Yearly Traffic Safety Analysis

521 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In Paulding County, total vehicle crashes increased slightly from 508 in 2022 to 521 in 2023, a change of approximately 2.6%. Despite the rise in total incidents, the number of reported injuries fell by 25.3% from 146 to 109. The most notable year-over-year shift was a significant decrease in hit-and-run incidents, which fell from 23 in the prior period to 8 in the current period.

521

2.6%was 508

Total Crash Events

3

200.0%was 1

Persons Killed

109

-25.3%was 146

Persons Injured

8

-65.2%was 23

Hit-and-Run Crashes

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 crash trends in Paulding County show a slight increase in the total number of incidents, rising from 508 in 2022 to 521 in 2023. However, this was accompanied by a notable 25.3% decrease in the number of people injured, which dropped from 146 to 109. Conversely, the number of fatalities recorded in crashes increased from one in 2022 to three in 2023.

8

Hit-and-Run Crashes — 2023

-65.2% vs prior (23)

Hit-and-run crashes saw a significant downward trend in 2023 compared to the prior year. The total number of hit-and-run incidents decreased by 65.2%, from 23 crashes in 2022 to 8 in 2023. Consequently, the hit-and-run rate as a percentage of all crashes fell from 4.5% to 1.5%.

Vulnerable Road User Casualties

3

Motorists Killed

Prior: 0%

109

Motorists Injured

Prior: 146-25.3%

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 shifted between the two periods. In 2023, the peak day for crashes was Friday with 85 incidents, a change from 2022 when Monday was the peak day with 99 incidents. Similarly, the peak hour for crashes moved from the evening at 7 p.m. in 2022 (45 crashes) to the morning commute at 7 a.m. in 2023 (62 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 showed a mixed trend year-over-year. The number of fatal crashes increased from one in 2022 to three in 2023, raising the fatal crash rate from 0.2% to 0.6% of all incidents. However, the overall proportion of crashes resulting in any type of injury (serious, minor, or possible) decreased from 17.5% of all crashes in 2022 to 13.9% in 2023, corresponding with an increase in no-injury crashes from 82.3% to 85.6%.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
200.0%prior 1
Serious Injury18serious injury crashes3.5%
12.5%prior 16
Minor Injury38minor injury crashes7.3%
-17.4%prior 46
Possible Injury16possible injury crashes3.1%
-40.7%prior 27
No Injury446no injury crashes85.6%
6.7%prior 418

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 remained largely consistent between 2022 and 2023. Crashes on dry roads (82.0% vs 81.5%) and in clear weather (66.8% vs 68.9%) made up similar proportions of the total in both years. The most notable change was a proportional increase in crashes occurring during dawn or dusk, which accounted for 13.2% of crashes in 2023, up from 9.4% in 2022.

Weather

Clear348 (66.8%)
-0.6%prior 350
Cloudy104 (20.0%)
15.6%prior 90
Rain41 (7.9%)
17.1%prior 35
Snow15 (2.9%)
-28.6%prior 21
Fog; Smog; Smoke11 (2.1%)
83.3%prior 6
Other/Unknown1 (0.2%)
Blowing Sand; Soil; Dirt; Snow1 (0.2%)

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

Lighting

Dark - Roadway Not Lighted243 (46.6%)
-0.8%prior 245
Daylight194 (37.2%)
0.0%prior 194
Dawn/Dusk69 (13.2%)
43.8%prior 48
Dark - Lighted Roadway13 (2.5%)
-27.8%prior 18
Dark - Unknown Roadway Lighting1 (0.2%)
Other/Unknown1 (0.2%)

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

Road Surface

Dry427 (82.0%)
3.1%prior 414
Wet75 (14.4%)
13.6%prior 66
Snow13 (2.5%)
-35.0%prior 20
Ice5 (1.0%)
-28.6%prior 7
Slush1 (0.2%)

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

Vehicles & Demographics

The composition of vehicles and persons involved in crashes showed some shifts between 2022 and 2023. Passenger cars and Sport Utility Vehicles remained the most common vehicle types involved, though the count of SUVs increased from 163 to 177 while passenger cars decreased from 239 to 227. Among persons involved, the 16-20 age group saw an increase from 105 to 120 individuals, while the 0-15 age group saw a significant decrease from 146 to 77 individuals.

Top Vehicle Makes (640 vehicles)

1
CHEVROLET193 (30.2%)
6.6%prior 181
2
FORD101 (15.8%)
-13.7%prior 117
3
DODGE40 (6.3%)
-11.1%prior 45
4
GMC35 (5.5%)
-12.5%prior 40
5
JEEP33 (5.2%)
135.7%prior 14
6
HONDA28 (4.4%)
40.0%prior 20
7
BUICK24 (3.8%)
26.3%prior 19
8
TOYOTA19 (3%)
11.8%prior 17
9
CHRYSLER17 (2.7%)
-22.7%prior 22
10
KIA17 (2.7%)
142.9%prior 7

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

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

Sex Distribution (849 persons with recorded sex)

Male491 (57.8%)
-2.2%prior 502
Female358 (42.2%)
-5.3%prior 378

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: 521
  • Total persons involved: 855
  • Total vehicles involved: 640

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