Hierarchical Bayesian modeling (also called multilevel modeling) is one of the most reliable ways to build predictive and inferential models when your data has natural grouping—teams, players, seasons, leagues, referees, venues, or even game states. In sports analytics, that grouping is unavoidable. In R, hierarchical Bayesian models are commonly …