ThatCarHitMe.com
An Injuria.ai Company
YEAR-OVER-YEAR CRASH REPORT · OHIO, OH · JANUARY 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/january-2023-report
Monthly Traffic Safety Analysis
262 CRASHES IN
OHIO, OH
JANUARY 2023
In January 2023, Allen County recorded 262 traffic crashes, a 9.6% increase from the 239 crashes in January 2022. The most significant year-over-year change was the increase in crash severity, with one fatal crash and a substantial rise in serious injury crashes, compared to none in the same period of the prior year.
262
▲ 9.6%was 239
Total Crash Events
1
Persons Killed
81
▲ 14.1%was 71
Persons Injured
34
▼ -24.4%was 45
Hit-and-Run Crashes
Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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 2023-01-31 · Aggregate counts from crash, person, and vehicle records
Trend Summary
Traffic crashes in Allen County showed an upward trend in January 2023 compared to the previous year. The total number of crashes increased by 9.6%, from 239 to 262. Similarly, the number of people injured rose by 14.1%, from 71 to 81, and fatalities increased from zero to one.
34
Hit-and-Run Crashes — January 2023
▼ -24.4% vs prior (45)
Hit-and-run incidents decreased in January 2023 compared to the same month in 2022. The total number of hit-and-run crashes fell from 45 to 34. Accordingly, the hit-and-run rate dropped from 18.8% to 13.0% of all reported crashes, indicating a downward trend for this crash type.
Vulnerable Road User Casualties
0
Pedestrians Killed
1
Motorists Killed
1
Pedestrians Injured
80
Motorists Injured
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)
When Crashes Happen
The timing of crashes shifted between the two periods. In January 2023, the peak day for crashes was Wednesday with 47 incidents, and the peak hour was 6 p.m. with 37 incidents. This contrasts with January 2022, when Monday was the peak day (52 crashes) and 3 p.m. was the peak hour (24 crashes).
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Crash date field aggregated by weekday
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Crash time field aggregated by hour (0-23)
Crash Severity Breakdown
Crash severity worsened significantly in January 2023 compared to the prior year. The county recorded one fatal crash, whereas there were none in January 2022. The number of serious injury crashes increased from 1 to 11, representing a shift from 0.4% to 4.2% of all crashes. Conversely, the number of minor and possible injury crashes saw a decrease.
Outcome by Severity (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · KABCO injury classification scale
Severity Distribution (Crash Events)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Most severe injury per crash record
Road & Environmental Conditions
There was a notable shift in crash conditions year-over-year. In January 2023, there were more crashes in cloudy (96) and snowy (42) weather compared to 65 and 25, respectively, in the prior year. Crashes on unlit dark roadways increased from 54 to 80, and incidents on wet road surfaces more than doubled from 31 to 82.
Weather
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Weather condition at time of crash
Lighting
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Lighting condition field
Road Surface
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Road surface condition field
Vehicles & Demographics
Ford became the most common vehicle make involved in crashes in January 2023 with 91 vehicles, up from 66 in the prior year when it was second to Chevrolet (75). An analysis of persons involved shows a notable increase in the 26-34 age group, from 66 to 80 individuals, and the 65+ age group, which grew from 45 to 69 individuals.
Top Vehicle Makes (426 vehicles)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · Vehicle unit records
34 persons with unknown or unrecorded age excluded from age chart.
Sex Distribution (498 persons with recorded sex)
Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2023-01-01 to 2023-01-31 · 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 2023-01-31
- Report generated: July 6, 2026
Data Coverage
- Reporting period: 2023-01-01 through 2023-01-31 (31 days)
- Geographic scope: ohio, OH
- Total crash records analyzed: 262
- Total persons involved: 522
- Total vehicles involved: 426
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: January 2023." Published July 6, 2026. Reporting period: 2023-01-01 to 2023-01-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/january-2023-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 – 2023-01-31
Generated: July 6, 2026 · All rights reserved