Advertisement

Affinity as Basis for Interchangeability Between Athletes

  • Jaime Gil-Lafuente
  • Anna Maria Gil-Lafuente
Chapter
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 675)

Abstract

As consequence of the recessive and depressive process of economic activity, sports entities have been forced to review its management in order to reduce financial costs. This requires a very strict administration from an aspect that generates one of the greater financial needs throughout the exercise: the acquisition of the rights over the athletes. But in addition, the selection of an athlete becomes more complex when it refers to a team sport. In team sports, in addition to having good professionals, groups of interchangeable athletes must be hired, in order to make substitutions due to fatigue, injury or various incidents. From a scientific perspective, algorithms are applied to solve some of the problems when placing financial resources in hiring a team athlete [Pichat (Inform. Process. 69, 1969), Huang et al. (Inform. Process. Lett. 99(4):149–153, 2006)]. In this paper we address the formation of groups of athletes with a high degree of interchangeability when there is inaccuracy in the information available. We will use the concepts of similarity, similitude and affinity. The objective is the adaptation of groups of players reducing financial cost to the team but maintaining the highest reachable performance.

Keywords

Affinities Fuzzy Subset Fuzzy Logic Grouping Sport Management Uncertainty 

References

  1. 1.
    J. Gil-Aluja, Fuzzy Set. Syst. 84(2), 187–197 (1996)CrossRefGoogle Scholar
  2. 2.
    A. Popa, J.J. McDowell, Behav. Process. 84(1), 428–434 (2010)CrossRefGoogle Scholar
  3. 3.
    W. Huang, Y. Shi, S. Zhang, Y. Zhu, Inform. Process. Lett. 99(4), 149–153 (2006)CrossRefGoogle Scholar
  4. 4.
    C.W. Duin, A. Volgenant, Eur. J. Oper. Res. 170(3), 887–899 (2006)CrossRefGoogle Scholar
  5. 5.
    E. Pichat, [1969] Algorithms for finding the maximal elements of a finite universal algebra, in Information Processing 68 (Proc. IFIP Congress, Edinburgh, 1968), Vol I: Mathematics, Software, pp. 214–218, North-Holland, AmsterdamGoogle Scholar
  6. 6.
    J. Gil Lafuente, Algoritmos para la excelencia: claves para el éxito en la gestión deportiva, (Milladoiro, España, 2002), pp. 7–59, 221–270Google Scholar
  7. 7.
    L.E. Dickson, Linear groups - With an exposition of the Galois field theory (Courier Dover Publications, 2003), pp. 75–88Google Scholar
  8. 8.
    J. Gil-Aluja, A.M. Gil-Lafuente, Optimal strategies in sports economics and management. (Springer, Berlin, 2010), pp. 1–14Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Comercialització i Investigació de MercatsUniversitat de BarcelonaBarcelonaSpain
  2. 2.Faculty of Economics and BusinessUniversity of BarcelonaBarcelonaSpain

Personalised recommendations