Yearly Traffic Safety Analysis

186 CRASHES IN
OHIO, OH
2022

All metrics benchmarked against2021

In 2022, Noble County recorded 186 total crashes, a 5.1% decrease from the 196 crashes reported in 2021. Despite the overall reduction in crashes, the number of fatalities increased from 5 in the prior year to 6 in the current year. The most significant temporal shift was the peak time for crashes, which moved from the afternoon in 2021 to the morning commute hour in 2022.

186

-5.1%was 196

Total Crash Events

6

20.0%was 5

Persons Killed

48

-21.3%was 61

Persons Injured

14

-6.7%was 15

Hit-and-Run Crashes

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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

The overall trend in traffic crashes in Noble County shows a year-over-year decrease. Total crashes fell by 5.1%, from 196 in 2021 to 186 in 2022. The number of people injured in these incidents also declined by 21.3% from 61 to 48, though total fatalities increased by one person from 5 to 6.

14

Hit-and-Run Crashes — 2022

-6.7% vs prior (15)

Hit-and-run incidents remained stable in Noble County between the two periods. In 2022, there were 14 hit-and-run crashes, a slight decrease from 15 in 2021. The hit-and-run rate was also nearly unchanged, moving from 7.7% of all crashes in 2021 to 7.5% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

6

Motorists Killed

Prior: 520.0%

2

Pedestrians Injured

Prior: 0%

46

Motorists Injured

Prior: 61-24.6%

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 shifted between the two periods. In 2022, the peak day for crashes was Sunday with 39 incidents, a change from 2021 when Wednesday and Monday were the joint peak days with 36 crashes each. The peak hour for crashes also moved from 2 p.m. in 2021 (17 crashes) to 7 a.m. in 2022 (15 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

While total crashes decreased, the severity of crashes increased in 2022 compared to 2021. The number of fatal crashes rose from 5 to 6, and the fatal crash rate increased from 2.6% to 3.2% of all crashes. Crashes resulting in serious injuries also saw a slight increase in proportion, from 3.1% of total crashes in 2021 to 3.8% in 2022.

Outcome by Severity (Crash Events)

Fatal6fatal crashes3.2%
20.0%prior 5
Serious Injury7serious injury crashes3.8%
16.7%prior 6
Minor Injury21minor injury crashes11.3%
-22.2%prior 27
Possible Injury11possible injury crashes5.9%
-8.3%prior 12
No Injury141no injury crashes75.8%
-3.4%prior 146

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 proportion of crashes occurring in adverse conditions increased in 2022. Crashes on wet roads rose from 12.2% of all incidents in 2021 to 19.4% in 2022. Similarly, the share of crashes happening during rain more than doubled, from 6.1% in the prior year to 12.4% in the current year, while the proportion of crashes in daylight decreased from 58.2% to 52.7%.

Weather

Clear106 (57.0%)
-8.6%prior 116
Cloudy39 (21.0%)
-17.0%prior 47
Rain23 (12.4%)
91.7%prior 12
Snow9 (4.8%)
-10.0%prior 10
Fog; Smog; Smoke6 (3.2%)
20.0%prior 5
Sleet; Hail2 (1.1%)
Blowing Sand; Soil; Dirt; Snow1 (0.5%)

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

Lighting

Daylight98 (52.7%)
-14.0%prior 114
Dark - Roadway Not Lighted70 (37.6%)
-1.4%prior 71
Dawn/Dusk10 (5.4%)
42.9%prior 7
Dark - Lighted Roadway7 (3.8%)
Dark - Unknown Roadway Lighting1 (0.5%)

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

Road Surface

Dry129 (69.4%)
-12.8%prior 148
Wet36 (19.4%)
50.0%prior 24
Snow14 (7.5%)
75.0%prior 8
Ice4 (2.2%)
-66.7%prior 12
Sand; Mud; Dirt; Oil; Gravel2 (1.1%)
Slush1 (0.5%)

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

Vehicles & Demographics

The types of vehicles involved in crashes remained broadly consistent year-over-year, with passenger cars, sport utility vehicles, and pickup trucks being the most common in both 2022 and 2021. Among vehicle makes, Chevrolet (39) and Ford (34) were the top two in 2022, though both saw a decrease in involvement from 2021 counts of 55 and 38, respectively. The age distribution of persons involved in crashes showed little change, with all age groups maintaining similar representation across both periods.

Top Vehicle Makes (243 vehicles)

1
CHEVROLET39 (16%)
-29.1%prior 55
2
FORD34 (14%)
-10.5%prior 38
3
TOYOTA22 (9.1%)
29.4%prior 17
4
GMC14 (5.8%)
40.0%prior 10
5
HONDA13 (5.3%)
-7.1%prior 14
6
DODGE12 (4.9%)
-52.0%prior 25
7
NISSAN11 (4.5%)
8
JEEP10 (4.1%)
-9.1%prior 11
9
BUICK7 (2.9%)
10
KIA7 (2.9%)

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

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

Sex Distribution (304 persons with recorded sex)

Male178 (58.6%)
-14.4%prior 208
Female126 (41.4%)
17.8%prior 107

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 6, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: ohio, OH
  • Total crash records analyzed: 186
  • Total persons involved: 316
  • Total vehicles involved: 243

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 6, 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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Noble County, OH Crash Report — 2022 | ThatCarHitMe.com