Yearly Traffic Safety Analysis

881 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Morrow County recorded 881 total traffic crashes, a 2.0% increase from the 864 crashes in 2022. While total crashes and injuries saw a slight rise, the most significant year-over-year change was a 50% reduction in traffic fatalities, which fell from 10 in 2022 to 5 in 2023.

881

2.0%was 864

Total Crash Events

5

-50.0%was 10

Persons Killed

340

6.6%was 319

Persons Injured

69

-12.7%was 79

Hit-and-Run Crashes

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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

Overall traffic safety trends in Morrow County were mixed year-over-year. Total crashes increased slightly from 864 to 881, and total injuries rose from 319 to 340. However, these increases were countered by a substantial improvement in fatal outcomes, with total fatalities dropping by half from 10 to 5.

69

Hit-and-Run Crashes — 2023

-12.7% vs prior (79)

Hit-and-run crashes trended downward between the two periods. The absolute number of such incidents decreased from 79 in 2022 to 69 in 2023. Consequently, the hit-and-run rate, representing the percentage of all crashes that were hit-and-runs, also declined from 9.1% to 7.8%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

5

Motorists Killed

Prior: 10-50.0%

4

Pedestrians Injured

Prior: 40.0%

336

Motorists Injured

Prior: 3156.7%

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 remained largely consistent between the two periods. Friday was the peak day for crashes in both 2022 (160 crashes) and 2023 (153 crashes). The peak hour for collisions shifted slightly from 6 PM in 2022 to 5 PM in 2023, with both hours marking the height of the evening commute.

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 saw a notable improvement, with the fatal crash rate decreasing from 1.04% in 2022 to 0.57% in 2023. The number of fatal crashes fell from 9 to 5. However, the proportion of crashes resulting in some form of injury increased, with serious injury crashes rising from 2.7% to 3.2% of all incidents and minor injury crashes increasing from 16.6% to 17.9%.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.6%
-44.4%prior 9
Serious Injury28serious injury crashes3.2%
21.7%prior 23
Minor Injury158minor injury crashes17.9%
10.5%prior 143
Possible Injury51possible injury crashes5.8%
24.4%prior 41
No Injury639no injury crashes72.5%
-1.4%prior 648

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 conditions under which crashes occurred shifted significantly, particularly concerning winter weather. Crashes on snowy roads decreased from 65 to 19, and collisions in snowy weather fell from 66 to 35. In contrast, crashes on wet roads increased from 136 to 167. The distribution of crashes by lighting conditions remained stable, with daylight crashes accounting for 57.1% of incidents in 2023 versus 56.1% in 2022.

Weather

Clear568 (64.5%)
6.8%prior 532
Cloudy175 (19.9%)
2.3%prior 171
Rain93 (10.6%)
20.8%prior 77
Snow35 (4.0%)
-47.0%prior 66
Fog; Smog; Smoke8 (0.9%)
14.3%prior 7
Other/Unknown1 (0.1%)
Sleet; Hail1 (0.1%)

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

Lighting

Daylight503 (57.1%)
3.7%prior 485
Dark - Roadway Not Lighted319 (36.2%)
6.3%prior 300
Dawn/Dusk43 (4.9%)
-28.3%prior 60
Dark - Lighted Roadway15 (1.7%)
-11.8%prior 17
Other/Unknown1 (0.1%)

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

Road Surface

Dry688 (78.1%)
7.8%prior 638
Wet167 (19.0%)
22.8%prior 136
Snow19 (2.2%)
-70.8%prior 65
Ice5 (0.6%)
-72.2%prior 18
Other/Unknown1 (0.1%)
Sand; Mud; Dirt; Oil; Gravel1 (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 makes of vehicles involved in crashes saw a slight change at the top, with Ford (217 vehicles) overtaking Chevrolet (214 vehicles) as the most frequently involved make in 2023. There was also a notable shift in the age of persons involved in crashes; the proportion of individuals aged 16-20 decreased from 13.4% to 11.7% year-over-year, while the 65+ age group's representation increased from 8.9% to 11.6%.

Top Vehicle Makes (1,261 vehicles)

1
FORD217 (17.2%)
19.9%prior 181
2
CHEVROLET214 (17%)
15.1%prior 186
3
HONDA117 (9.3%)
-4.1%prior 122
4
TOYOTA89 (7.1%)
-12.7%prior 102
5
DODGE80 (6.3%)
25.0%prior 64
6
JEEP47 (3.7%)
-11.3%prior 53
7
NISSAN41 (3.3%)
-4.7%prior 43
8
HYUNDAI38 (3%)
-25.5%prior 51
9
KIA37 (2.9%)
-19.6%prior 46
10
GMC32 (2.5%)
3.2%prior 31

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

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

Sex Distribution (1,722 persons with recorded sex)

Male1,041 (60.5%)
-3.0%prior 1,073
Female681 (39.5%)
2.4%prior 665

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 6, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 881
  • Total persons involved: 1,762
  • Total vehicles involved: 1,261

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 6, 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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Morrow County, OH Crash Report — 2023 | ThatCarHitMe.com