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Conducted independent t-test to compare the quality across Frisbee leagues. Developed a prediction model to predict the outcome of Frisbee games by analyzing rolling statistics from previous matches. Implemented k-means clustering with PCA to identify specific player roles within a Frisbee team

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Kalyugsasur/AUDL---Ultimate-frisbee-analysis

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AUDL---Ultimate-frisbee-analysis

This was a capstone project for "DS-GA1001 - Intro to Data Science". As part of the project, we ran hypothesis testing to identify if there were any differences across the different AUDL leagues followed by creating a prediction algorithm for predicting win vs loss in a single match. Finally we classified each player into a specific role they play in the team by using the statistics recorded from each game. Please refer to the report for further details around the analysis

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Conducted independent t-test to compare the quality across Frisbee leagues. Developed a prediction model to predict the outcome of Frisbee games by analyzing rolling statistics from previous matches. Implemented k-means clustering with PCA to identify specific player roles within a Frisbee team

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