The winning probability of a game and the importance of points in tennis matches

(Die Gewinnwahrscheinlichkeit in einem Spiel und die Bedeutung von Punkten in Tennisspielen)

Purpose: This study builds a stochastic model of a discrete-time Markov chain (DTMC) that fits well with a dataset of professional playing records. Methods: The point-by-point dataset of Men`s single matches played in the Association of Tennis Professionals (ATP) tour from 2011 to 2015 is analyzed. A long-debated assumption on the iid-ness in the point winning probability of the server is statistically tested. A DTMC model is then developed to analyze the dataset further. Results: The statistical test results indicate that the identicality of point winning probabilities is not a valid assumption. For example, the server`s point winning probability from scores 40:0, 30:15, 15:30, and 0:40 are significantly different. On the other hand, the independence is a generally valid assumption except for 40:15 where who won the previous point influences the point winning probability. Game winning probabilities and the importance of each point in winning a game are analyzed using the DTMC model by court surfaces and player groups of the different levels of serve effectiveness. Conclusion: Extensive empirical validation concludes unsealed debates over the stochastic models for tennis. The presented results reveal interesting properties in professional tennis matches.
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Schlagworte: Tennis Analyse Modellierung Prognose
Notationen: Spielsportarten
Tagging: Big Data Markov Ketten
DOI: 10.1080/02701367.2019.1666203
Veröffentlicht in: Research Quarterly for Exercise and Sport
Veröffentlicht: 2020
Jahrgang: 91
Heft: 3
Seiten: 361-372
Dokumentenarten: Artikel
Sprache: Englisch
Level: hoch