Yearly Traffic Safety Analysis

1,235 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Pickaway County recorded 1,235 total traffic crashes, a slight decrease of 3.1% from the 1,274 crashes reported in 2022. During this period, the number of fatalities also decreased significantly, falling 30% from 10 in 2022 to 7 in 2023. The overall number of injuries also saw a modest decline.

1,235

-3.1%was 1,274

Total Crash Events

7

-30.0%was 10

Persons Killed

524

-4.7%was 550

Persons Injured

111

-17.8%was 135

Hit-and-Run Crashes

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (7) 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 safety metrics in Pickaway County showed a slight improvement from 2022 to 2023. Total crashes declined by 3.1% from 1,274 to 1,235. Similarly, total injuries fell by 4.7% (from 550 to 524), and fatalities decreased by 30% (from 10 to 7).

111

Hit-and-Run Crashes — 2023

-17.8% vs prior (135)

Incidents of hit-and-run crashes decreased from 2022 to 2023. The total number of hit-and-run incidents fell from 135 to 111. Correspondingly, the hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, declined from 10.6% in 2022 to 9.0% in 2023.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

6

Motorists Killed

Prior: 9-33.3%

5

Pedestrians Injured

Prior: 13-61.5%

519

Motorists Injured

Prior: 537-3.4%

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 in Pickaway County showed some shifts between 2022 and 2023. The peak day for crashes moved from Friday (212 incidents) in 2022 to Thursday (201 incidents) in 2023. However, the peak hour for collisions remained consistent year-over-year, with the 3 p.m. hour having the highest frequency in both periods, recording 102 crashes in both 2022 and 2023.

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 saw a notable improvement from 2022 to 2023. The fatal crash rate decreased from 0.78% to 0.57%, with 7 fatal crashes in 2023 compared to 10 in the prior year. While the number of minor injury crashes declined from 206 to 193, serious injury crashes saw a slight increase from 53 to 56 incidents. The proportion of crashes resulting in no injuries remained stable at approximately 70% for both years.

Outcome by Severity (Crash Events)

Fatal7fatal crashes0.6%
-30.0%prior 10
Serious Injury56serious injury crashes4.5%
5.7%prior 53
Minor Injury193minor injury crashes15.6%
-6.3%prior 206
Possible Injury110possible injury crashes8.9%
-2.7%prior 113
No Injury869no injury crashes70.4%
-2.6%prior 892

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 conditions under which crashes occurred showed some variation year-over-year, largely reflecting different weather patterns. Crashes on snow or ice-covered roads dropped significantly, from a combined 109 incidents in 2022 to just 20 in 2023. Conversely, crashes on wet roads increased from 189 to 220. The majority of crashes in both periods occurred in daylight on dry roads, with these conditions accounting for proportions similar to the prior year.

Weather

Clear771 (62.4%)
-0.9%prior 778
Cloudy285 (23.1%)
-6.9%prior 306
Rain128 (10.4%)
39.1%prior 92
Snow20 (1.6%)
-69.7%prior 66
Fog; Smog; Smoke16 (1.3%)
60.0%prior 10
Other/Unknown8 (0.6%)
60.0%prior 5
Severe Crosswinds3 (0.2%)
Freezing Rain or Freezing Drizzle2 (0.2%)
-60.0%prior 5
Sleet; Hail2 (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

Daylight751 (60.8%)
0.9%prior 744
Dark - Roadway Not Lighted306 (24.8%)
-13.1%prior 352
Dawn/Dusk87 (7.0%)
-3.3%prior 90
Dark - Lighted Roadway52 (4.2%)
-25.7%prior 70
Dark - Unknown Roadway Lighting33 (2.7%)
230.0%prior 10
Other/Unknown6 (0.5%)
-25.0%prior 8

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

Road Surface

Dry986 (79.8%)
1.9%prior 968
Wet220 (17.8%)
16.4%prior 189
Snow15 (1.2%)
-75.8%prior 62
Other/Unknown9 (0.7%)
80.0%prior 5
Ice5 (0.4%)
-89.4%prior 47

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

Vehicles & Demographics

The types of vehicles involved in crashes remained consistent between 2022 and 2023. Passenger Cars (875), Sport Utility Vehicles (466), and Pick-ups (363) were the three most common vehicle types in 2023, mirroring the previous year's rankings with very similar counts. The top vehicle makes also held steady, with Chevrolet (324) and Ford (318) being the most frequently involved makes in 2023, down from 358 and 338 respectively in 2022.

Top Vehicle Makes (2,055 vehicles)

1
CHEVROLET324 (15.8%)
-9.5%prior 358
2
FORD318 (15.5%)
-5.9%prior 338
3
HONDA204 (9.9%)
5.2%prior 194
4
TOYOTA149 (7.3%)
5.7%prior 141
5
HYUNDAI124 (6%)
31.9%prior 94
6
DODGE107 (5.2%)
-9.3%prior 118
7
KIA83 (4%)
-14.4%prior 97
8
JEEP82 (4%)
3.8%prior 79
9
NISSAN82 (4%)
-7.9%prior 89
10
GMC73 (3.6%)
30.4%prior 56

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

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

Sex Distribution (2,632 persons with recorded sex)

Male1,576 (59.9%)
1.8%prior 1,548
Female1,056 (40.1%)
1.8%prior 1,037

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: 1,235
  • Total persons involved: 2,697
  • Total vehicles involved: 2,055

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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