Yearly Traffic Safety Analysis

793 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In Jackson County, total vehicle crashes decreased by approximately 2%, from 809 incidents in 2022 to 793 in 2023. While overall crash volume saw a minor decline, the most significant year-over-year change was a 60% reduction in traffic fatalities, which fell from five in the prior period to two in the current period. The total number of injuries reported remained unchanged at 252 for both years.

793

-2.0%was 809

Total Crash Events

2

-60.0%was 5

Persons Killed

252

Persons Injured

74

10.4%was 67

Hit-and-Run Crashes

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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

The overall crash trend in Jackson County shows a slight decrease in volume, with total crashes falling by 16 incidents (-2.0%) from 2022 to 2023. This was accompanied by a notable drop in fatalities from 5 to 2. However, the total number of individuals injured in crashes was identical in both years at 252, indicating stability in non-fatal injury outcomes despite fewer total and fatal crashes.

74

Hit-and-Run Crashes — 2023

10.4% vs prior (67)

Hit-and-run incidents showed an upward trend in Jackson County. The absolute number of hit-and-run crashes increased from 67 in 2022 to 74 in 2023. Correspondingly, the hit-and-run rate, which measures these incidents as a percentage of all crashes, also rose from 8.3% in the prior year to 9.3% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

2

Motorists Killed

Prior: 5-60.0%

3

Pedestrians Injured

Prior: 1200.0%

249

Motorists Injured

Prior: 251-0.8%

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 temporal patterns of crashes in Jackson County were highly consistent year-over-year. In both 2023 and 2022, Friday was the most frequent day for crashes, with 148 and 138 incidents respectively. Similarly, the 3 p.m. hour was the peak time for collisions in both periods, accounting for 58 crashes in 2023 and 59 in 2022, showing no significant shift in when crashes occurred.

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 outcomes improved, with fatal crashes decreasing from 5 in 2022 to 2 in 2023, and the corresponding fatal crash rate falling from 0.62% to 0.25%. The proportion of crashes resulting in no injuries increased slightly from 76.4% to 77.2%. Within injury categories, serious injury crashes saw a small increase from 13 to 16 incidents, while minor injury crashes decreased from 138 to 124.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.3%
-60.0%prior 5
Serious Injury16serious injury crashes2%
23.1%prior 13
Minor Injury124minor injury crashes15.6%
-10.1%prior 138
Possible Injury39possible injury crashes4.9%
11.4%prior 35
No Injury612no injury crashes77.2%
-1.0%prior 618

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 environmental conditions shifted slightly between the two periods. In 2023, a larger share of crashes occurred on dry roads (82.2%) compared to 2022 (75.6%), while the proportion of crashes on wet roads declined from 19.5% to 16.6%. Similarly, crashes in clear weather constituted a larger percentage of the total in 2023 (68.1%) than in 2022 (57.5%), suggesting a lower incidence of crashes in adverse weather conditions in the more recent period.

Weather

Clear540 (68.1%)
16.1%prior 465
Cloudy146 (18.4%)
-33.0%prior 218
Rain91 (11.5%)
1.1%prior 90
Other/Unknown6 (0.8%)
Fog; Smog; Smoke5 (0.6%)
-16.7%prior 6
Snow4 (0.5%)
-81.8%prior 22
Severe Crosswinds1 (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

Daylight465 (58.6%)
3.8%prior 448
Dark - Roadway Not Lighted232 (29.3%)
-10.1%prior 258
Dark - Lighted Roadway52 (6.6%)
-1.9%prior 53
Dawn/Dusk38 (4.8%)
-13.6%prior 44
Other/Unknown4 (0.5%)
Dark - Unknown Roadway Lighting2 (0.3%)
-60.0%prior 5

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

Road Surface

Dry652 (82.2%)
6.5%prior 612
Wet132 (16.6%)
-16.5%prior 158
Ice3 (0.4%)
-50.0%prior 6
Snow3 (0.4%)
-88.5%prior 26
Other/Unknown2 (0.3%)
Slush1 (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 types involved in crashes—Passenger Cars, Sport Utility Vehicles, and Pickups—remained the same across both years, though the count of passenger cars decreased from 554 to 467. The top two vehicle makes, Ford and Chevrolet, also held their positions. In 2023, Dodge (84 vehicles) replaced Honda (77 vehicles) as the third most common make involved in crashes, compared to 2022 when Honda ranked third with 98 vehicles. The 35-44 age group was the most represented among persons involved in crashes in 2023, replacing the 26-34 age group from the prior year.

Top Vehicle Makes (1,169 vehicles)

1
FORD217 (18.6%)
-3.1%prior 224
2
CHEVROLET178 (15.2%)
-2.2%prior 182
3
DODGE84 (7.2%)
-12.5%prior 96
4
TOYOTA83 (7.1%)
16.9%prior 71
5
HONDA77 (6.6%)
-21.4%prior 98
6
KIA61 (5.2%)
7.0%prior 57
7
JEEP55 (4.7%)
7.8%prior 51
8
HYUNDAI52 (4.4%)
-22.4%prior 67
9
NISSAN50 (4.3%)
-18.0%prior 61
10
GMC40 (3.4%)
-9.1%prior 44

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

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

Sex Distribution (1,502 persons with recorded sex)

Male830 (55.3%)
0.0%prior 830
Female672 (44.7%)
-5.1%prior 708

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: 793
  • Total persons involved: 1,552
  • Total vehicles involved: 1,169

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