Multivariate Analysis on Player Performance & Market Value

Performed data cleaning, feature engineering, and variable selection to analyze how player roles relate to skills and market valuation.

• Applied Factor Analysis to condense 28 performance variables into 3 main components, capturing 75% of the variance and enhancing interpretability.

• Developed a Flexible Discriminant Analysis model for position classification (82% accuracy) and conducted MANOVA to reveal significant effects of position on salary and market value.