Markov simulation by numerical derivation in table tennis

Sebastian Wenninger; Martin Lames

doi:10.1007/978-3-319-24560-7_21

Markov simulation by numerical derivation in table tennis

Sebastian Wenninger, Martin Lames

Chair of Training Science and Computer Science in Sports

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

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.

Original language	English
Title of host publication	Proceedings of the 10th International Symposium on Computer Science in Sports, ISCSS
Editors	Paul Chung, Andrea Soltoggio, Christian W. Dawson, Qinggang Meng, Matthew Pain
Publisher	Springer Verlag
Pages	161-169
Number of pages	9
ISBN (Print)	9783319245584
DOIs	https://doi.org/10.1007/978-3-319-24560-7_21
State	Published - 2016
Event	10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015 - Loughborough, United Kingdom Duration: 9 Sep 2015 → 11 Sep 2015

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	392
ISSN (Print)	2194-5357

Conference

Conference	10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015
Country/Territory	United Kingdom
City	Loughborough
Period	9/09/15 → 11/09/15

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10.1007/978-3-319-24560-7_21

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Wenninger, S., & Lames, M. (2016). Markov simulation by numerical derivation in table tennis. In P. Chung, A. Soltoggio, C. W. Dawson, Q. Meng, & M. Pain (Eds.), Proceedings of the 10th International Symposium on Computer Science in Sports, ISCSS (pp. 161-169). (Advances in Intelligent Systems and Computing; Vol. 392). Springer Verlag. https://doi.org/10.1007/978-3-319-24560-7_21

@inproceedings{ea001a9cfd9747b691761b51ea5b0090,

title = "Markov simulation by numerical derivation in table tennis",

abstract = "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.",

author = "Sebastian Wenninger and Martin Lames",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015 ; Conference date: 09-09-2015 Through 11-09-2015",

year = "2016",

doi = "10.1007/978-3-319-24560-7_21",

language = "English",

isbn = "9783319245584",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "161--169",

editor = "Paul Chung and Andrea Soltoggio and Dawson, {Christian W.} and Qinggang Meng and Matthew Pain",

booktitle = "Proceedings of the 10th International Symposium on Computer Science in Sports, ISCSS",

}

Wenninger, S & Lames, M 2016, Markov simulation by numerical derivation in table tennis. in P Chung, A Soltoggio, CW Dawson, Q Meng & M Pain (eds), Proceedings of the 10th International Symposium on Computer Science in Sports, ISCSS. Advances in Intelligent Systems and Computing, vol. 392, Springer Verlag, pp. 161-169, 10th International Symposium of Computer Science in Sport, IACSS/ISCSS 2015, Loughborough, United Kingdom, 9/09/15. https://doi.org/10.1007/978-3-319-24560-7_21

Markov simulation by numerical derivation in table tennis. / Wenninger, Sebastian; Lames, Martin.
Proceedings of the 10th International Symposium on Computer Science in Sports, ISCSS. ed. / Paul Chung; Andrea Soltoggio; Christian W. Dawson; Qinggang Meng; Matthew Pain. Springer Verlag, 2016. p. 161-169 (Advances in Intelligent Systems and Computing; Vol. 392).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lames, Martin

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2016.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

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Markov simulation by numerical derivation in table tennis

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