Yearly Traffic Safety Analysis

3,983 CRASHES IN
OHIO, OH
2025

All metrics benchmarked against2024

In 2025, Delaware County recorded 3,983 total vehicle crashes, a 16.9% increase from the 3,408 crashes documented in 2024. Despite this rise in total collisions, the number of fatalities decreased from 20 to 17 over the same period. The most significant shift was the overall increase in crash volume, which occurred alongside a decrease in the rate of fatal and serious injury crashes.

3,983

16.9%was 3,408

Total Crash Events

17

-15.0%was 20

Persons Killed

1,620

2.5%was 1,581

Persons Injured

514

13.5%was 453

Hit-and-Run Crashes

Note: "Persons Killed" (17) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) 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 · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Delaware County show a notable increase year-over-year. The total number of crashes rose from 3,408 in 2024 to 3,983 in 2025, representing a 16.9% increase. Correspondingly, total injuries saw a slight rise from 1,581 to 1,620, while fatalities declined from 20 to 17.

514

Hit-and-Run Crashes — 2025

13.5% vs prior (453)

The number of hit-and-run incidents in Delaware County increased from 453 in 2024 to 514 in 2025. However, due to the larger overall increase in total crashes, the hit-and-run rate as a percentage of all collisions saw a slight decrease. The rate fell from 13.3% in the prior year to 12.9% in the current year, indicating that hit-and-runs grew at a slower pace than other crash types.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

16

Motorists Killed

Prior: 19-15.8%

16

Pedestrians Injured

Prior: 17-5.9%

1,604

Motorists Injured

Prior: 1,5642.6%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

Temporal patterns of crashes remained broadly similar year-over-year, with Friday being the most frequent day for collisions in both 2025 (640 crashes) and 2024 (599 crashes). However, the peak hour for crashes shifted from the 5 p.m. hour in 2024 (321 crashes) to the 2 p.m. hour in 2025 (324 crashes). The afternoon rush, from 2 p.m. to 5 p.m., showed a more distributed high volume of crashes in the current period compared to the prior year.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While total crashes increased, the severity of those crashes generally decreased in 2025 compared to 2024. The fatal crash rate fell from 0.56% to 0.33%, with 13 fatal crashes in 2025 versus 19 in the prior year. The proportion of crashes resulting in serious injuries also declined from 2.7% to 2.0%. Conversely, crashes resulting in 'Possible Injury' or 'No Injury' made up a larger share of the total, increasing from 12.0% to 13.0% and 69.5% to 72.1%, respectively.

Severity is per crash event (most severe injury). 13 fatal crash events resulted in 17 persons killed.

Outcome by Severity (Crash Events)

Fatal13fatal crashes0.3%
-31.6%prior 19
Serious Injury80serious injury crashes2%
-13.0%prior 92
Minor Injury501minor injury crashes12.6%
-3.8%prior 521
Possible Injury517possible injury crashes13%
26.4%prior 409
No Injury2,872no injury crashes72.1%
21.3%prior 2,367

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The majority of crashes in both periods occurred in clear weather and on dry roads. In 2025, 63.6% of crashes were in clear conditions, down slightly from 65.6% in 2024. A notable shift occurred in adverse winter conditions, with the number of crashes happening in snow nearly doubling from 113 to 214, and those on snowy road surfaces increasing from 105 to 204. The proportion of crashes during daylight hours increased slightly from 68.4% in 2024 to 70.4% in 2025.

Weather

Clear2,532 (63.6%)
13.2%prior 2,236
Cloudy827 (20.8%)
21.8%prior 679
Rain319 (8.0%)
-1.5%prior 324
Snow214 (5.4%)
89.4%prior 113
Other/Unknown35 (0.9%)
9.4%prior 32
Fog; Smog; Smoke34 (0.9%)
161.5%prior 13
Freezing Rain or Freezing Drizzle14 (0.4%)
180.0%prior 5
Blowing Sand; Soil; Dirt; Snow5 (0.1%)
Sleet; Hail3 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight2,804 (70.4%)
20.2%prior 2,332
Dark - Roadway Not Lighted640 (16.1%)
12.5%prior 569
Dark - Lighted Roadway286 (7.2%)
7.1%prior 267
Dawn/Dusk213 (5.3%)
6.5%prior 200
Other/Unknown29 (0.7%)
16.0%prior 25
Dark - Unknown Roadway Lighting11 (0.3%)
-26.7%prior 15

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry3,041 (76.3%)
13.2%prior 2,687
Wet639 (16.0%)
13.9%prior 561
Snow204 (5.1%)
94.3%prior 105
Ice63 (1.6%)
142.3%prior 26
Other/Unknown28 (0.7%)
21.7%prior 23
Slush8 (0.2%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

The types of vehicles involved in crashes remained consistent year-over-year, with Honda (1,115 vehicles), Ford (806), and Chevrolet (738) being the most common makes in 2025, reflecting a similar ranking from 2024. The number of vehicles from these top makes involved in crashes increased, in line with the overall rise in collisions. Analysis of persons involved shows the 16-20 age group was the most frequently represented in both years, increasing from 1,214 individuals in 2024 to 1,398 in 2025.

Top Vehicle Makes (7,250 vehicles)

1
HONDA1,115 (15.4%)
17.1%prior 952
2
FORD806 (11.1%)
18.7%prior 679
3
CHEVROLET738 (10.2%)
15.1%prior 641
4
TOYOTA730 (10.1%)
16.4%prior 627
5
NISSAN304 (4.2%)
5.2%prior 289
6
HYUNDAI292 (4%)
32.7%prior 220
7
JEEP287 (4%)
13.4%prior 253
8
KIA273 (3.8%)
22.4%prior 223
9
GMC180 (2.5%)
7.8%prior 167
10
DODGE180 (2.5%)
-6.3%prior 192

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

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

Sex Distribution (9,259 persons with recorded sex)

Male5,158 (55.7%)
13.0%prior 4,565
Female4,101 (44.3%)
12.4%prior 3,648

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2025-01-01 to 2025-12-31 · 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: 2025-01-01 through 2025-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 3,983
  • Total persons involved: 9,612
  • Total vehicles involved: 7,250

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: 2025." Published July 6, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2025-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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Delaware County, OH Crash Report — 2025 | ThatCarHitMe.com