Yearly Traffic Safety Analysis

1,131 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Williams County recorded 1,131 total vehicle crashes, a 5.8% decrease from the 1,201 crashes reported in 2022. Despite the overall reduction in collisions, the total number of persons injured increased by 14.7% from 279 to 320 year-over-year. The number of fatalities resulting from these crashes decreased from 8 in 2022 to 5 in 2023.

1,131

▼ -5.8%was 1,201

Total Crash Events

▼ -37.5%was 8

Persons Killed

320

▲ 14.7%was 279

Persons Injured

▼ -2.6%was 77

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 collisions in Williams County showed a downward trend in 2023, with total crashes decreasing by 5.8% compared to 2022. While the number of crashes and related fatalities (down from 8 to 5) declined, the number of persons injured in these incidents rose by 14.7% from 279 to 320.

Hit-and-Run Crashes — 2023

▼ -2.6% vs prior (77)

The number of hit-and-run incidents remained relatively stable, with 75 crashes in 2023 compared to 77 in 2022. Despite this slight decrease in absolute numbers, the hit-and-run rate as a percentage of all crashes saw a marginal increase. In 2023, hit-and-runs accounted for 6.6% of all collisions, up slightly from 6.4% in the previous year.

Vulnerable Road User Casualties

Pedestrians Killed

Prior: 0→0.0%

Motorists Killed

Prior: 8↓-37.5%

Pedestrians Injured

Prior: 0→%

317

Motorists Injured

Prior: 279↑13.6%

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 broadly consistent year-over-year, with Friday being the peak day for collisions in 2023 (191 crashes), similar to 2022 when it tied for the peak with 195 crashes. However, the peak hour for crashes shifted an hour earlier, moving from 7 a.m. in 2022 (88 crashes) to 6 a.m. in 2023 (99 crashes).

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 severity of crashes shifted in 2023, with a notable increase in the proportion of injury-related incidents despite a drop in total collisions. The fatal crash rate decreased from 0.58% in 2022 to 0.44% in 2023. Conversely, the share of crashes resulting in any level of injury increased from 15.3% of all crashes in 2022 to 18.7% in 2023, driven by a rise in all injury categories.

Outcome by Severity (Crash Events)

Fatal5fatal crashes0.4%

↓-28.6%prior 7

Serious Injury27serious injury crashes2.4%

↑12.5%prior 24

Minor Injury136minor injury crashes12%

↑14.3%prior 119

Possible Injury49possible injury crashes4.3%

↑19.5%prior 41

No Injury914no injury crashes80.8%

↓-9.5%prior 1,010

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

Crashes in clear weather and daylight conditions remained the majority in both periods, though there were minor shifts in the distribution of crashes under adverse conditions. The proportion of collisions occurring on non-dry road surfaces (wet, snow, or ice) increased from 18.4% of total crashes in 2022 to 20.7% in 2023. Similarly, crashes during adverse weather like rain or snow constituted a slightly larger share of the total, rising from 12.7% to 14.5% year-over-year.

Weather

Clear659 (58.3%)

↓-10.0%prior 732

Cloudy308 (27.2%)

↓-2.5%prior 316

Rain82 (7.3%)

↑60.8%prior 51

Snow53 (4.7%)

↓-15.9%prior 63

Fog; Smog; Smoke20 (1.8%)

↓-28.6%prior 28

Other/Unknown4 (0.4%)

Sleet; Hail3 (0.3%)

Freezing Rain or Freezing Drizzle1 (0.1%)

Blowing Sand; Soil; Dirt; Snow1 (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

Daylight522 (46.2%)

↓-3.9%prior 543

Dark - Roadway Not Lighted441 (39.0%)

↓-0.2%prior 442

Dawn/Dusk110 (9.7%)

↓-14.1%prior 128

Dark - Lighted Roadway55 (4.9%)

↓-36.0%prior 86

Dark - Unknown Roadway Lighting2 (0.2%)

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

Dry897 (79.3%)

↓-8.5%prior 980

Wet170 (15.0%)

↑29.8%prior 131

Snow47 (4.2%)

↓-19.0%prior 58

Ice9 (0.8%)

↓-60.9%prior 23

Slush5 (0.4%)

→0.0%prior 5

Other/Unknown3 (0.3%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet (319) and Ford (311) leading in 2023, similar to their positions in 2022 (330 and 289, respectively). The demographic profile of persons involved in crashes also showed stability, with the 26-34 age group being the most represented cohort in both 2023 (314 persons) and 2022 (362 persons). Proportional representation across all age groups saw minimal change year-over-year.

Top Vehicle Makes (1,564 vehicles)

CHEVROLET319 (20.4%)

↓-3.3%prior 330

FORD311 (19.9%)

↑7.6%prior 289

DODGE99 (6.3%)

↑2.1%prior 97

FREIGHTLINER80 (5.1%)

↓-20.0%prior 100

GMC70 (4.5%)

↑11.1%prior 63

JEEP66 (4.2%)

↓-28.3%prior 92

BUICK49 (3.1%)

↓-3.9%prior 51

TOYOTA44 (2.8%)

↓-8.3%prior 48

HONDA42 (2.7%)

↓-22.2%prior 54

CHRYSLER40 (2.6%)

↓-37.5%prior 64

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

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

Sex Distribution (1,967 persons with recorded sex)

Male1,173 (59.6%)

↓-9.2%prior 1,292

Female794 (40.4%)

↓-5.5%prior 840

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: 1,131
Total persons involved: 2,013
Total vehicles involved: 1,564

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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1,131 CRASHES INOHIO, OH2023