Basketball Background 7 3.1
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UNIVERSITY OF LAS PALMAS DE GRAN CANARIA DEPARTAMENT OF PHYSICAL EDUCACTION Doctoral Program: Motor Praxiology, Physical Education and Sport Training DOCTORAL THESIS BASKETBALL FROM THE PERSPECTIVE OF NON-LINEAR COMPLEX SYSTEMS YVES DE SAÁ GUERRA LAS PALMAS DE GRAN CANARIA, 2013 BASKETBALL FROM THE PERSPECTIVE OF NON-LINEAR COMPLEX SYSTEMS DOCTORAL THESIS By YVES DE SAÁ GUERRA, B.S. SCIENCES OF PHYSICAL ACTIVITY AND SPORT \ UNIVERSITY OF LAS PALMAS DE GRAN CANARIA, GRAN CANARIA, SPAIN 2013 Anexo II UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA Departamento de Educación Física. Facultad de Educación Física Programa de doctorado: Praxiología motriz, educación física y entrenamiento deportivo. Título de la Tesis BASKETBALL FROM THE PERSPECTIVE OF NON-LINEAR COMPLEX SYSTEMS Tesis Doctoral presentada por D. Yves de Saá Guerra Dirigida por el Dr. D. Manuel Navarro Valdivielso Codirigida por el Dr. D. Juan Manuel García Manso Codirigida por el Dr. D. Juan Manuel Martín González El Director, El Codirector , El Codirector, El Doctorando, (firma) (firma) (firma) (firma) Las Palmas de Gran Canaria, a _____ de_________________ de 2013 The more I know, the less I can affirm, categorically. Cuanto más sé, menos puedo afirmar las cosas categóricamente. Yves ACKNOWLEDGEMENTS This dissertation would not have been possible without the help of so many people in so many ways. It carried out thanks to the commitment and dedication of a research group led by Dr. Manuel Navarro Valdivielso, Dr. Juan Manuel García Manso and Dr. Juan Manuel Martín. It is an honor be part of this group and I would like to express my sincere gratitude to my thesis director Dr. Manuel Navarro Valdivielso for his unconditional support, his advices and his academic orientation, as well as for his help in the develop of this thesis. Also I would like to express my deepest admiration to my co-directors Dr. Juan Manuel García Manso, because he taught me everything I know about training and advised me about sport in an exquisite way. He has conveyed me all his strength and passion for the sport. I will never be able to remove his seed; and to Dr. Juan Manuel Martín, because he developed the necessary programs in Matlab that allow us to deepen in sports reality and advise with mathematics. I have been fascinated by all of our conversations about the universe and the secrets of life. It is a real pleasure to listen to and learn from him. Without his help this thesis would not been possible. I feel privileged for sharing part of my life with these three great people. I also would like to acknowledge the collaboration and support of Professor Adrian Bejan, from Duke University, USA. by his passionate discussions and by his outstanding relevance in the scientific community. I was a real pleasure learn from him during my stay at Duke University. I cannot conclude this chapter without to extend my sincere thanks to my fellows of the Laboratory for Analysis and Planning of Sports Training, of Department of Physical Education of this university, especially to Dr. Samuel Sarmiento Montesdeoca for his support and friendship. I must also acknowledge the support of the University of Las Palmas de Gran Canaria, for supporting my research by awarding a grant for the development of this thesis. Finally, and by no means least important, I would like to give thanks to my entire family for their unconditional support every time I needed it. They are my role models. They always have been. And always will be. Yves Index 1. Abstract 1 2. Introduction 3 3. Basketball background 7 3.1. Basketball History 9 3.2. Basketball General Description 12 3.3. Organizational structure of basketball 19 3.3.1. General structures 19 3.3.2. International structures 21 3.3.3. National Structures 23 3.3.3.1. Organizational structure of basketball in USA 23 3.3.3.2. Organizational structure of basketball in Spain 32 3.3.4. Structural comparison between beginning and the present 39 3.4. Competition Analysis 45 3.5. Game Analysis 47 4. Non-linear complex systems 51 4.1. Non-Linear 53 4.2. Self-organization 54 4.3. Critical State 55 4.4. Self-Organized Systems and Sport 56 5. General Research Design: 61 5.1. Objetives 63 5.2. Hypothesis 63 5.3. Research design 63 5.4. Significance 67 6. Study 1. Basketball league. 