Once we can measure player impact patterns on the return, it is natural to use these patterns to compare players. This post delves into these comparisons and presents a set of distinct impact types that describe the impact styles of top ATP players when returning the first serve on hardcourts.
Which of the top ATP players are the most aggressive on the serve return? Which are the most defensive? Is Andrey Rublev’s serve return style closer to Roger Federer’s or Novak Djokovic’s? In this post, I introduce an interactive visualization tool to help answer these and many other questions about the return impact of top men’s tennis players.
The serve return is the most important shot for a receiver. What can receivers do to put themselves in a better position to make a good impact on the serve return? The answer to that question is too big a task for one blog post alone. As a small first step, I take a look at a new public data source that includes the position of players at the time of return impact in ATP matches. Through a handful of case studies, it delves into the kind of patterns in return positioning these data could help reveal.
The 2020 tennis calendar was put into a tailspin by the pandemic. In a normal year, a player’s competitive schedule can tell us a lot about a player’s overall readiness to play, what I will call a player’s ‘availability’. In this post, I show how a Hidden Markov Model can be used to describe a player’s competitive schedule as the output from periods of varying availability and how irregularities in availability can be a tell-tale sign of probable injury.
Can you ever have too much height in tennis? In this post, Peter Tea analyzes two sides of the “big server” equation as he delves into the influence of height on the rate of aces hit and aces allowed among ATP players.