Yearly Traffic Safety Analysis

1,970 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Erie County recorded 1,970 total vehicle crashes, a 4.3% decrease from the 2,059 crashes documented in 2022. Despite the overall reduction in collisions, the number of fatal incidents more than doubled, increasing from 5 in 2022 to 11 in 2023. This resulted in 12 fatalities in 2023, compared to 9 in the prior year.

1,970

-4.3%was 2,059

Total Crash Events

12

33.3%was 9

Persons Killed

613

-17.7%was 745

Persons Injured

220

-11.3%was 248

Hit-and-Run Crashes

Note: "Persons Killed" (12) counts individual fatalities across all crash events. "Fatal" in the severity table below (11) 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 crash volume in Erie County showed a downward trend, with total incidents decreasing by 4.3% from 2,059 in 2022 to 1,970 in 2023. This decline was also reflected in the number of people injured, which fell by 17.7% from 745 to 613. In contrast, the number of fatalities rose from 9 to 12 during the same period.

220

Hit-and-Run Crashes — 2023

-11.3% vs prior (248)

Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. In 2023, there were 220 hit-and-run crashes, down from 248 in 2022, an 11.3% reduction. The hit-and-run rate also trended downward, falling from 12.0% of all crashes in 2022 to 11.2% in 2023.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 0%

9

Motorists Killed

Prior: 90.0%

13

Pedestrians Injured

Prior: 1030.0%

600

Motorists Injured

Prior: 735-18.4%

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 temporal patterns of crashes in Erie County remained consistent year-over-year. The peak day for crashes in both 2023 and 2022 was Friday, with 332 and 325 incidents, respectively. Similarly, the 3 p.m. hour was the most frequent time for crashes in both periods, accounting for 150 crashes in 2023 and 137 in 2022.

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

While total crashes decreased, the severity of crashes worsened in 2023 compared to 2022. The fatal crash rate more than doubled, rising from 0.24% to 0.56% of all crashes. The proportion of crashes resulting in serious injuries also increased from 2.0% to 2.5%, while the share of crashes involving minor or possible injuries saw a slight decline.

Severity is per crash event (most severe injury). 11 fatal crash events resulted in 12 persons killed.

Outcome by Severity (Crash Events)

Fatal11fatal crashes0.6%
120.0%prior 5
Serious Injury50serious injury crashes2.5%
22.0%prior 41
Minor Injury230minor injury crashes11.7%
-6.9%prior 247
Possible Injury131possible injury crashes6.6%
-16.6%prior 157
No Injury1,548no injury crashes78.6%
-3.8%prior 1,609

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 majority of crashes in both 2023 and 2022 occurred in clear weather and on dry roads. There was a notable year-over-year shift in crashes related to winter conditions, with incidents on snowy or icy roads falling from 10.5% of the total in 2022 to 3.1% in 2023. Conversely, the proportion of crashes occurring on wet roads increased from 13.6% to 16.3%.

Weather

Clear1,318 (66.9%)
2.5%prior 1,286
Cloudy340 (17.3%)
-10.1%prior 378
Rain204 (10.4%)
33.3%prior 153
Snow69 (3.5%)
-52.4%prior 145
Fog; Smog; Smoke17 (0.9%)
-15.0%prior 20
Other/Unknown9 (0.5%)
-60.9%prior 23
Sleet; Hail7 (0.4%)
-53.3%prior 15
Severe Crosswinds3 (0.2%)
-76.9%prior 13
Freezing Rain or Freezing Drizzle2 (0.1%)
-60.0%prior 5
Blowing Sand; Soil; Dirt; Snow1 (0.1%)
-95.2%prior 21

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

Lighting

Daylight1,188 (60.3%)
-5.6%prior 1,259
Dark - Roadway Not Lighted405 (20.6%)
0.0%prior 405
Dark - Lighted Roadway231 (11.7%)
-3.3%prior 239
Dawn/Dusk125 (6.3%)
6.8%prior 117
Other/Unknown15 (0.8%)
-51.6%prior 31
Dark - Unknown Roadway Lighting6 (0.3%)
-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

Dry1,572 (79.8%)
2.8%prior 1,529
Wet321 (16.3%)
14.6%prior 280
Snow47 (2.4%)
-69.7%prior 155
Ice14 (0.7%)
-77.0%prior 61
Other/Unknown6 (0.3%)
-64.7%prior 17
Water (Standing; Moving)6 (0.3%)
Slush4 (0.2%)
-73.3%prior 15

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 stable year-over-year, with Ford (634 vehicles) and Chevrolet (535 vehicles) being the most common makes in 2023, similar to 2022. An analysis of persons involved shows a shift in age demographics, as the proportion of individuals aged 26-34 increased from 13.4% of all persons involved in 2022 to 15.0% in 2023. The representation of other age groups remained relatively consistent.

Top Vehicle Makes (3,211 vehicles)

1
FORD634 (19.7%)
2.3%prior 620
2
CHEVROLET535 (16.7%)
-5.6%prior 567
3
HONDA206 (6.4%)
-5.1%prior 217
4
DODGE162 (5%)
-14.7%prior 190
5
JEEP157 (4.9%)
-8.2%prior 171
6
KIA151 (4.7%)
-0.7%prior 152
7
TOYOTA146 (4.5%)
-16.1%prior 174
8
GMC105 (3.3%)
-5.4%prior 111
9
HYUNDAI95 (3%)
-5.9%prior 101
10
CHRYSLER81 (2.5%)
26.6%prior 64

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

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

Sex Distribution (3,933 persons with recorded sex)

Male2,046 (52.0%)
-16.2%prior 2,441
Female1,887 (48.0%)
-3.9%prior 1,964

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: 1,970
  • Total persons involved: 4,125
  • Total vehicles involved: 3,211

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