ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · 2023
Purpose: Machine-readable JSON endpoint for AI agents, LLMs, researchers, and programmatic consumers. Returns all underlying crash data and AI-generated commentary without HTML.
Authentication: None required. Public endpoint.
GET: https://thatcarhitme.com/api/crash-data/reports/data/ohio/statewide/2023-annual-report
Yearly Traffic Safety Analysis
3,173 CRASHES IN
OHIO, OH
2023
In 2023, Licking County recorded 3,173 total traffic crashes, a 9.0% decrease from the 3,487 crashes reported in 2022. While overall crashes and injuries declined, the most notable year-over-year shift was a 35.3% increase in traffic fatalities, which rose from 17 in 2022 to 23 in 2023.
3,173
▼ -9.0%was 3,487
Total Crash Events
23
▲ 35.3%was 17
Persons Killed
1,107
▼ -17.2%was 1,337
Persons Injured
394
▼ -8.2%was 429
Hit-and-Run Crashes
Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (17) 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 trend for traffic incidents in Licking County shows a year-over-year decline. Total crashes fell by 314, from 3,487 in 2022 to 3,173 in 2023. Similarly, the number of people injured in these crashes decreased by 17.2%, from 1,337 to 1,107.
394
Hit-and-Run Crashes — 2023
▼ -8.2% vs prior (429)
The number of hit-and-run crashes decreased from 429 in 2022 to 394 in 2023. However, because total crashes also decreased, the hit-and-run rate as a percentage of all crashes remained stable, ticking up slightly from 12.3% to 12.4%.
Vulnerable Road User Casualties
2
Pedestrians Killed
21
Motorists Killed
30
Pedestrians Injured
1,077
Motorists Injured
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 timing of crashes remained consistent between the two periods. Friday was the peak day for crashes in both 2023 (527 crashes) and 2022 (571 crashes). The afternoon rush hour at 4 p.m. was also the consistent peak hour for incidents in both years, accounting for 272 crashes in 2023 and 305 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
While total crashes decreased, the severity of outcomes worsened. The number of fatalities increased from 17 to 23, and though the number of fatal crashes was unchanged at 17, the fatal crash rate per 100 crashes rose from 0.49% to 0.54%. The proportion of crashes involving any level of injury (serious, minor, or possible) decreased slightly from 26.4% in 2022 to 25.1% in 2023.
Severity is per crash event (most severe injury). 17 fatal crash events resulted in 23 persons killed.
Outcome by Severity (Crash Events)
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
Crash conditions were broadly similar year-over-year. The proportion of crashes occurring in daylight was stable at 65.0% in 2023 versus 63.9% in 2022. While crashes on dry roads remained the majority in both periods, the share of crashes on wet surfaces increased from 15.2% in 2022 to 18.0% in 2023.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field
Road Surface
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 Ford, Chevrolet, and Honda in both 2022 and 2023, with all three seeing a decrease in crash involvement. Analysis of persons involved in crashes shows a shift in age distribution; the proportion of individuals aged 16-20 increased from 11.4% of all persons in 2022 to 13.1% in 2023, despite a decrease in total persons involved.
Top Vehicle Makes (5,528 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records
377 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (6,878 persons with recorded sex)
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: 3,173
- Total persons involved: 7,157
- Total vehicles involved: 5,528
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
ThatCarHitMe.com
An Injuria.ai Company
Crash Data Intelligence
Data: Ohio Crash Data (ODOT TIMS) · Csv
Period: 2023-01-01 – 2023-12-31
Generated: July 5, 2026 · All rights reserved