Yearly Traffic Safety Analysis

824 CRASHES IN
OHIO, OH
2024

All metrics benchmarked against2023

In 2024, Crawford County recorded 824 total traffic crashes, a 7.2% increase from the 769 crashes reported in 2023. While the overall number of crashes and injuries (213 vs. 200) rose, the number of fatalities saw a significant decrease, falling from 7 in the prior year to 3 in the current year. This drop in fatalities represents the most notable year-over-year shift in the data.

824

7.2%was 769

Total Crash Events

3

-57.1%was 7

Persons Killed

213

6.5%was 200

Persons Injured

49

-10.9%was 55

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend in traffic crashes in Crawford County is rising year-over-year. The county experienced a 7.2% increase in total crashes, from 769 in 2023 to 824 in 2024. This represents an additional 55 crashes in the current period.

49

Hit-and-Run Crashes — 2024

-10.9% vs prior (55)

Hit-and-run incidents in Crawford County showed a downward trend in the most recent period. The total number of hit-and-run crashes decreased from 55 in 2023 to 49 in 2024. Correspondingly, the hit-and-run rate, as a percentage of total crashes, fell from 7.2% to 5.9%.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

3

Motorists Killed

Prior: 7-57.1%

3

Pedestrians Injured

Prior: 250.0%

210

Motorists Injured

Prior: 1986.1%

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

Temporal analysis shows a shift in the daily peak for crashes between the two periods. While Friday remained the day with the most crashes in both 2024 (163 crashes) and 2023 (139 crashes), the peak hour for collisions changed. In 2024, the most crashes occurred at 6 PM with 63 incidents, shifting from the 7 AM peak (60 incidents) observed in the prior year.

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

Crash severity outcomes improved year-over-year, with a notable decrease in fatal incidents. The number of fatal crashes dropped from 7 in 2023 to 3 in 2024, and the fatal crash rate per 100 crashes fell from 0.91 to 0.36. While serious injury crashes remained proportionally stable (2.7% in 2024 vs. 2.6% in 2023), there was an increase in the proportion of minor injury crashes, which rose from 9.8% to 11.7% of all crashes.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.4%
-57.1%prior 7
Serious Injury22serious injury crashes2.7%
10.0%prior 20
Minor Injury96minor injury crashes11.7%
28.0%prior 75
Possible Injury44possible injury crashes5.3%
-13.7%prior 51
No Injury659no injury crashes80%
7.0%prior 616

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 majority of crashes in both periods occurred in clear weather and on dry roads. However, there was a notable increase in crashes during adverse conditions in 2024, with incidents in snow more than doubling from 24 to 61 and crashes on ice more than tripling from 7 to 22. The proportion of crashes occurring in dark conditions also increased from 35.6% in 2023 to 38.5% in 2024, while the share of daylight crashes decreased.

Weather

Clear555 (67.4%)
8.8%prior 510
Cloudy118 (14.3%)
-10.6%prior 132
Rain71 (8.6%)
-15.5%prior 84
Snow61 (7.4%)
154.2%prior 24
Fog; Smog; Smoke7 (0.8%)
-12.5%prior 8
Other/Unknown4 (0.5%)
-33.3%prior 6
Sleet; Hail4 (0.5%)
Freezing Rain or Freezing Drizzle3 (0.4%)
Blowing Sand; Soil; Dirt; Snow1 (0.1%)

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

Lighting

Daylight430 (52.2%)
-0.7%prior 433
Dark - Roadway Not Lighted257 (31.2%)
16.8%prior 220
Dawn/Dusk73 (8.9%)
30.4%prior 56
Dark - Lighted Roadway55 (6.7%)
7.8%prior 51
Dark - Unknown Roadway Lighting5 (0.6%)
Other/Unknown4 (0.5%)
-33.3%prior 6

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

Road Surface

Dry624 (75.7%)
4.7%prior 596
Wet131 (15.9%)
-5.8%prior 139
Snow40 (4.9%)
100.0%prior 20
Ice22 (2.7%)
214.3%prior 7
Slush3 (0.4%)
Sand; Mud; Dirt; Oil; Gravel2 (0.2%)
Other/Unknown2 (0.2%)
-60.0%prior 5

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

Vehicles & Demographics

Passenger Cars, Sport Utility Vehicles, and Pick-ups were the top three vehicle types involved in crashes for both years. The top three vehicle makes also remained consistent, with Chevrolet (261 vehicles), Ford (162), and Honda (93) being the most common in 2024. Analysis of persons involved shows the 65+ age group had the largest representation in 2024 with 220 individuals, an increase from 197 in the prior year.

Top Vehicle Makes (1,239 vehicles)

1
CHEVROLET261 (21.1%)
14.0%prior 229
2
FORD162 (13.1%)
-8.0%prior 176
3
HONDA93 (7.5%)
-12.3%prior 106
4
DODGE74 (6%)
-7.5%prior 80
5
TOYOTA70 (5.6%)
27.3%prior 55
6
KIA68 (5.5%)
88.9%prior 36
7
JEEP59 (4.8%)
25.5%prior 47
8
HYUNDAI49 (4%)
58.1%prior 31
9
GMC47 (3.8%)
20.5%prior 39
10
NISSAN43 (3.5%)
-4.4%prior 45

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

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

Sex Distribution (1,323 persons with recorded sex)

Male742 (56.1%)
0.7%prior 737
Female581 (43.9%)
2.8%prior 565

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 5, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 824
  • Total persons involved: 1,442
  • Total vehicles involved: 1,239

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 5, 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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Crawford County, OH Crash Report — 2024 | ThatCarHitMe.com