Abstract

The purpose of this study was to investigate a long-range correlation in elite tennis players’ dynamic behavior during tennis competitions. Fractal dynamics of movement time series in expert tennis players were analyzed using the Detrended Fluctuation Analysis (DFA), which provides the stability of the fluctuations in the time series. Three match videos of elite tennis players (1st round between professionals, the semi-final between top-ranked professionals, and the boys’ final between junior players) were selected and downloaded from the open-source website. Every frame from the high-definition video was captured using Kinovea (sports analysis software), then imported into a custom written MATLAB program that can manually track the displacements of players and tennis balls on the court. Distance time series between player and center mark on the baseline in addition to distance time series between player and tennis ball displacements, were made for each player. The distance time series to the center mark showed that the winner displayed a long-range correlation, αwinner=0.53, whereas the loser had a random correlation, αloser=0.47, in the 1st round. In the boys’ final, the winner had αwinner=0.58 and the loser αloser=0.41. A long-range correlation did not emerge in the semifinal when both players were top ranked players, αwinner =0.45, αloser=0.47. The winner might show greater DFA alpha values than 0.5 as a long-range correlation, indicating the winner maintained a relatively consistent distance from the center of the court during the competition.

Keywords:Performance analysis; Dynamic behavior; Video analysis; Tennis match