Yearly Traffic Safety Analysis

2,401 CRASHES IN
OHIO, OH
2023

All metrics benchmarked against2022

In 2023, Miami County recorded 2,401 total crashes, a slight decrease of approximately 1% from the 2,424 crashes reported in 2022. Despite the marginal drop in overall collisions, the number of fatalities saw a significant year-over-year increase. The most notable change was the rise in total fatalities from 9 in 2022 to 16 in 2023.

2,401

-0.9%was 2,424

Total Crash Events

16

77.8%was 9

Persons Killed

601

-8.2%was 655

Persons Injured

368

7.3%was 343

Hit-and-Run Crashes

Note: "Persons Killed" (16) counts individual fatalities across all crash events. "Fatal" in the severity table below (14) 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 Miami County remained relatively stable, with total collisions decreasing by just under 1% from 2,424 in 2022 to 2,401 in 2023. While total crashes and injuries (601 in 2023 vs. 655 in 2022) saw a modest decline, fatal outcomes increased significantly. The number of fatalities rose from 9 in the prior year to 16 in the current year.

368

Hit-and-Run Crashes — 2023

7.3% vs prior (343)

Hit-and-run incidents in Miami County trended upward in 2023. The total number of hit-and-run crashes increased from 343 in 2022 to 368 in 2023. This rise in volume also resulted in a higher hit-and-run rate, which grew from 14.2% of all crashes in the prior year to 15.3% in the current year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

16

Motorists Killed

Prior: 977.8%

17

Pedestrians Injured

Prior: 1330.8%

584

Motorists Injured

Prior: 642-9.0%

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 Miami County showed consistency year-over-year. Friday remained the peak day for crashes in both 2023 (414 incidents) and 2022 (426 incidents). Similarly, the 3 p.m. hour was the most frequent time for collisions in both periods, with 201 crashes in 2023 and 203 in 2022, indicating no significant shift in daily or hourly crash trends.

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 slightly decreased, the severity of crashes worsened in 2023 compared to 2022. The number of fatal crashes increased from 9 to 14, raising the fatal crash rate from 0.37% to 0.58%. Conversely, serious injury crashes declined from 55 to 48, while minor injury crashes increased from 218 to 241. The proportion of crashes resulting in no injuries remained stable at approximately 81% for both years.

Severity is per crash event (most severe injury). 14 fatal crash events resulted in 16 persons killed.

Outcome by Severity (Crash Events)

Fatal14fatal crashes0.6%
55.6%prior 9
Serious Injury48serious injury crashes2%
-12.7%prior 55
Minor Injury241minor injury crashes10%
10.6%prior 218
Possible Injury145possible injury crashes6%
-16.2%prior 173
No Injury1,953no injury crashes81.3%
-0.8%prior 1,969

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

Crash conditions in 2023 were broadly similar to 2022, with most incidents occurring in daylight (1,490 in both years) and on dry roads (1,913 in 2023 vs. 1,813 in 2022). There was a notable decrease in crashes occurring in adverse winter conditions; incidents on snowy roads dropped from 100 to 25, and crashes on icy surfaces fell from 63 to 25. Crashes during rainy conditions increased from 207 to 252, while those in snowy weather decreased from 109 to 43.

Weather

Clear1,498 (62.4%)
3.7%prior 1,444
Cloudy537 (22.4%)
-9.4%prior 593
Rain252 (10.5%)
21.7%prior 207
Snow43 (1.8%)
-60.6%prior 109
Other/Unknown36 (1.5%)
-14.3%prior 42
Fog; Smog; Smoke20 (0.8%)
122.2%prior 9
Freezing Rain or Freezing Drizzle6 (0.2%)
-25.0%prior 8
Sleet; Hail4 (0.2%)
Blowing Sand; Soil; Dirt; Snow3 (0.1%)
-50.0%prior 6
Severe Crosswinds2 (0.1%)

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

Lighting

Daylight1,490 (62.1%)
0.0%prior 1,490
Dark - Roadway Not Lighted435 (18.1%)
0.2%prior 434
Dark - Lighted Roadway281 (11.7%)
-4.7%prior 295
Dawn/Dusk148 (6.2%)
1.4%prior 146
Other/Unknown36 (1.5%)
-20.0%prior 45
Dark - Unknown Roadway Lighting11 (0.5%)
-21.4%prior 14

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

Road Surface

Dry1,913 (79.7%)
5.5%prior 1,813
Wet404 (16.8%)
-1.5%prior 410
Other/Unknown30 (1.2%)
0.0%prior 30
Ice25 (1.0%)
-60.3%prior 63
Snow25 (1.0%)
-75.0%prior 100
Slush2 (0.1%)
Water (Standing; Moving)2 (0.1%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent, with Chevrolet (674 vehicles), Ford (575), and Honda (452) leading in 2023, similar to the prior year. An analysis of persons involved shows a shift in age demographics; there was a decrease in individuals aged 16-20 (from 695 to 620) and 26-34 (from 732 to 692). Conversely, the number of persons aged 35-44 and 65+ involved in crashes increased, rising to 691 and 671, respectively.

Top Vehicle Makes (4,098 vehicles)

1
CHEVROLET674 (16.4%)
-5.2%prior 711
2
FORD575 (14%)
-1.7%prior 585
3
HONDA452 (11%)
5.6%prior 428
4
TOYOTA240 (5.9%)
-6.3%prior 256
5
DODGE217 (5.3%)
-11.8%prior 246
6
GMC187 (4.6%)
13.3%prior 165
7
NISSAN166 (4.1%)
-3.5%prior 172
8
JEEP147 (3.6%)
3.5%prior 142
9
KIA119 (2.9%)
11.2%prior 107
10
CHRYSLER114 (2.8%)
25.3%prior 91

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

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

Sex Distribution (4,894 persons with recorded sex)

Male2,712 (55.4%)
1.6%prior 2,669
Female2,182 (44.6%)
-1.7%prior 2,219

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 5, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 2,401
  • Total persons involved: 5,140
  • Total vehicles involved: 4,098

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 5, 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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Miami County, OH Crash Report — 2023 | ThatCarHitMe.com