Yearly Traffic Safety Analysis

51 CRASHES IN
GATES MILLS, OH
2024

All metrics benchmarked against2023

Total crashes increased from 29 in 2023 to 51 in 2024, representing a 75.86% rise year-over-year. Total injuries saw a substantial increase of 171.4%, rising from 7 in 2023 to 19 in 2024. This indicates a significant escalation in both crash frequency and injury severity within the jurisdiction.

51

75.9%was 29

Total Crash Events

0

Persons Killed

19

171.4%was 7

Persons Injured

4

100.0%was 2

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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

The overall trend shows a considerable increase in crash activity year-over-year. Total crashes rose from 29 in 2023 to 51 in 2024, marking a 75.86% increase. Concurrently, the number of injured persons surged by 171.4%, from 7 in 2023 to 19 in 2024.

4

Hit-and-Run Crashes — 2024

100.0% vs prior (2)

Hit-and-run crashes increased from 2 in 2023 to 4 in 2024. The hit-and-run crash rate also saw a slight increase, rising from 6.9% of total crashes in 2023 to 7.8% in 2024. This indicates an upward trend in both the absolute number and proportion of hit-and-run incidents.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 00.0%

19

Motorists Injured

Prior: 7171.4%

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · 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 periods, with 11 crashes in 2024 compared to 6 in 2023. However, the peak hour shifted from 12p with 4 crashes in 2023 to 5p with 8 crashes in 2024. This suggests a change in the most crash-prone time of day, moving towards the evening commute.

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Both periods reported 0 fatalities. The number of serious injury crashes decreased from 2 (6.9% of total crashes) in 2023 to 1 (2% of total crashes) in 2024. However, minor injury crashes increased from 2 to 3, and possible injury crashes increased from 3 to 6, contributing to an overall rise in total injuries from 7 to 19.

Outcome by Severity (Crash Events)

Serious Injury1serious injury crashes2%
-50.0%prior 2
Minor Injury3minor injury crashes5.9%
50.0%prior 2
Possible Injury6possible injury crashes11.8%
100.0%prior 3
No Injury41no injury crashes80.4%
86.4%prior 22

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Road & Environmental Conditions

Crashes occurring in clear weather conditions increased from 11 in 2023 to 28 in 2024, while rain-related crashes increased from 7 to 8. Similarly, crashes on dry road surfaces rose from 11 to 32, and those on wet surfaces increased from 6 to 10. Daylight crashes also saw an increase, from 22 in 2023 to 39 in 2024.

Weather

Clear28 (54.9%)
154.5%prior 11
Cloudy8 (15.7%)
60.0%prior 5
Rain8 (15.7%)
14.3%prior 7
Snow6 (11.8%)
0.0%prior 6
Sleet; Hail1 (2.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight39 (76.5%)
77.3%prior 22
Dark - Roadway Not Lighted6 (11.8%)
Dark - Lighted Roadway5 (9.8%)
Dawn/Dusk1 (2.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry32 (62.7%)
190.9%prior 11
Wet10 (19.6%)
66.7%prior 6
Snow7 (13.7%)
Other/Unknown1 (2.0%)
Water (Standing; Moving)1 (2.0%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The total number of vehicles involved in crashes increased from 48 in 2023 to 86 in 2024. Passenger Cars involved in crashes increased from 18 to 41, and Sport Utility Vehicles from 19 to 29. Regarding persons involved, the 0-15 and 16-20 age groups saw decreases in representation, while the 21-25, 55-64, and 65+ age groups saw increases.

Top Vehicle Makes (86 vehicles)

1
TOYOTA11 (12.8%)
120.0%prior 5
2
CHEVROLET10 (11.6%)
42.9%prior 7
3
JEEP10 (11.6%)
4
FORD8 (9.3%)
-20.0%prior 10
5
HONDA7 (8.1%)
6
SUBARU6 (7%)
7
KIA4 (4.7%)
8
BMW3 (3.5%)
9
GMC2 (2.3%)
10
NISSAN2 (2.3%)

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (110 persons with recorded sex)

Male66 (60.0%)
73.7%prior 38
Female44 (40.0%)
-31.3%prior 64

Source: Ohio Crash Data (ODOT TIMS) · Csv Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: July 6, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: Gates Mills, OH
  • Total crash records analyzed: 51
  • Total persons involved: 111
  • Total vehicles involved: 86

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). "Gates Mills, OH Crash Intelligence Report: 2024." Published July 6, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Ohio Crash Data (ODOT TIMS), Csv Open Data. Available at: https://thatcarhitme.com/crash-data/ohio/gates-mills/2024-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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