71 6.1. Introduction 73 6.2. Methodology 76 6.3. Results and discussion 82 6.3.1. Entropy analysis 82 6.3.2. Statistical and cluster analysis 91 6.4. Conclusions 106 6.5. Practical Proposals 107 6.6. Limitations of the techniques used 108 7. Study 2. Basketball game. 109 7.1. Introduction 111 7.2. Methodology 112 7.2.1. Poisson Model 113 7.2.2. Application of Poisson Model to Sport 114 7.2.3. Scaling behavior 115 7.3. Results and discussion 117 7.4. Conclusions 156 7.5. Practical Proposals 157 7.6. Limitations of the techniques used 157 8. Study 3. Basketball team. 159 8.1. Introduction 161 8.2. Methodology 161 8.2.1. Network theory 161 8.2.2. Complex Networks 165 8.2.3. Sport Application 167 8.2.4. Application to Basketball 168 8.3. Results and discussion 169 8.4. Conclusions 180 8.5. Practical Proposals 181 8.6. Limitations of the techniques used 181 9. General Conclusions 183 10. Future research lines 187 11. Spanish Abstract. Resumen en español 191 12. Bibliography 211 13. Annexes 229 13.1. Annex Index 231 Abstract We consider basketball as a complex systemic unit. There is a reciprocal relationship between the basketball team and its environment. Therefore it is important to figure out the behavior of the participating agents, as well as their relationships. First at all we carried out an approach to the degree of competitiveness of a sport league as complex phenomenon. In the first study, we used the results of previous seasons as a way to investigate the victory probabilities of each team. We developed a model based on Shannon entropy using two extreme competitive structures, a hierarchical structure and a random structure and applied this model to investigate competitiveness of the NBA (USA) and the ACB (Spain). Both leagues entropy levels are high (NBA mean 0.983; ACB mean 0.980) indicating high competitiveness although entropy of the ACB (from 0.986 to 0.972) demonstrated more seasonal variability than the NBA (from 0.985 to 0.990). This methodology has been useful for investigating sports competitiveness. The second study deal with score in basketball. Scoring in a basketball game is a highly dynamic, non-linear process. Several mechanisms concur to make the scoring process in the NBA games exciting and hardly predictable. We analyze all the games in five NBA regular seasons (2005-06, 2006-07, 2007-08, 2008-09, 2009-10), for a total of 6150 games. Scoring does not behave uniformly; therefore, we as well analyze the distributions of the differences in points in the basketball games. To further analyze the behavior of the tail of the distribution, we also carry out a scaling analysis in order to verify that distribution. This analysis reveals different areas of behavior related to the score, with specific instances of time that could be considered tipping points of the game. The presence of these critical points suggests that there are phase transitions where the scoring dynamic of the games varies significantly. As third study we propose the use of the network theory in order to clarify the features of the basketball teams as a player network. Sport as network is a new field of application in sport research. In fact, there are only few papers dealing with sport as network. We carried out an in investigation about player network in order to clarify the behavior of players of the same team when they fight against the other team. We study the game of NBA Finals Chicago Bulls vs. Miami Heat. Regarding player interactions, we measured for each team the number or passes, screens and space creations per play. This analysis point out that teams modify their interactions and are able to behave as small-world network or as scale-free network regarding the game situation (time and score). Introduction Basketball from the perspective of non-linear complex systems Yves de Saá Guerra 2013 Introduction In our effort to try to understand the sport reality, we are forced to question everything that we consider true or static. This leads us inexorably, to try to isolate a phenomenon in order to study better. But far from our purpose, when we move towards this point, we realize that we fall into the contradiction of hoping of be able to understand a phenomenon by isolating it from its environment. Following the asseveration: ” I am I and my circumstance” (Ortega y Gasset, 1933), it is not possible to understand the sport phenomenon by isolating the constituent elements of their relationships with their own universe. There is a duality element–environment. From this relationship might emerge new behaviors, which is known from the perspective of complexity, as an emergency phenomenon or an emergent behavior. I.e. in order to reason this phenomenon, it would be good to move away from the deterministic and reductionist classical model, and move on to study the systems from a more global conception (holistic), allowing us to identify and describe the processes of new forms of organization, which is also useful in sport. Organizing the sport training from a systematic conception and conceive the athlete, or the team in our case, as a system that functions as a whole and that is affected by the surrounding environment (Gambetta, 1989; Martín Acero & Lago Peñas, 2005; García Manso & Martín González, 2008).