Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A comparative multi criteria decision analysis of football teams: evidence on FIFA world cup

A comparative multi criteria decision analysis of football teams: evidence on FIFA world cup World Cup tournament is one of the most popular international organizations in football. The purpose of this paper is to investigate the overall performance of World Cup 2018 teams via multi-criteria decision-making (MCDM) approaches.Design/methodology/approachThe presented approach adopts entropy integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches to weight the criteria and evaluate the performance of World Cup 2018 teams. Initially, the authors compute weight criteria via Shannon Entropy method. Then, the authors compute and compare the results of TOPSIS and WASPAS methods so as to evaluate the performance of World Cup 2018 teams.FindingsAccording to TOPSIS and WASPAS results, Belgium has demonstrated better performance in comparison to other teams. As per to the empirical results, both methods have shown a significant harmony in terms of performance figures. There is also strong positive correlation between TOPSIS and WASPAS method results. This result confirms the stability of the analysis.Originality/valueThis paper contributes to sport performance management literature by using MCDM methods in FIFA World Cup 2018 teams. To the best of the authors’ knowledge, this is the first paper to measure performance of an international football organization via MCDM methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Team Performance Management Emerald Publishing

A comparative multi criteria decision analysis of football teams: evidence on FIFA world cup

Gökgöz, Fazıl; Yalçın, Engin
Team Performance Management , Volume 27 (3/4): 15 – Jun 8, 2021
Download PDF
15 pages

Loading next page...
 
/lp/emerald-publishing/a-comparative-multi-criteria-decision-analysis-of-football-teams-Fs8hp59r0b
Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1352-7592
DOI
10.1108/tpm-05-2020-0039
Publisher site
See Article on Publisher Site

Abstract

World Cup tournament is one of the most popular international organizations in football. The purpose of this paper is to investigate the overall performance of World Cup 2018 teams via multi-criteria decision-making (MCDM) approaches.Design/methodology/approachThe presented approach adopts entropy integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches to weight the criteria and evaluate the performance of World Cup 2018 teams. Initially, the authors compute weight criteria via Shannon Entropy method. Then, the authors compute and compare the results of TOPSIS and WASPAS methods so as to evaluate the performance of World Cup 2018 teams.FindingsAccording to TOPSIS and WASPAS results, Belgium has demonstrated better performance in comparison to other teams. As per to the empirical results, both methods have shown a significant harmony in terms of performance figures. There is also strong positive correlation between TOPSIS and WASPAS method results. This result confirms the stability of the analysis.Originality/valueThis paper contributes to sport performance management literature by using MCDM methods in FIFA World Cup 2018 teams. To the best of the authors’ knowledge, this is the first paper to measure performance of an international football organization via MCDM methods.

Journal

Team Performance Management – Emerald Publishing

Published: Jun 8, 2021

Keywords: Sport performance; World cup; Multi-criteria decision-making; TOPSIS; WASPAS

References

  • Selecting sustainable supplier countries for Iran's steel industry at three levels by using AHP and TOPSIS methods
    Azimifard, A.; Moosavirad, S.H.; Ariafar, S.
  • Human risk assessment of panchet dam in India using TOPSIS and WASPAS Multi-Criteria Decision-Making (MCDM) methods
    Bid, S.; Siddique, G.
  • Increasing offensive or defensive efficiency? An analysis of Italian and Spanish football
    Boscá, J.E.; Liern, V.; Martínez, A.; Sala, R.
  • Measuring the efficiency of decision making units
    Charnes, A.; Cooper, W.W.; Rhodes, E.
  • A mathematical model of self-organisation in football
    Chassy, P.; Malone, J.J.; Clark, D.P.
  • Multiciteria evaluation of football clubs: the Greek superleague
    Chelmis, E.; Niklis, D.; Baourakis, G.; Zopounidis, C.
  • Effects of normalization on the entropy-based TOPSIS method
    Chen, P.
  • Towards smart-data: improving predictive accuracy in long-term football team performance
    Constantinou, A.; Fenton, N.
  • Regression models for forecasting goals and match results in association football
    Goddard, J.
  • Measuring the financial efficiencies and performances of Turkish funds
    Gökgöz, F.
  • Investigating the energy efficiencies of European countries with super efficiency model and super SBM approaches
    Gökgöz, F.; Erkul, E.
  • Investigating the total factor productivity changes in the top ICT companies worldwide
    Gökgöz, F.; Güvercin, M.T.
  • Measuring efficiency and productivity in professional football teams: evidence from the English premier league
    Guzmán, I.; Morrow, S.
  • A case study assessing possession regain patterns in English premier league football
    Jamil, M.
  • Possession as a performance indicator in soccer
    Jones, P.D.; James, N.; Mellalieu, S.D.
  • Constructing composite indicators with Shannon entropy: the case of human development index
    Karagiannis, R.; Karagiannis, G.
  • Outcome bias in subjective ratings of performance: evidence from the (football) field
    Kausel, E.E.; Ventura, S.; Rodríguez, A.
  • Differences in performance indicators between winning and losing teams in the UEFA champions league
    Lago-Peñas, C.; Lago-Ballesteros, J.; Rey, E.
  • Determination of most suitable low-emission energy technologies development in Poland using integrated fuzzy AHP-TOPSIS method
    Ligus, M.; Peternek, P.
  • Analysis of the financial parameters of Serbian banks through the application of the fuzzy AHP and TOPSIS methods
    Mandic, K.; Delibasic, B.; Knezevic, S.; Benkovic, S.
  • A systematic review and meta-analysis of SWARA and WASPAS methods: theory and applications with recent fuzzy developments
    Mardani, A.; Nilashi, M.; Zakuan, N.; Loganathan, N.; Soheilirad, S.; Saman, M.Z.M.; Ibrahim, O.
  • Supplier selection with Shannon entropy and fuzzy TOPSIS in the context of supply chain risk management
    Mavi, R.K.; Goh, M.; Mavi, N.K.
  • Distance matters in away games: evidence from the German football league
    Oberhofer, H.; Philippovich, T.; Winner, H.
  • Identification of the football teams assessment model using the COMET method
    Palczewski, K.; Sałabun, W.
  • Science and football
    Reilly, T.; Lees, A.; Davids, K.; Murphy, W. J.
  • The DEA game cross efficiency model applied to the Brazilian football championship
    Roberado, M.C.; Aizemberg, L.; Meza, L.A.
  • A mathematical theory of communication
    Shannon, C.E.
  • Assessment of economic and environmental energy performance of EU countries using CV-TOPSIS technique
    Vavrek, R.; Chovancová, J.
  • Assessing the scoring efficiency of a football match
    Villa, G.; Lozano, S.
  • Integrated flood vulnerability assessment approach based on TOPSIS and Shannon entropy methods
    Yang, W.; Xu, K.; Lian, J.; Ma, C.; Bin, L.
  • Performance evaluation in the UEFA champions league
    Zambom-Ferraresi, F.; García-Cebrián, L.I.; Lera-López, F.; Iráizoz, B.
  • Optimization of weighted aggregated sum product assessment
    Zavadskas, E.K.; Turskis, Z.; Antucheviciene, J.; Zakarevicius, A.