Comparing dominance of tennis' big three via multiple-output Bayesian quantile regression models
Bruno Santos

TL;DR
This paper compares the dominance of Djokovic, Federer, and Nadal in tennis using a Bayesian multivariate quantile regression model on match statistics, revealing surface-specific strengths and overall performance differences.
Contribution
It introduces a Bayesian multiple-output quantile regression approach to jointly analyze match duration and points won, accounting for dependence between these metrics in tennis performance comparison.
Findings
Nadal's dominance is strongest on clay courts.
Federer excels in court time during wins.
Djokovic leads in relative points won across surfaces.
Abstract
Tennis has seen a myriad of great male tennis players throughout its history and we are often interested in the discussion of who is/was the greatest player of all time. While we do not try to answer this question here, we delve into comparing some key statistics related to dominance over their opponents for the male players with the most Grand Slam titles, currently: Djokovic, Federer and Nadal, in alphabetical order. Here we consider the minutes played and the relative points in each of their completed matches, as a measure of dominance against other players. We consider important covariates such as surface, win or loss, type of tournament and whether their opponent was a top 20 ranked player in the world or not, to create a more complete comparison of their performance. We consider a Bayesian quantile regression model for multiple-output response variables to take into account the…
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Taxonomy
TopicsSports Analytics and Performance · Advanced Statistical Methods and Models · Forecasting Techniques and Applications
