Yearly Traffic Safety Analysis

2,127 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Fairfield County recorded 2,127 total crashes, a 20.4% decrease from the 2,673 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities increased from 12 in the prior year to 15 in the current year. This resulted in the fatal crash rate rising from 0.45% to 0.71% year-over-year.

2,127

-20.4%was 2,673

Total Crash Events

15

25.0%was 12

Persons Killed

852

-11.9%was 967

Persons Injured

286

-29.0%was 403

Hit-and-Run Crashes

Note: "Persons Killed" (15) counts individual fatalities across all crash events. "Fatal" in the severity table below (15) 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 collisions in Fairfield County saw a significant downward trend, with total crashes decreasing by 20.4% from 2,673 in 2022 to 2,127 in 2023. The number of injuries also fell by 11.9% from 967 to 852. However, fatalities bucked this trend, increasing by 25% from 12 to 15 over the same period.

286

Hit-and-Run Crashes — 2023

-29.0% vs prior (403)

Hit-and-run incidents decreased in both absolute numbers and as a percentage of total crashes. In 2023, there were 286 hit-and-run crashes, down from 403 in 2022. This represents a drop in the hit-and-run rate from 15.1% of all crashes in the prior year to 13.4% in the current year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0%

14

Motorists Killed

Prior: 1216.7%

22

Pedestrians Injured

Prior: 26-15.4%

830

Motorists Injured

Prior: 941-11.8%

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

Temporal patterns remained largely consistent year-over-year, with Friday being the peak day for crashes in both 2023 (361 crashes) and 2022 (458 crashes). The peak hour for collisions shifted slightly from the 3 p.m. hour in the prior period (240 crashes) to the 4 p.m. hour in the current period (179 crashes). Crash volumes decreased across all days of the week and most hours of the day compared to the previous year.

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 increased from 0.45% to 0.71%, with fatal crashes rising from 12 to 15. The proportion of serious injury crashes also grew, from 2.5% of all crashes in 2022 (68 incidents) to 3.8% in 2023 (81 incidents). Consequently, the share of no-injury crashes decreased from 74.1% to 72.5% of the total.

Outcome by Severity (Crash Events)

Fatal15fatal crashes0.7%
25.0%prior 12
Serious Injury81serious injury crashes3.8%
19.1%prior 68
Minor Injury310minor injury crashes14.6%
-21.9%prior 397
Possible Injury178possible injury crashes8.4%
-17.6%prior 216
No Injury1,543no injury crashes72.5%
-22.1%prior 1,980

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 periods occurred in clear weather and on dry roads, with these conditions representing a stable proportion of incidents year-over-year. In 2023, 61.5% of crashes happened in clear weather, compared to 62.3% in 2022. There was a slight proportional increase in crashes on wet roads (19.4% in 2023 vs. 16.1% in 2022). Conversely, crashes involving snow on the road surface decreased from 4.2% of all incidents in 2022 to 1.9% in 2023.

Weather

Clear1,309 (61.5%)
-21.4%prior 1,665
Cloudy490 (23.0%)
-15.2%prior 578
Rain256 (12.0%)
0.8%prior 254
Snow40 (1.9%)
-64.3%prior 112
Other/Unknown16 (0.8%)
-23.8%prior 21
Fog; Smog; Smoke11 (0.5%)
-31.3%prior 16
Severe Crosswinds2 (0.1%)
Blowing Sand; Soil; Dirt; Snow1 (0.0%)
-90.0%prior 10
Freezing Rain or Freezing Drizzle1 (0.0%)
-88.9%prior 9
Sleet; Hail1 (0.0%)
-83.3%prior 6

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

Lighting

Daylight1,438 (67.6%)
-22.3%prior 1,851
Dark - Roadway Not Lighted267 (12.6%)
-27.0%prior 366
Dark - Lighted Roadway246 (11.6%)
-13.7%prior 285
Dawn/Dusk154 (7.2%)
7.7%prior 143
Other/Unknown15 (0.7%)
-11.8%prior 17
Dark - Unknown Roadway Lighting7 (0.3%)
-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

Dry1,654 (77.8%)
-19.3%prior 2,049
Wet412 (19.4%)
-4.4%prior 431
Snow28 (1.3%)
-74.5%prior 110
Ice20 (0.9%)
-60.8%prior 51
Other/Unknown10 (0.5%)
-37.5%prior 16
Water (Standing; Moving)2 (0.1%)
Slush1 (0.0%)
-92.9%prior 14

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

Vehicles & Demographics

Passenger Cars, Sport Utility Vehicles, and Pick-ups were the three most common vehicle types involved in crashes in both years, with their proportions remaining stable. Ford (568 vehicles), Honda (535), and Chevrolet (455) were the top three makes involved in crashes in 2023, with Honda overtaking Chevrolet for the second position compared to 2022. The age distribution of persons involved in crashes was also consistent, with the 26-34 age group representing the largest share in both 2023 (15.3%) and 2022 (14.8%).

Top Vehicle Makes (3,878 vehicles)

1
FORD568 (14.6%)
-14.6%prior 665
2
HONDA535 (13.8%)
-15.7%prior 635
3
CHEVROLET455 (11.7%)
-28.5%prior 636
4
TOYOTA408 (10.5%)
-16.2%prior 487
5
NISSAN192 (5%)
-26.4%prior 261
6
KIA170 (4.4%)
-17.9%prior 207
7
JEEP160 (4.1%)
-2.4%prior 164
8
DODGE157 (4%)
-28.6%prior 220
9
HYUNDAI140 (3.6%)
-28.9%prior 197
10
GMC100 (2.6%)
-17.4%prior 121

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

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

Sex Distribution (4,846 persons with recorded sex)

Male2,597 (53.6%)
-15.7%prior 3,079
Female2,249 (46.4%)
-16.5%prior 2,694

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: 2,127
  • Total persons involved: 5,023
  • Total vehicles involved: 3,878

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