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Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference

  • Conference proceedings
  • © 2022

Overview

Editors:
  1. Arnold Baca

    1. Institut für Sportwissenschaft Universität Wien, Wien, Austria

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  2. Juliana Exel

    1. University of Vienna, Wien, Austria

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  3. Martin Lames

    1. Faculty of Sports and Health Sciences, Technical University Munich, München, Germany

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  4. Nic James

    1. Middlesex University, Hendon, UK

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  5. Nimai Parmar

    1. The Burroughs, Middlesex University, Hendon, UK

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  • Focuses on contextual questions using the methods of computer science in the context of sport
  • Presents an overview of research in the multidisciplinary field of computer science and sports
  • Bridges the gap between theoretical computer science and practical performance analysis

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 1426)

Included in the following conference series:

Conference proceedings info: PACSS 2021.

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Table of contents (29 papers)

  1. Front Matter

    Pages i-xiii
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  2. Keynotes Contributions

    1. Front Matter

      Pages 1-1
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    2. Text Mining and Performance Analysis

      • Otto Kolbinger
      Pages 3-8

    3. Match Analysis 4.0 with Big Data: From Studies to Experiments

      • Daniel Memmert
      Pages 9-12

    4. Using Machine Learning to Assess and Compare Athletes in Team Sports

      • Albrecht Zimmermann
      Pages 13-17

  3. Application of Text Mining in Sports Performance

    1. Front Matter

      Pages 19-19
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    2. Kick It to Me, or Maybe Not – How Player Roles Affect AFL Possessions

      • Zachery Born, Jason Weber, Ajmal Mian, Jacqueline Alderson
      Pages 21-28

    3. Predicting and Understanding Australian Rules Football Using Markov Processes

      • Jacob Holden, Paul Gastin, Tom Kempton, Brent Manson, David L. Carey
      Pages 29-37

  4. Interdisciplinarity in Sports Performance

    1. Front Matter

      Pages 39-39
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    2. Inertial Sensors Containing Device-Based Match Characteristics that Act as Prognosticators of Elite, Male Badminton Players’ Performance Levels

      • Yahaya Abdullahi, Ben Coetzee
      Pages 41-48

    3. Excluding Random Scoring Effects from Soccer Results Using Deserved Points

      • Jonas Birk, Hendrik Meth, Georgio Syrianos
      Pages 49-52

    4. Passing Networks: An Examination of the Prevalence of Positions in Positional Attack in Handball

      • Mario Borges, John Seeley
      Pages 53-60

    5. Generating Weekly Training Plans in the Style of a Professional Swimming Coach Using Genetic Algorithms and Random Trees

      • Rikard Eriksson, Johan Nicander, Moa Johansson, C. Mikael Mattsson
      Pages 61-68

    6. Flexibility, Stability, and Adaptability of Team Playing Style as Key Determinants of Within-Season Performance in Football

      • Qixiang He, Ying Hwa Kee, John Komar
      Pages 69-73

    7. Anthropometry, Physical Fitness, Sport-Specific Performance and the Prediction of Performance Level in Young Canoe Sprint Athletes

      • Christian Saal, Norman Helm, Olaf Prieske
      Pages 74-77

    8. Deriving Player Types from Soccer Event Data as a Means to Improve Tactical Flexibility

      • Patrick Schmider, Hendrik Meth, Georgios Syrianos
      Pages 78-81

    9. Exercise Evaluation Using Time-of-Flight Image Data

      • Christoph Uran, David Kreitmayr, Helmut Wöllik
      Pages 82-85

    10. Relation Between Match Outcomes and Discipline in Japan Rugby Top League

      • Takumi Yamamoto, Koh Sasaki, Jun Murakami, Ichiro Watanabe, Hironobu Shimozono, Toshihito Kajiyama et al.
      Pages 86-89

  5. Applications of Machine Learning in Sports Performance

    1. Front Matter

      Pages 91-91
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    2. Improving Springboard Diving Video Classification Accuracy Through Cumulated Segment Values

      • Adnan Bicaj, Hendrik Meth
      Pages 93-96
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Other volumes

  1. Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference

Keywords

About this book

This covers the PACSS 2021 which approached interdisciplinary collaboration between theoretical computer science and practical performance analysis though an online workshop and conference. Readers find in this book the peer-reviewed and discussed evidences on how computer scientists and performance analysts can and have worked together to solve both applied and research-based problems in elite sport, using the methods of computer science. In this edition, we organize the content according to four major topics: machine learning, text mining, best practice and interdisciplinary collaboration. This is a refined material written by leading experts with up-to-date overview of research in the multidisciplinary field of computer science and elite sport performance analysis.

Editors and Affiliations

  • Institut für Sportwissenschaft Universität Wien, Wien, Austria

    Arnold Baca

  • University of Vienna, Wien, Austria

    Juliana Exel

  • Faculty of Sports and Health Sciences, Technical University Munich, München, Germany

    Martin Lames

  • Middlesex University, Hendon, UK

    Nic James

  • The Burroughs, Middlesex University, Hendon, UK

    Nimai Parmar

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