Yearly Traffic Safety Analysis

683 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Mercer County recorded 683 total traffic crashes, an 8.0% decrease from the 742 crashes reported in 2021. Despite the overall reduction in collisions, the number of resulting fatalities more than doubled, increasing from 6 in 2021 to 13 in 2022. The number of fatal crashes also doubled from 6 to 12 year-over-year.

683

-8.0%was 742

Total Crash Events

13

116.7%was 6

Persons Killed

231

6.9%was 216

Persons Injured

39

14.7%was 34

Hit-and-Run Crashes

Note: "Persons Killed" (13) counts individual fatalities across all crash events. "Fatal" in the severity table below (12) 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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Mercer County showed a downward trend, decreasing by 8.0% from 742 in 2021 to 683 in 2022. However, this reduction in crash volume did not correspond to a decrease in severity. Total injuries rose by 6.9% from 216 to 231, and total fatalities increased from 6 to 13 year-over-year.

39

Hit-and-Run Crashes — 2022

14.7% vs prior (34)

Hit-and-run incidents trended upward in 2022. The total number of hit-and-run crashes increased from 34 in 2021 to 39 in 2022. The hit-and-run rate, which measures the percentage of total crashes that were hit-and-runs, also rose from 4.6% to 5.7% year-over-year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 10.0%

12

Motorists Killed

Prior: 5140.0%

8

Pedestrians Injured

Prior: 4100.0%

223

Motorists Injured

Prior: 2125.2%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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 2022 showed some shifts compared to the prior year. While Friday remained the peak day for crashes in both periods, the number of crashes on that day fell from 132 in 2021 to 107 in 2022. The peak hour for collisions shifted slightly earlier, moving from the 4 PM hour in 2021 (57 crashes) to the 3 PM hour in 2022 (53 crashes).

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened significantly in 2022 compared to 2021. The number of fatal crashes doubled from 6 to 12, increasing their share of all crashes from 0.8% to 1.8%. Similarly, serious injury crashes increased from 18 to 33, with their proportion rising from 2.4% to 4.8%. Consequently, the proportion of crashes with no reported injuries decreased from 78.2% in 2021 to 73.9% in 2022.

Severity is per crash event (most severe injury). 12 fatal crash events resulted in 13 persons killed.

Outcome by Severity (Crash Events)

Fatal12fatal crashes1.8%
100.0%prior 6
Serious Injury33serious injury crashes4.8%
83.3%prior 18
Minor Injury103minor injury crashes15.1%
4.0%prior 99
Possible Injury30possible injury crashes4.4%
-23.1%prior 39
No Injury505no injury crashes73.9%
-12.9%prior 580

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Road & Environmental Conditions

The distribution of environmental conditions during crashes shifted between the two periods. In 2022, a larger proportion of crashes occurred in clear weather (72.0%) compared to 2021 (65.4%). Correspondingly, the share of crashes happening in the rain decreased from 9.2% to 6.1%, and crashes on wet road surfaces fell from 16.2% to 13.0%. The proportion of crashes in daylight increased from 51.2% in 2021 to 54.8% in 2022.

Weather

Clear492 (72.0%)
1.4%prior 485
Cloudy108 (15.8%)
-27.0%prior 148
Rain42 (6.1%)
-38.2%prior 68
Snow27 (4.0%)
22.7%prior 22
Blowing Sand; Soil; Dirt; Snow6 (0.9%)
Fog; Smog; Smoke4 (0.6%)
-55.6%prior 9
Other/Unknown2 (0.3%)
Freezing Rain or Freezing Drizzle2 (0.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight374 (54.8%)
-1.6%prior 380
Dark - Roadway Not Lighted228 (33.4%)
-10.9%prior 256
Dark - Lighted Roadway41 (6.0%)
-14.6%prior 48
Dawn/Dusk37 (5.4%)
-21.3%prior 47
Dark - Unknown Roadway Lighting3 (0.4%)
-62.5%prior 8

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry539 (78.9%)
-8.6%prior 590
Wet89 (13.0%)
-25.8%prior 120
Snow36 (5.3%)
63.6%prior 22
Ice17 (2.5%)
112.5%prior 8
Other/Unknown1 (0.1%)
Slush1 (0.1%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The top three vehicle makes involved in crashes remained consistent year-over-year: Chevrolet (198 vehicles in 2022 vs. 217 in 2021), Ford (179 vs. 175), and Honda (96 vs. 103). An analysis of persons involved in crashes shows a relatively stable age distribution. The 16-20 age group represented 16.6% of individuals in 2022, a slight increase from 15.9% in 2021, while the 65+ age group's share also rose from 12.1% to 13.6%.

Top Vehicle Makes (1,049 vehicles)

1
CHEVROLET198 (18.9%)
-8.8%prior 217
2
FORD179 (17.1%)
2.3%prior 175
3
HONDA96 (9.2%)
-6.8%prior 103
4
DODGE81 (7.7%)
-13.8%prior 94
5
CHRYSLER44 (4.2%)
-30.2%prior 63
6
GMC43 (4.1%)
-23.2%prior 56
7
TOYOTA39 (3.7%)
-4.9%prior 41
8
BUICK34 (3.2%)
9.7%prior 31
9
JEEP33 (3.1%)
-10.8%prior 37
10
HYUNDAI25 (2.4%)
-26.5%prior 34

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (1,274 persons with recorded sex)

Male749 (58.8%)
-12.0%prior 851
Female525 (41.2%)
-16.1%prior 626

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: July 5, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 683
  • Total persons involved: 1,290
  • Total vehicles involved: 1,049

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: 2022." Published July 5, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/statewide/2022-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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Mercer County, OH Crash Report — 2022 | ThatCarHitMe.com