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Yearly Traffic Safety Analysis

64 CRASHES IN
CLYDE, OH
2022

All metrics benchmarked against2021

In 2022, Clyde experienced 64 total crashes, a decrease of 14.7% compared to the 75 crashes recorded in 2021. Despite this reduction in overall crash incidents, total injuries saw a substantial increase of 111.8%, rising from 17 in 2021 to 36 in 2022. This shift towards more injury-involved crashes is the most notable change year-over-year.

▼ -14.7%was 75

Total Crash Events

Persons Killed

▲ 111.8%was 17

Persons Injured

▼ -40.0%was 5

Hit-and-Run Crashes

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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, the total number of crashes in Clyde decreased by 14.7%, from 75 crashes in 2021 to 64 crashes in 2022. However, total injuries increased significantly by 111.8%, from 17 injuries in 2021 to 36 injuries in 2022, indicating a rise in the severity of crash outcomes.

Hit-and-Run Crashes — 2022

▼ -40.0% vs prior (5)

Hit-and-run crashes decreased from 5 incidents in 2021 to 3 in 2022. This led to a reduction in the hit-and-run rate, which fell from 6.7% of all crashes in 2021 to 4.7% in 2022, indicating a downward trend.

Vulnerable Road User Casualties

Motorists Killed

Prior: 0→0.0%

Motorists Injured

Prior: 16↑125.0%

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 peak day for crashes shifted from Wednesday in 2021, which had 18 crashes, to Tuesday in 2022, with 16 crashes. The peak hour also changed, moving from 12p with 9 crashes in 2021 to 3p with 10 crashes in 2022, suggesting a shift in high-incident times.

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 there were no fatalities in either period, the proportion of crashes resulting in injuries increased year-over-year. Serious injuries (Severity A) rose from 0 in 2021 to 2 in 2022, and minor injuries (Severity B) increased from 8 to 13. Consequently, the percentage of crashes with no injuries decreased from 80% in 2021 to 62.5% in 2022.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes3.1%

Minor Injury13minor injury crashes20.3%

↑62.5%prior 8

Possible Injury9possible injury crashes14.1%

↑28.6%prior 7

No Injury40no injury crashes62.5%

↓-33.3%prior 60

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

Crashes occurring in clear weather conditions accounted for 79.7% of incidents in 2022, an increase from 69.3% in 2021, despite a slight decrease in the absolute count (51 vs 52). Similarly, crashes on dry road surfaces increased proportionally from 80% in 2021 to 87.5% in 2022, even as the total number of dry-road crashes decreased from 60 to 56. This indicates a higher proportion of crashes occurred under ideal conditions in the current period.

Weather

Clear51 (79.7%)

↓-1.9%prior 52

Cloudy9 (14.1%)

↓-43.8%prior 16

Rain2 (3.1%)

Blowing Sand; Soil; Dirt; Snow1 (1.6%)

Fog; Smog; Smoke1 (1.6%)

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

Lighting

Daylight48 (75.0%)

↓-11.1%prior 54

Dark - Lighted Roadway10 (15.6%)

→0.0%prior 10

Dawn/Dusk4 (6.3%)

↓-55.6%prior 9

Dark - Roadway Not Lighted2 (3.1%)

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

Road Surface

Dry56 (87.5%)

↓-6.7%prior 60

Wet6 (9.4%)

↓-33.3%prior 9

Ice1 (1.6%)

Snow1 (1.6%)

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

Vehicles & Demographics

The total number of vehicles involved in crashes decreased from 144 in 2021 to 130 in 2022. A notable shift was observed in Semi-Tractor involvement, which increased from 2 vehicles in 2021 to 7 in 2022. The age distribution of persons involved saw a significant decrease in the 0-15 age group, from 47 persons in 2021 to 18 in 2022.

Top Vehicle Makes (130 vehicles)

FORD34 (26.2%)

↓-10.5%prior 38

CHEVROLET29 (22.3%)

↑7.4%prior 27

DODGE8 (6.2%)

↓-42.9%prior 14

JEEP8 (6.2%)

↑60.0%prior 5

HONDA7 (5.4%)

CHRYSLER7 (5.4%)

↓-30.0%prior 10

LINCOLN4 (3.1%)

TOYOTA4 (3.1%)

↓-33.3%prior 6

NISSAN4 (3.1%)

↓-20.0%prior 5

RAM3 (2.3%)

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

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

Sex Distribution (173 persons with recorded sex)

Male97 (56.1%)

↓-19.8%prior 121

Female76 (43.9%)

↓-12.6%prior 87

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: August 23, 2026

Data Coverage

Reporting period: 2022-01-01 through 2022-12-31 (365 days)
Geographic scope: Clyde, OH
Total crash records analyzed: 64
Total persons involved: 174
Total vehicles involved: 130

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). "Clyde, OH Crash Intelligence Report: 2022." Published August 23, 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/clyde/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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