A State-Space Perspective on Modelling and Inference for Online Skill Rating

arXiv:2308.02414v3 Announce Type: replace-cross
Abstract: We summarise popular methods used for skill rating in competitive sports, along with their inferential paradigms and introduce new approaches based on sequential Monte Carlo and discrete hidden Markov models. We advocate for a state-space model perspective, wherein players' skills are represented as time-varying, and match results serve as observed quantities. We explore the steps to construct the model and the three stages of inference: filtering, smoothing and parameter estimation. We examine the challenges of …

arxiv inference modelling perspective space stat.ap state stat.ml type