Papahristodoulou, Christos (2012): Optimal football strategies: AC Milan versus FC Barcelona.
Download (290Kb) | Preview
In a recent UEFA Champions League game between AC Milan and FC Barcelona, played in Italy (final score 2-3), the collected match statistics, classified into four offensive and two defensive strategies, were in favour of FC Barcelona (by 13 versus 8 points). The aim of this paper is to examine to what extent the optimal game strategies derived from some deterministic, possibilistic, stochastic and fuzzy LP models would improve the payoff of AC Milan at the cost of FC Barcelona.
|Item Type:||MPRA Paper|
|Original Title:||Optimal football strategies: AC Milan versus FC Barcelona|
|Keywords:||football game; offensive & defensive strategies; Deterministic LP; fuzzy LP; stochastic LP; Nash equilibria;|
|Subjects:||L - Industrial Organization > L8 - Industry Studies: Services > L83 - Sports; Gambling; Recreation; Tourism
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C61 - Optimization Techniques; Programming Models; Dynamic Analysis
M - Business Administration and Business Economics; Marketing; Accounting > M5 - Personnel Economics > M54 - Labor Management
C - Mathematical and Quantitative Methods > C7 - Game Theory and Bargaining Theory > C72 - Noncooperative Games
|Depositing User:||Christos Papahristodoulou|
|Date Deposited:||14. Jan 2012 21:22|
|Last Modified:||12. Feb 2013 15:40|
Carlton, D.W. & J.M. Perloff: Modern Industrial Organization, 4th ed., Pearson Addison Wesley, (2005).
Dickhaut J. & T. Kaplan: A Program for Finding Nash Equilibria, in H.R. Varian, (ed.) Economic and Financial Modeling with Mathematica, Telos, Springer-Verlag (1993).
Inuiguchi, M. and J. Ramík: Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem, Fuzzy Sets and Systems, 111 (2000), 3-28.
Luhandjula, M.K.: Optimization under hybrid uncertainty, Fuzzy Sets and Systems 146 (2004), 187-203.
Luhandjula, M.K.: Fuzziness and randomness in an optimization framework, Fuzzy Sets and Systems 77 (1996), 291-297.
Papahristodoulou, C.: The optimal layout of football players: A case study for AC Milan, Working Paper, Munich Personal RePec Archive, (2010), downloadable at: http://mpra.ub.uni-muenchen.de/20102/1/MPRA_paper_20102.pdf
Papahristodoulou, C.: An Analysis of UEFA Champions League Match Statistics, International Journal of Applied Sports Sciences 20 (2008), 67-93.
Pollard, R. and C. Reep: Measuring the effectiveness of playing strategies at soccer, The Statistician, 46, (1997), 541-50.
Taha, H.A.: Operations research: An Introduction, 8th ed., Pearson Prentice Hall, Upper Saddle River, NJ, (2007).
Van Hop, N.: Solving fuzzy (stochastic) linear programming problems using superiority and inferiority measures, Information Sciences, 177 (2007), 1977-91.
Wolfram Research, Mathematica: Fuzzy Logic (2003).