Yearly Traffic Safety Analysis

3,453 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Delaware County recorded 3,453 total crashes, a slight decrease of 0.3% from the 3,463 crashes reported in 2022. While overall crash volume remained stable, the most notable year-over-year shift was a 16.2% increase in hit-and-run incidents, which rose from 450 in the prior year to 523 in the current period.

3,453

-0.3%was 3,463

Total Crash Events

16

-5.9%was 17

Persons Killed

1,469

0.1%was 1,468

Persons Injured

523

16.2%was 450

Hit-and-Run Crashes

Note: "Persons Killed" (16) counts individual fatalities across all crash events. "Fatal" in the severity table below (16) 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

The overall crash trend in Delaware County was stable year-over-year, with a minor 0.3% decrease from 3,463 crashes in 2022 to 3,453 in 2023. Total fatalities decreased from 17 to 16, while total injuries remained virtually unchanged, increasing by one from 1,468 to 1,469.

523

Hit-and-Run Crashes — 2023

16.2% vs prior (450)

Hit-and-run crashes saw a significant year-over-year increase in Delaware County. The total number of hit-and-run incidents rose by 16.2%, from 450 in 2022 to 523 in 2023. This pushed the hit-and-run rate, which is the percentage of all crashes that are hit-and-runs, up from 13.0% to 15.1%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

15

Motorists Killed

Prior: 16-6.3%

25

Pedestrians Injured

Prior: 28-10.7%

1,444

Motorists Injured

Prior: 1,4400.3%

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 temporal patterns of crashes remained largely consistent year-over-year, with Friday being the peak day for crashes in both 2023 (588 crashes) and 2022 (575 crashes). However, the peak hour for collisions shifted one hour earlier, from 5 p.m. in 2022 (282 crashes) to 4 p.m. in 2023 (317 crashes), indicating a change in the afternoon commute's highest-risk time.

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 overall severity of crashes showed minor changes between the two periods. The fatal crash count decreased from 17 in 2022 to 16 in 2023, with the corresponding fatal crash rate dropping from 0.49% to 0.46%. The proportion of serious injury crashes also declined from 2.5% to 2.3% of all crashes, while minor injury crashes saw a slight proportional increase from 13.6% to 14.0%.

Outcome by Severity (Crash Events)

Fatal16fatal crashes0.5%
-5.9%prior 17
Serious Injury80serious injury crashes2.3%
-7.0%prior 86
Minor Injury485minor injury crashes14%
2.8%prior 472
Possible Injury415possible injury crashes12%
-3.7%prior 431
No Injury2,457no injury crashes71.2%
0.0%prior 2,457

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 distribution of crashes by condition saw some shifts related to weather patterns. Crashes occurring in rainy conditions increased from 261 in 2022 to 366 in 2023, and crashes on wet roads rose from 523 to 592. Conversely, incidents during snowy conditions decreased from 153 to 89, with a corresponding drop in crashes on snow or ice-covered roads from 215 to 76.

Weather

Clear2,159 (62.5%)
0.3%prior 2,153
Cloudy789 (22.8%)
-1.3%prior 799
Rain366 (10.6%)
40.2%prior 261
Snow89 (2.6%)
-41.8%prior 153
Other/Unknown21 (0.6%)
-25.0%prior 28
Fog; Smog; Smoke19 (0.6%)
-40.6%prior 32
Blowing Sand; Soil; Dirt; Snow3 (0.1%)
-75.0%prior 12
Severe Crosswinds3 (0.1%)
Sleet; Hail3 (0.1%)
-76.9%prior 13
Freezing Rain or Freezing Drizzle1 (0.0%)
-88.9%prior 9

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

Lighting

Daylight2,374 (68.8%)
3.3%prior 2,299
Dark - Roadway Not Lighted610 (17.7%)
-10.2%prior 679
Dark - Lighted Roadway255 (7.4%)
-3.4%prior 264
Dawn/Dusk181 (5.2%)
0.6%prior 180
Other/Unknown26 (0.8%)
-13.3%prior 30
Dark - Unknown Roadway Lighting7 (0.2%)
-36.4%prior 11

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

Road Surface

Dry2,764 (80.0%)
2.4%prior 2,698
Wet592 (17.1%)
13.2%prior 523
Snow64 (1.9%)
-57.9%prior 152
Other/Unknown17 (0.5%)
-5.6%prior 18
Ice12 (0.3%)
-81.0%prior 63
Slush4 (0.1%)
-50.0%prior 8

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Honda, Ford, and Chevrolet being the top three in both 2022 and 2023. An analysis of persons involved shows a notable demographic shift, with the number of individuals aged 65 and older increasing by 17.0%, from 752 in 2022 to 880 in 2023. The 16-20 age group also saw an increase from 1,210 to 1,256 persons involved.

Top Vehicle Makes (6,305 vehicles)

1
HONDA991 (15.7%)
14.0%prior 869
2
FORD750 (11.9%)
-2.0%prior 765
3
CHEVROLET648 (10.3%)
-0.5%prior 651
4
TOYOTA592 (9.4%)
-7.9%prior 643
5
NISSAN284 (4.5%)
-0.7%prior 286
6
JEEP284 (4.5%)
41.3%prior 201
7
HYUNDAI217 (3.4%)
-12.5%prior 248
8
KIA210 (3.3%)
-0.9%prior 212
9
GMC179 (2.8%)
6.5%prior 168
10
DODGE174 (2.8%)
-24.0%prior 229

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

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

Sex Distribution (8,219 persons with recorded sex)

Male4,540 (55.2%)
3.7%prior 4,379
Female3,679 (44.8%)
4.6%prior 3,517

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: 3,453
  • Total persons involved: 8,546
  • Total vehicles involved: 6,305

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