In the present study, we aim at showing how some characteristics of the serve summed up in the resulting ball trajectory can determine the efficiency of tennis serves. To that purpose, we analyzed a big set of data collected between 2003 and 2008 at international ATP, WTA and Grand Slam tournaments and corresponding to 84 tournaments, 1729 matches, 262,596 points. Using time-dependent three-dimensional ball trajectory data recorded by the automated ball tracking Hawk-Eye system, we show the relationships that exists between the characteristics of the serve kinematics and impacts on the ground on the gain of the points.
© Copyright 2015 Machine Learning and Data Mining for Sports Analytics ECML/PKDD 2015 workshop. Published by Department of Computer Science, KU Leuven. All rights reserved.