GR Cup Analytics

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  Logo

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  About

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  Driver Insights

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  Pre Event Prediction

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  Post Event Analysis

Inspiration

The goal was to analyze GR Cup Data using race data that was provided. There were multiple races with different races data information

What it does

The app analyzes race 1 data for Barber Motorsports Park,Circuit of the Americas,Indianapolis, Sonoma race tracks. It provides driver insights, pre race predictions and post event analysis. The user can select a race and get the insights. It also provides the ability for the user to select a driver and see how well they performed compared to the average.

How we built it

It was built using python and streamlit. Python data analysis libraries were used (python, dumpy, scikit-learn, plotly). Streamlit was used to build a data web app which showcases the insights in a simple to understand format.

Challenges we ran into

The main challenge was understanding the data as there was no main data dictionary. Another challenge was inconsistent naming and columns information across races. The file names were inconsistent as well as some columns were not present in some of the race data. To tackle this the information was narrowed to Race 1 information for Barber Motorsports Park,Circuit of the Americas,Indianapolis, Sonoma race tracks.

What we learned

For me it was my first time working with race data, so it was a fun learning experience.

What's next for GR Cup Analytics

In terms of next steps it is to improve

• Improved Data: Work to ensure data is consistent across GR Cup races
• Experiment with more models: Use different modelling approaches -Multi-Race Comparison: Improve the application to provide the ability to analyze results and metrics across races

Built With

• html5
• python
• streamlit