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Ultimate Performance Analysis Tool (uPATO)

Implementation of Network Measures Based on Adjacency Matrices for Team Sports

  • Book
  • © 2019

Overview

  • Explains the codification of the network analysis metrics for team sports
  • Presents a software that compiles the metrics referenced in the literature for the network analysis based on adjacency matrices
  • Shows a generic tool that can be used in other contexts besides network analysis in team sports

Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)

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Table of contents (5 chapters)

Keywords

About this book

This book introduces the ultimate performance analysis tool (uPATO) as a new software to compute social network metrics in the scope of team sports analysis. The reader will identify the algorithms to test the general properties of the team, the co-dependencies and the centrality levels of players, i.e. to evaluate the individual, sub-group, and team performance analysis. As uPATO tool implements the metrics for all options, namely for unweighted graphs, weighted graphs, unweighted digraphs and weighted digraphs, it is also useful for network analysis into other areas beyond team sports. The book assists the reader to compute the metrics and to use it in different scenarios.

Authors and Affiliations

  • Universidade da Beira Interior, Covilhã, Portugal

    Frutuoso G. M. Silva

  • Instituto de Telecomunicações, Delegação da Covilhã, Covilhã, Portugal

    Quoc Trong Nguyen, Acácio F.P.P. Correia

  • Instituto Politécnico de Viana do Castelo, Escola Superior de Desporto e Lazer, Melgaço, Portugal

    Filipe Manuel Clemente

  • Instituto Politécnico de Coimbra, Escola Superior de Educação, Coimbra, Portugal

    Fernando Manuel Lourenço Martins

About the authors

1) Frutuoso G. M. Silva is Assistant Professor at the Department of Computer Science at UBI and leader of the Regain group of Instituto de Telecomunicações (IT), Portugal. His research interests include geometric modeling, augmented reality, and computer games. 

Quoc Trong Nguyen is a PhD student and researcher at the Instituto de Telecomunicacões, Universidade da Beira Interior, Covilhã, Portugal.  His research interests include geometric computing, point-based graphics, and visualization.

Acácio F. P. P. Correia has recently finished a Master’s Degree in Computer Science and Engineering, at the Universidade da Beira Interior. His professional interests include procedural generation, artificial intelligence,  natural  language  processing,  cryptography  and  video  game development.

Filipe  Manuel  Clemente is  Assistant  Professor  at the  Instituto  Politécnico  de Viana do Castelo and researcher in Instituto de Telecomunicações, Delegação da Covilhã (Portugal). He has conducted studies in performance analysis, match analysis, computational tactical metrics, network analysis applied to team sports analysis, small-sided and conditioned games, physical activity and health and sports medicine. 

Fernando  Manuel  Lourenço  Martins is the Scientific Coordinator of Applied Mathematics group in Instituto de Telecomunicações, Delegação  da  Covilhã,  Portugal  and  Professor  and  Course  Director  of  Basic Education in Instituto Politécnico de Coimbra. His research interests include advances in network analysis applied to team sports and assessment of inter-actions between children, statistical analysis in team sports and mathematical and statistical knowledge for teaching.

Bibliographic Information

  • Book Title: Ultimate Performance Analysis Tool (uPATO)

  • Book Subtitle: Implementation of Network Measures Based on Adjacency Matrices for Team Sports

  • Authors: Frutuoso G. M. Silva, Quoc Trong Nguyen, Acácio F.P.P. Correia, Filipe Manuel Clemente, Fernando Manuel Lourenço Martins

  • Series Title: SpringerBriefs in Applied Sciences and Technology

  • DOI: https://doi.org/10.1007/978-3-319-99753-7

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-319-99752-0Published: 11 September 2018

  • eBook ISBN: 978-3-319-99753-7Published: 30 August 2018

  • Series ISSN: 2191-530X

  • Series E-ISSN: 2191-5318

  • Edition Number: 1

  • Number of Pages: XI, 76

  • Number of Illustrations: 3 b/w illustrations, 28 illustrations in colour

  • Topics: Computational Intelligence, Sport Science

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