Driver Consistency - First Data Analysis

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  Driver Consistency Analysis

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  Modeling Weather - Wind Analysis

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  Telemetry Analysis - Understand variance by driver and laps

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  Overview Toyota Gazoo Racing Analytics - Overview

Inspiration

I'm a big fan F1, far long I've been wanting to play around motorsports data. This was the best opportunity I had to do so

What it does

It helps drivers to understand where are their gaps in consistency to make every lap closer to their best lap, once they get reliability in their laps, improvements in the best lap can be done, comparing output between drivers

How we built it

I used DuckDB as analytical database and integrate with observable framework to support the charts. In Duck DB I developed a dimensional data model

Challenges we ran into

• Amount of data and rendering time tradeoff: I needed to reduce the amount of data I was supposed to display to ensure a reasonable rendering time

Accomplishments that we're proud of

• Full dimensional model for telemetry, weather and laps

What we learned

• Integration between duck db and observable
• I didn't pay a single dollar for storage neither compute, I was able to perform this PoC in my laptop. Local development for the win!

What's next for Driver Consistency - First Data Analysis

• Add more information for weather, prediction ability over this is key to perform better in track
• Host the solution with a public domain
• Improve slice/dice features
• Run a exploratory data analysis, and identify the correlation between maneuver transitions and outcome
• Integrate PostGIS so more features can be extracted from the track maps, and use those features in the exploratory data analysis

Built With

• dbt
• duckdb
• observable