Advertisement

uPATO—Individual Measures

  • Frutuoso G. M. SilvaEmail author
  • Quoc Trong Nguyen
  • Acácio F. P. P. Correia
  • Filipe Manuel Clemente
  • Fernando Manuel Lourenço Martins
Chapter
Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)

Abstract

This chapter contains a set of individual metrics that can be used to analyze the importance of each player in a team sport. The metrics were divided into two main categories: Centrality (Sect. 3.1) and Prestige (Sect. 3.2). Each metric includes a description of a possible interpretation of the metric, and the pseudocode to implement it. Each pseudocode describes the cases (unweighted graphs, unweighted digraphs, weighted graphs, or weighted digraphs) for which it can be used. When the description simply contains graph (or graphs), without any other specifier, it means that the pseudocode is valid for any of the four types of graphs. The included interpretation considers that the connections between the players are the passes performed between them.

References

  1. 1.
    M. Bolaños, E.M. Bernat, B. He, S. Aviyente, A weighted small world network measure for assessing functional connectivity. J. Neurosci. Methods 212(1), 133–142 (2013)CrossRefGoogle Scholar
  2. 2.
    P. Bonacich, Power and centrality: a family of measures. Am. J. Sociol. 92(5), 1170–1182 (1987)CrossRefGoogle Scholar
  3. 3.
    U. Brandes, T. Erlebach, Network Analysis: Methodological Foundations, Lecture Notes in Computer Science (Springer, New York Inc., Secaucus, USA, 2005)CrossRefGoogle Scholar
  4. 4.
    Y. Cho, J. Yoon, S. Lee, Using social network analysis and gradient boosting to develop a soccer win-lose prediction model. Eng. Appl. Artif. Intell. 72, 228–240 (2018)CrossRefGoogle Scholar
  5. 5.
    F.M. Clemente, F.M.L. Martins, R.S. Mendes, Social Network Analysis Applied to Team Sports Analysis, 1st edn. (Springer International Publishing, 2016)Google Scholar
  6. 6.
    E. Estrada, J.A. Rodríguez-Velázquez, Subgraph centrality in complex networks. Phys. Rev. E 71, 056103 (2005)MathSciNetCrossRefGoogle Scholar
  7. 7.
    L. Freeman, A set of measures of centrality based on betweenness. 40, 35–41 (1977)Google Scholar
  8. 8.
    A. Gaggioli, G. Riva, L. Milani, E. Mazzoni, Networked Flow: Towards an Understanding of Creative Networks, SpringerBriefs in Education (Springer, Netherlands, 2012)Google Scholar
  9. 9.
    J. Gudmundsson, M. Horton, Spatio-temporal analysis of team sports. ACM Comput. Surv. 50(2), 22:1–22:34 (2017)Google Scholar
  10. 10.
    P. Hage, F. Harary, Eccentricity and centrality in networks. Soc. Netw. 17(1), 57–63 (1995)CrossRefGoogle Scholar
  11. 11.
    M.E.J. Newman, Mixing patterns in networks. Phys. Rev. E 67, 026126 (2003)MathSciNetCrossRefGoogle Scholar
  12. 12.
    G.A. Pavlopoulos, M. Secrier, C.N. Moschopoulos, T.G. Soldatos, S. Kossida, J. Aerts, R. Schneider, P.G. Bagos, Using graph theory to analyze biological networks. BioData Min. 4(1), 10 (2011)CrossRefGoogle Scholar
  13. 13.
    J.L. Peña, H. Touchette, A network theory analysis of football strategies (2012)Google Scholar
  14. 14.
    X. Qi, E. Fuller, Q. Wu, Y. Wu, C.-Q. Zhang, Laplacian centrality: a new centrality measure for weighted networks. Inf. Sci. 194, 240–253 (2012). Intelligent Knowledge-Based Models and Methodologies for Complex Information SystemsGoogle Scholar
  15. 15.
    M. Rubinov, O. Sporns, Complex network measures of brain connectivity: uses and interpretations. NeuroImage 52(3), 1059–1069 (2010). Computational Models of the BrainGoogle Scholar
  16. 16.
    G. Scardoni, C. Laudanna, Centralities based analysis of complex networks, in New Frontiers in Graph Theory, ed. by Y. Zhang (2012), pp. 323–348Google Scholar
  17. 17.
    A. Shimbel, Structural parameters of communication networks. Bull. Math. Biophys. 15(4), 501–507 (1953)MathSciNetCrossRefGoogle Scholar
  18. 18.
    S. Wasserman, K. Faust, in Social Network Analysis: Methods and Applications. Structural Analysis in the Social Sciences (Cambridge University Press, 1994)Google Scholar

Copyright information

© The Author(s), under exclusive license to Springer Nature Switzerland AG, part of Springer Nature 2019

Authors and Affiliations

  • Frutuoso G. M. Silva
    • 1
    • 2
    Email author
  • Quoc Trong Nguyen
    • 2
  • Acácio F. P. P. Correia
    • 2
  • Filipe Manuel Clemente
    • 2
    • 3
  • Fernando Manuel Lourenço Martins
    • 2
    • 4
  1. 1.Universidade da Beira InteriorCovilhãPortugal
  2. 2.Instituto de Telecomunicações, Delegação da CovilhãCovilhãPortugal
  3. 3.Instituto Politécnico de Viana do Castelo, Escola Superior de Desporto e LazerMelgaçoPortugal
  4. 4.Instituto Politécnico de Coimbra, Escola Superior de EducaçãoCoimbraPortugal

Personalised recommendations