Yearly Traffic Safety Analysis

175 CRASHES IN
CONNEAUT, OH
2022

All metrics benchmarked against2021

Total crashes in Conneaut increased from 162 in 2021 to 175 in 2022, representing an 8.02% rise. A significant shift was the occurrence of one fatality in 2022, compared to zero fatalities in 2021. Additionally, pedestrian and bicycle crashes, which were absent in 2021, emerged with 3 and 1 crashes respectively in 2022.

175

8.0%was 162

Total Crash Events

1

Persons Killed

44

-17.0%was 53

Persons Injured

24

14.3%was 21

Hit-and-Run Crashes

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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, Conneaut experienced an upward trend in total crashes, increasing by 8.02% from 162 in 2021 to 175 in 2022. Fatalities also saw an increase, with one fatality recorded in 2022 compared to none in 2021. Conversely, total injuries decreased by 16.98%, from 53 in 2021 to 44 in 2022.

24

Hit-and-Run Crashes — 2022

14.3% vs prior (21)

Hit-and-run crashes increased from 21 in 2021 to 24 in 2022. The hit-and-run crash rate slightly increased from 13% in 2021 to 13.7% in 2022.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 00.0%

1

Motorists Killed

Prior: 0%

3

Pedestrians Injured

Prior: 0%

41

Motorists Injured

Prior: 53-22.6%

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 peak day for crashes remained Friday in both years, with 33 crashes in 2022 and 34 crashes in 2021. The peak hour for crashes shifted from 3 PM with 20 crashes in 2021 to 5 PM with 15 crashes in 2022. Monthly patterns show October as the peak crash month in 2022 with 21 crashes, while July was the peak in 2021 with 23 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

Conneaut recorded one fatal crash and one fatality in 2022, whereas no fatal crashes or fatalities occurred in 2021. Serious injuries (Severity A) decreased from 6 (3.7% of crashes) in 2021 to 3 (1.7%) in 2022. Minor injuries (Severity B) increased from 14 (8.6%) to 17 (9.7%), while possible injuries (Severity C) decreased from 16 (9.9%) to 14 (8%).

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
Serious Injury3serious injury crashes1.7%
-50.0%prior 6
Minor Injury17minor injury crashes9.7%
21.4%prior 14
Possible Injury14possible injury crashes8%
-12.5%prior 16
No Injury140no injury crashes80%
11.1%prior 126

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

Clear weather remained the most common condition for crashes, increasing from 83 crashes in 2021 to 109 in 2022. Crashes on snowy road surfaces increased significantly from 7 in 2021 to 18 in 2022, and those on icy surfaces rose from 3 to 14. Daylight remained the predominant lighting condition for crashes, with 114 crashes in 2022 compared to 113 in 2021.

Weather

Clear109 (62.3%)
31.3%prior 83
Cloudy29 (16.6%)
-37.0%prior 46
Rain18 (10.3%)
-18.2%prior 22
Snow16 (9.1%)
77.8%prior 9
Sleet; Hail2 (1.1%)
Fog; Smog; Smoke1 (0.6%)

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

Lighting

Daylight114 (65.1%)
0.9%prior 113
Dark - Roadway Not Lighted27 (15.4%)
8.0%prior 25
Dark - Lighted Roadway26 (14.9%)
36.8%prior 19
Dawn/Dusk7 (4.0%)
Dark - Unknown Roadway Lighting1 (0.6%)

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

Road Surface

Dry105 (60.0%)
-2.8%prior 108
Wet37 (21.1%)
-9.8%prior 41
Snow18 (10.3%)
157.1%prior 7
Ice14 (8.0%)
Slush1 (0.6%)

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 slightly increased from 275 in 2021 to 277 in 2022. Chevrolet remained the most frequently involved vehicle make, although its count decreased from 47 to 44, while Toyota involvement increased from 18 to 26. Among persons involved, the 16-20 age group saw a significant increase from 27 to 48, and the 45-54 age group also rose from 36 to 55.

Top Vehicle Makes (277 vehicles)

1
CHEVROLET44 (15.9%)
-6.4%prior 47
2
FORD35 (12.6%)
-10.3%prior 39
3
TOYOTA26 (9.4%)
44.4%prior 18
4
HONDA24 (8.7%)
20.0%prior 20
5
OTHER/UNKNOWN19 (6.9%)
58.3%prior 12
6
DODGE17 (6.1%)
0.0%prior 17
7
JEEP15 (5.4%)
66.7%prior 9
8
KIA9 (3.2%)
12.5%prior 8
9
HYUNDAI9 (3.2%)
-25.0%prior 12
10
SUBARU8 (2.9%)
33.3%prior 6

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

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

Sex Distribution (331 persons with recorded sex)

Male188 (56.8%)
11.2%prior 169
Female143 (43.2%)
-12.8%prior 164

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: Conneaut, OH
  • Total crash records analyzed: 175
  • Total persons involved: 361
  • Total vehicles involved: 277

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). "Conneaut, 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/conneaut/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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Conneaut, OH Crash Report — 2022 | ThatCarHitMe.com