Yearly Traffic Safety Analysis

3,397 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In 2024, Wood County recorded 3,397 total vehicle crashes, a figure nearly identical to the 3,394 crashes reported in 2023, representing a change of less than 0.1%. Despite the stable number of total incidents, the number of fatalities resulting from these crashes decreased from 23 in the prior year to 19 in the current year. Total injuries remained consistent, with 1,062 in 2024 compared to 1,063 in 2023.

3,397

0.1%was 3,394

Total Crash Events

19

-17.4%was 23

Persons Killed

1,062

-0.1%was 1,063

Persons Injured

344

3.0%was 334

Hit-and-Run Crashes

Note: "Persons Killed" (19) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash trends in Wood County remained stable year-over-year. Total crashes increased by just three incidents, from 3,394 in 2023 to 3,397 in 2024. While the total number of injuries was also nearly unchanged (1,063 vs. 1,062), there was a notable decrease in fatalities, which fell from 23 in the prior year to 19 in the current year.

344

Hit-and-Run Crashes — 2024

3.0% vs prior (334)

Hit-and-run incidents in Wood County trended slightly upward in 2024 compared to the previous year. The total number of hit-and-run crashes increased from 334 in 2023 to 344 in 2024. This corresponds to a rise in the hit-and-run rate, which grew from 9.8% of all crashes in the prior period to 10.1% in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

18

Motorists Killed

Prior: 22-18.2%

18

Pedestrians Injured

Prior: 20-10.0%

1,044

Motorists Injured

Prior: 1,0430.1%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes in Wood County showed consistency year-over-year. Friday remained the peak day for crashes, with incidents on this day increasing from 580 in 2023 to 631 in 2024. Similarly, the 5 PM hour continued to be the peak time for collisions, rising from 291 crashes in the prior period to 306 in the current period. The afternoon commute hours from 3 PM to 6 PM consistently accounted for the highest concentration of crashes in both years.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw minor shifts between the two periods. The number of fatal crashes decreased from 21 in 2023 to 19 in 2024, and the corresponding fatal crash rate dropped from 0.62% to 0.56%. While the proportion of minor injury crashes slightly decreased from 10.6% to 10.5%, crashes resulting in serious injuries (2.1% to 2.2%) and possible injuries (8.0% to 8.7%) saw small proportional increases. The majority of crashes in both years, over 78%, resulted in no injuries.

Outcome by Severity (Crash Events)

Fatal19fatal crashes0.6%
-9.5%prior 21
Serious Injury74serious injury crashes2.2%
5.7%prior 70
Minor Injury355minor injury crashes10.5%
-1.7%prior 361
Possible Injury295possible injury crashes8.7%
9.3%prior 270
No Injury2,654no injury crashes78.1%
-0.7%prior 2,672

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The environmental conditions at the time of crashes showed some year-over-year shifts. Crashes on dry roads increased from 72.5% to 73.7% of the total, while those on wet roads decreased from 22.1% to 19.0%. Notably, crashes on icy roads nearly doubled, increasing from 48 incidents in 2023 to 92 in 2024. Regarding lighting, crashes in daylight conditions decreased slightly, while those in unlit, dark conditions increased from 17.8% to 19.0% of all crashes.

Weather

Clear2,106 (62.0%)
7.3%prior 1,962
Cloudy637 (18.8%)
-16.5%prior 763
Rain364 (10.7%)
-18.0%prior 444
Snow192 (5.7%)
40.1%prior 137
Fog; Smog; Smoke37 (1.1%)
0.0%prior 37
Other/Unknown35 (1.0%)
12.9%prior 31
Sleet; Hail13 (0.4%)
Severe Crosswinds8 (0.2%)
60.0%prior 5
Freezing Rain or Freezing Drizzle3 (0.1%)
Blowing Sand; Soil; Dirt; Snow2 (0.1%)
-81.8%prior 11

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight2,041 (60.1%)
-2.3%prior 2,089
Dark - Roadway Not Lighted644 (19.0%)
6.4%prior 605
Dark - Lighted Roadway414 (12.2%)
-2.4%prior 424
Dawn/Dusk248 (7.3%)
6.0%prior 234
Dark - Unknown Roadway Lighting26 (0.8%)
73.3%prior 15
Other/Unknown24 (0.7%)
-11.1%prior 27

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry2,505 (73.7%)
1.8%prior 2,460
Wet646 (19.0%)
-14.0%prior 751
Snow118 (3.5%)
7.3%prior 110
Ice92 (2.7%)
91.7%prior 48
Other/Unknown28 (0.8%)
33.3%prior 21
Slush5 (0.1%)
Water (Standing; Moving)3 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

Analysis of persons involved in crashes shows a shift in age demographics, with the 26-34 age group increasing from 1,060 individuals in 2023 to 1,155 in 2024. Conversely, the number of persons in the 16-20 age group decreased from 1,077 to 965. The ranking of vehicle makes involved in crashes remained largely consistent. Ford (897 vehicles) and Chevrolet (872 vehicles) continued to be the most common makes, both seeing a small increase from the prior year. Toyota moved up to the fourth most-involved make, displacing Dodge.

Top Vehicle Makes (5,633 vehicles)

1
FORD897 (15.9%)
3.0%prior 871
2
CHEVROLET872 (15.5%)
3.6%prior 842
3
HONDA488 (8.7%)
-0.8%prior 492
4
TOYOTA359 (6.4%)
5.6%prior 340
5
DODGE326 (5.8%)
-7.4%prior 352
6
JEEP278 (4.9%)
-10.9%prior 312
7
NISSAN190 (3.4%)
3.3%prior 184
8
HYUNDAI180 (3.2%)
10.4%prior 163
9
GMC176 (3.1%)
-21.4%prior 224
10
CHRYSLER168 (3%)
3.7%prior 162

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (7,164 persons with recorded sex)

Male3,982 (55.6%)
-1.2%prior 4,032
Female3,182 (44.4%)
2.0%prior 3,119

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 3,397
  • Total persons involved: 7,435
  • Total vehicles involved: 5,633

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: 2024." Published July 6, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2024-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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Wood County, OH Crash Report — 2024 | ThatCarHitMe.com