Social Network Analysis Applied To Team Sports Analysis

Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

Social network analysis is a methodological tool used to investigate social networks, or collections of individuals, groups, or organizations and their shared relationships. Sport researchers increasingly have applied social network analysis to a variety of sport contexts, from team interactions among players and coaches to tailgating among fans to mega sporting events and their organizers and other stakeholders. An opportunity now exists to expand this research and generate new insights regarding myriad sport contexts and applications. This book provides an overview of the growing body of social network analysis research in sport. Additionally, it offers practical guidance for applying social network analysis within different sport settings and for using this methodology with new research applications.

This book introduces the ultimate performance analysis tool (uPATO) as a new software to compute social network metrics in the scope of team sports analysis. The reader will identify the algorithms to test the general properties of the team, the co-dependencies and the centrality levels of players, i.e. to evaluate the individual, sub-group, and team performance analysis. As uPATO tool implements the metrics for all options, namely for unweighted graphs, weighted graphs, unweighted digraphs and weighted digraphs, it is also useful for network analysis into other areas beyond team sports. The book assists the reader to compute the metrics and to use it in different scenarios.

To date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical analysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks.

Complex systems in nature are those with many interacting parts, all capable of influencing global system outcomes. There is a growing body of research that has modeled sport performance from a complexity sciences perspective, studying the behavior of individual athletes and sports teams as emergent phenomena which self-organise under interacting constraints. This book is the first to bring together experts studying complex systems in the context of sport from across the world to collate core theoretical ideas, current methodologies and existing data into one comprehensive resource. It offers new methods of analysis for investigating representative complex sport movements and actions at an individual and team level, exploring the application of methodologies from the complexity sciences in the context of sports performance and the organization of sport practice. Complex Systems in Sport is important reading for any advanced student or researcher working in sport and exercise science, sports coaching, kinesiology or human movement.

The objective of the book is to make accessible the ways in whichsocial network analysis (SNA) may be used to observe, monitor andanalyse systems and relationships in major construction projectcoalitions. Although this has been an established analyticaltechnique in the US for some time, it is only now being developedin the UK. Having spent nearly two decades investigating major projectrelationships using SNA, the author has brought togethermathematical and sociological methods, and major projectrelationships in a manner that will inspire both academic interestand a desire to apply these concepts and techniques to liveconstruction projects. Case studies include projects from two ofthe UKs largest property developers, the UK Ministry of Defence anda County Council. SNA is innovative - but potentially inaccessible to projectmanagement analysts and practitioners. This book will provide clearand relevant explanation and illustration of the possibilities ofusing SNA in a major project environment. In addition to offering the potential; for sophisticatedretrospective analysis of a wide range of systems associated withconstruction and engineering project coalitions, the author looksat how we might apply the network analysis findings to the designand management of project and supply chain networks.

This is the first textbook on social network analysis integrating theory, applications, and professional software for performing network analysis. The book introduces the main concepts and their applications in social research with exercises. An application section explaining how to perform the network analyses with Pajek software follows each theoretical section.

To understand the dynamic patterns of behaviours and interactions between athletes that characterize successful performance in different sports is an important challenge for all sport practitioners. This book guides the reader in understanding how an ecological dynamics framework for use of artificial intelligence (AI) can be implemented to interpret sport performance and the design of practice contexts. By examining how AI methodologies are utilized in team games, such as football, as well as in individual sports, such as golf and climbing, this book provides a better understanding of the kinematic and physiological indicators that might better capture athletic performance by looking at the current state-of-the-art AI approaches. Artificial Intelligence in Sport Performance Analysis provides an all-encompassing perspective in an innovative approach that signals practical applications for both academics and practitioners in the fields of coaching, sports analysis, and sport science, as well as related subjects such as engineering, computer and data science, and statistics.