This project will extend the analysis conducted by Seri, Rocci, and Murphy to investigate the performances of rugby players in major leagues using a soft clustering approach (https://link.springer.com/article/10.1007/s00180-025-01655-w). Rather than assigning each player to a single performance category, soft clustering will allow players to be associated with multiple performance profiles to varying degrees, based on a range of performance indicators. This approach aims to provide a more nuanced characterization of players and to identify similarities and differences in their performance patterns. Data are anticipated to be sourced from available online repositories, e.g https://github.com/seanyboi/rugbypy.
Required skills: Statistical Inference, Statistical Modelling