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

The number of fatal crashes in Shelby County decreased from 5 in 2022 to 4 in 2023, while the fatal crash rate remained stable at approximately 0.4% of all crashes. While total injuries declined, the proportion of crashes resulting in serious injury increased from 1.5% to 2.3% of all incidents, with the count rising from 20 to 25. Crashes with possible injuries decreased from 72 in 2022 to 53 in 2023.

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.4%
↓-20.0%prior 5
Serious Injury25serious injury crashes2.3%
↑25.0%prior 20
Minor Injury121minor injury crashes11.3%
↓-4.7%prior 127
Possible Injury53possible injury crashes4.9%
↓-26.4%prior 72
No Injury868no injury crashes81%
↓-21.4%prior 1,105

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 lighting and weather conditions remained relatively stable between the two periods, with most incidents occurring in daylight (61.0% in 2023 vs. 57.4% in 2022) and clear weather (59.5% in 2023 vs. 57.5% in 2022). A significant change was observed in crashes related to adverse road surfaces. Crashes on icy roads decreased from 122 in 2022 to 23 in 2023, and crashes in snow fell from 119 to 32.

Weather

Clear637 (59.5%)
↓-16.6%prior 764
Cloudy240 (22.4%)
↓-10.1%prior 267
Rain121 (11.3%)
↑22.2%prior 99
Snow32 (3.0%)
↓-73.1%prior 119
Other/Unknown24 (2.2%)
↑4.3%prior 23
Fog; Smog; Smoke13 (1.2%)
↑18.2%prior 11
Freezing Rain or Freezing Drizzle3 (0.3%)
↓-81.3%prior 16
Severe Crosswinds1 (0.1%)
↓-85.7%prior 7

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

Lighting

Daylight653 (61.0%)
↓-14.4%prior 763
Dark - Roadway Not Lighted219 (20.4%)
↓-37.2%prior 349
Dark - Lighted Roadway98 (9.2%)
↓-10.1%prior 109
Dawn/Dusk71 (6.6%)
↓-16.5%prior 85
Other/Unknown22 (2.1%)
↑4.8%prior 21
Dark - Unknown Roadway Lighting8 (0.7%)

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

Road Surface

Dry811 (75.7%)
↓-12.8%prior 930
Wet198 (18.5%)
↑7.6%prior 184
Ice23 (2.1%)
↓-81.1%prior 122
Other/Unknown20 (1.9%)
↓-9.1%prior 22
Snow17 (1.6%)
↓-75.0%prior 68
Slush1 (0.1%)
Water (Standing; Moving)1 (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 remained Chevrolet, Ford, and Honda, though their order shifted. In 2023, Chevrolet was the most common make with 277 vehicles, followed by Ford with 264; this reverses the 2022 ranking where Ford led with 319 vehicles. The 26-34 age group represented the largest number of persons involved in crashes in both periods, though their count decreased from 421 to 306. The 16-20 age group became the second-most represented demographic in 2023, with 290 individuals involved in crashes.

Top Vehicle Makes (1,770 vehicles)

1
CHEVROLET277 (15.6%)
↓-9.5%prior 306
2
FORD264 (14.9%)
↓-17.2%prior 319
3
HONDA207 (11.7%)
↓-20.4%prior 260
4
DODGE115 (6.5%)
↓-7.3%prior 124
5
TOYOTA76 (4.3%)
↓-29.6%prior 108
6
GMC69 (3.9%)
↓-14.8%prior 81
7
JEEP65 (3.7%)
↓-3.0%prior 67
8
NISSAN61 (3.4%)
↓-12.9%prior 70
9
CHRYSLER61 (3.4%)
↓-9.0%prior 67
10
KIA51 (2.9%)
↓-15.0%prior 60

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

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

Sex Distribution (2,086 persons with recorded sex)

Male1,203 (57.7%)
↓-16.7%prior 1,444
Female883 (42.3%)
↓-18.5%prior 1,083

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: 1,071
  • Total persons involved: 2,220
  • Total vehicles involved: 1,770

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