Yearly Traffic Safety Analysis

5,239 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In Mahoning County, total vehicle crashes decreased by 7.2% from 5,648 in 2022 to 5,239 in 2023. While the overall number of crashes fell, the most significant year-over-year change was a 73% reduction in traffic fatalities, which dropped from 37 in the prior period to 10 in the current period. The total number of injuries saw a slight increase of 1.6%, rising from 1,971 to 2,002.

5,239

-7.2%was 5,648

Total Crash Events

10

-73.0%was 37

Persons Killed

2,002

1.6%was 1,971

Persons Injured

644

-4.9%was 677

Hit-and-Run Crashes

Note: "Persons Killed" (10) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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

Traffic safety data for Mahoning County indicates a general downward trend in the total number of crashes, with a 7.2% decrease from 5,648 in 2022 to 5,239 in 2023. This decline was accompanied by a substantial drop in fatalities from 37 to 10. However, the total number of persons injured in crashes saw a slight increase, rising from 1,971 to 2,002.

644

Hit-and-Run Crashes — 2023

-4.9% vs prior (677)

The total number of hit-and-run crashes in Mahoning County decreased from 677 in 2022 to 644 in 2023. However, due to the larger overall decline in total crashes, the hit-and-run rate as a percentage of all incidents slightly increased. In 2023, hit-and-runs constituted 12.3% of all crashes, compared to 12.0% in the prior year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 5-100.0%

10

Motorists Killed

Prior: 32-68.8%

27

Pedestrians Injured

Prior: 1942.1%

1,975

Motorists Injured

Prior: 1,9521.2%

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 showed a minor shift between the two periods. The peak day for crashes moved from Friday in 2022 (947 incidents) to Thursday in 2023 (809 incidents). Similarly, the peak hour shifted slightly later in the day, from the 3 p.m. hour in the prior period (458 crashes) to the 4 p.m. hour in the current period (448 crashes).

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 severity of crashes improved significantly year-over-year, primarily driven by a sharp drop in fatal incidents. Fatal crashes decreased from 34 in 2022 to 10 in 2023, causing the fatal crash rate to fall from 0.6% to 0.2% of all crashes. The proportion of serious injury crashes also declined from 2.4% to 2.2%, while crashes resulting in minor or possible injuries saw a slight proportional increase.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.2%
-70.6%prior 34
Serious Injury113serious injury crashes2.2%
-16.3%prior 135
Minor Injury709minor injury crashes13.5%
4.0%prior 682
Possible Injury531possible injury crashes10.1%
-1.3%prior 538
No Injury3,876no injury crashes74%
-9.0%prior 4,259

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

While most crashes in both periods occurred in clear weather on dry roads, there was a noticeable shift in the proportion of crashes under adverse conditions. In 2023, crashes during rain increased to account for 12.1% of all incidents, up from 8.0% in 2022. Correspondingly, crashes on wet road surfaces rose from 17.3% to 22.3% of the total. Lighting conditions at the time of crashes remained proportionally consistent year-over-year, with daylight crashes comprising the majority in both periods.

Weather

Clear2,817 (53.8%)
-9.0%prior 3,095
Cloudy1,549 (29.6%)
-6.4%prior 1,655
Rain636 (12.1%)
40.4%prior 453
Snow170 (3.2%)
-51.0%prior 347
Other/Unknown24 (0.5%)
-7.7%prior 26
Fog; Smog; Smoke19 (0.4%)
-29.6%prior 27
Severe Crosswinds9 (0.2%)
Sleet; Hail9 (0.2%)
-50.0%prior 18
Freezing Rain or Freezing Drizzle6 (0.1%)
-57.1%prior 14

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

Lighting

Daylight3,483 (66.5%)
-9.0%prior 3,829
Dark - Lighted Roadway764 (14.6%)
-3.2%prior 789
Dark - Roadway Not Lighted704 (13.4%)
-2.9%prior 725
Dawn/Dusk249 (4.8%)
-4.2%prior 260
Dark - Unknown Roadway Lighting22 (0.4%)
-4.3%prior 23
Other/Unknown17 (0.3%)
-22.7%prior 22

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

Road Surface

Dry3,904 (74.5%)
-6.2%prior 4,163
Wet1,166 (22.3%)
19.5%prior 976
Snow89 (1.7%)
-71.4%prior 311
Ice54 (1.0%)
-60.9%prior 138
Other/Unknown15 (0.3%)
-28.6%prior 21
Slush6 (0.1%)
-76.0%prior 25
Water (Standing; Moving)4 (0.1%)
-55.6%prior 9
Sand; Mud; Dirt; Oil; Gravel1 (0.0%)
-80.0%prior 5

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

Vehicles & Demographics

The composition of vehicles involved in crashes remained stable year-over-year. Passenger Cars, Sport Utility Vehicles, and Pickups were the three most common vehicle types in both 2022 and 2023. The top vehicle makes involved also showed little change, with Chevrolet and Ford leading in both periods. The age distribution of persons involved in crashes was also consistent, with the 26-34 age group representing the largest share in both years.

Top Vehicle Makes (9,239 vehicles)

1
CHEVROLET1,849 (20%)
-4.1%prior 1,928
2
FORD1,252 (13.6%)
-13.1%prior 1,441
3
HONDA537 (5.8%)
-5.6%prior 569
4
TOYOTA530 (5.7%)
-2.6%prior 544
5
NISSAN436 (4.7%)
3.1%prior 423
6
JEEP432 (4.7%)
-3.8%prior 449
7
KIA428 (4.6%)
-10.5%prior 478
8
DODGE414 (4.5%)
-6.1%prior 441
9
HYUNDAI320 (3.5%)
14.7%prior 279
10
BUICK307 (3.3%)
7.7%prior 285

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

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

Sex Distribution (11,864 persons with recorded sex)

Male6,223 (52.5%)
-7.0%prior 6,694
Female5,641 (47.5%)
-3.9%prior 5,870

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: 5,239
  • Total persons involved: 12,265
  • Total vehicles involved: 9,239

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: 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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Mahoning County, OH Crash Report — 2023 | ThatCarHitMe.com