Modeling Team-Compatibility Factors Using a Semi-Markov Decision Process: a Framework for Performance Analysis in Soccer
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Modeling Team-Compatibility Factors Using a Semi-Markov Decision Process: A Framework for Performance Analysis in Soccer By Ali Jarvandi B.S. in Systems Engineering, May 2009, George Mason University M.S. in Operations Research, May 2010, George Mason University A Dissertation Submitted to The Faculty of The School of Engineering and Applied Science of The George Washington University in partial satisfaction of the requirements for the degree of Doctor of Philosophy January 31, 2014 Dissertation directed by Shahram Sarkani Professor of Engineering Management & Systems Engineering Thomas A. Mazzuchi Professor of Engineering Management & Systems Engineering The School of Engineering and Applied Science of The George Washington University certifies that Ali Jarvandi has passed the Final Examination for the degree of Doctor of Philosophy or Doctor of Science as of 5 November 2013. This is the final and approved form of the dissertation. Modeling Team-Compatibility Factors Using a Semi-Markov Decision Process: A Framework for Performance Analysis in Soccer Ali Jarvandi Dissertation Research Committee: Shahram Sarkani, Professor of Engineering Management & Systems Engineering, Dissertation Co-Director Thomas Mazzuchi, Professor of Engineering Management & Systems Engineering, Dissertation Co-Director Edward Lile Murphree, Professor Emeritus of Engineering Management & Systems Engineering, Committee Member Bereket Tanju, Adjunct Professor of Engineering Management & Systems Engineering, Committee Member Pavel Fomin, Adjunct Professor of Engineering Management & Systems Engineering, Committee Member ii Acknowledgements Dr. David Rico, for providing guidance in generating the original idea. Dr. Jeffrey Ohlmann, for conducting several detailed reviews and providing invaluable technical feedback. Dr. Shahram Sarkani and Dr. Thomas Mazzuchi for supporting this research idea and providing guidance throughout the dissertation process. iii Abstract Modeling Team-Compatibility Factors Using a Semi-Markov Decision Process: A Framework for Performance Analysis in Soccer Soccer is the most popular sport worldwide. Over time, the importance of soccer has grown beyond the sports domain, making it a large industry, a source of national pride, and the center of public attention in most countries. Due to this increased significance, it is highly important for soccer teams at both the club and national levels to invest in sciences providing a competitive edge over opponents. Quantitative analysis of soccer is one of the domains that have enjoyed a sharp growth in the recent years. Using the advanced data collection and analysis tools, it has become possible to implement more sophisticated performance analysis methodologies. In this study, a model has been developed to anticipate the collective team performance based on the attributes of the individual players. The model is then used to predict how the hiring of new players affects team performance. The data used for this study has been collected from the English Premier League between the 2008/09 and 2011/2012 seasons. Using the model, team performance can be predicted with an average error of 7.857 units of goal differential. Also, the effect of a new player on team performance can be predicted with an average error of 18.912 units of goal differential. Using a classification strategy, the model was able to correctly predict the direction of change in team performance caused by a new player 85.6% of the time. This provides a minimum of 20% increase in accuracy compared to the current transfer success rate at the highest level of club soccer. Therefore, using this model is expected to save clubs large amounts of money while enhancing performance. iv Contents Acknowledgements ......................................................................................................................... iii Abstract ........................................................................................................................................... iv List of Figures ................................................................................................................................ vii List of Tables ................................................................................................................................... ix 1. Soccer as an Ever-Growing Industry ....................................................................................... 1 1.1 Initial Development and Growth of Soccer ..................................................................... 1 1.2 From a Sport to an Industry ............................................................................................. 3 1.3 Soccer in the Recent Decades .......................................................................................... 8 2. Great Expectations, Great Risks ............................................................................................ 12 2.1 Emotional Involvements ................................................................................................ 12 2.2 Social and Political implications ................................................................................... 14 2.3 Winning: Great Value and High Uncertainty ................................................................ 16 3. Quantitative Analysis: A New Way Forward ........................................................................ 19 3.1 Why and How? .............................................................................................................. 19 3.2 Performance Analysis in Soccer .................................................................................... 21 3.3 Existing Models ............................................................................................................. 26 3.4 The Problem of Team Compatibility ............................................................................. 27 4. Markov Models, Simulation, and Stochastic Modeling ........................................................ 29 4.1 Stochastic Models and Markov Decision Process ......................................................... 29 4.2 Simulation ..................................................................................................................... 32 5. Team Compatibility Model ................................................................................................... 33 5.1 Team Performance Measures ........................................................................................ 33 5.2 Data ..................................................................................................................................... 36 5.3 Game-flow ........................................................................................................................... 39 5.4 Scoring and Conceding Goals ............................................................................................. 44 6. Output Analysis and Results ..................................................................................................... 50 6.1 Baseline Model Accuracy.................................................................................................... 50 6.2 Transfer Analysis Strategy .................................................................................................. 54 6.3 Performance Variability ...................................................................................................... 56 v 6.4 Transfer Analysis Results .................................................................................................... 57 6.5 Multiple Changes in a Transfer Season ............................................................................... 61 6.6 Suitability Analysis ............................................................................................................. 63 6.7 Player Classification Method .............................................................................................. 65 6.8 Sensitivity Analysis ............................................................................................................. 68 7. Conclusion ................................................................................................................................. 71 7.1 Overview of Model, Results, and Benefits .......................................................................... 71 7.2 Limitations and Future Directions ....................................................................................... 73 8. Bibliography .............................................................................................................................. 75 9. Appendices ................................................................................................................................ 80 vi List of Figures Figure 1 - Business Value System for Football Clubs ..................................................................... 6 Figure 2 – Wage Bill (£) for a Bottom-table Second Division English Club .................................. 7 Figure 3 – FIFA’s annual revenue between years 2007 and 2012 .................................................. 9 Figure 4 – Market Share for Different Sports in the Sports Events Market .................................. 10 Figure 5 – Market Size and Compound Annual Growth Rate for Different Sports ...................... 11 Figure 6 – The process of quantitative analysis in soccer ............................................................. 21 Figure