Anzeige
Erschienen in:
2016 | OriginalPaper | Buchkapitel
Markov Simulation by Numerical Derivation in Table Tennis
verfasst von : Sebastian Wenninger, Martin Lames
Erschienen in: Proceedings of the 10th International Symposium on Computer Science in Sports (ISCSS)
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
This study tries to assess the impact of different tactical behaviors on the winning probability in table tennis by mathematical simulation. Using discrete states of the game and transitions between them by means of the Markov chain model, the numerical derivation of winning probabilities is calculated under assumption of the Markov chain property. The method introduced in this study improves the traditional model by omitting the necessity to perform a second modeling step to define the difficulty of tactical behaviors. Application of our method on table-tennis shows meaningful results like the identification of long rallies as highly influencing stroke types and the effects of risky play on winning probability in different game situations.