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.

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.

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.

Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw. The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks. Written using simple language and notation with few equations, this book masterfully covers the research process, including: · The initial design stage · Data collection and manipulation · Measuring key variables · Exploration of structure · Hypothesis testing · Interpretation This is an essential resource for students, researchers and practitioners across the social sciences who want to use network analysis as part of their research. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

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.

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.

Social Network Analysis in Construction Increasingly demanding and knowledgeable clients in construction require an approach to project management that recognises both the important role played by the client in the definition of a project and the lack of certainty that large and/or complex projects present. Having identified the importance of managing relationships, both analysts and practitioners today need a sophisticated framework and methodology for observing systems and managing the complex relationships in major construction project coalitions. Social Network Analysis in Construction shows how social network analysis (SNA) can be used to observe, monitor and analyse systems and relationships. Although this has been an established analytical technique in the US for some time, it is only now being developed in the UK. Stephen Pryke spent nearly two decades investigating major project relationships using SNA and brings together here mathematical and sociological methods, and major project relationships in a manner that will inspire both academic interest and a desire to apply these concepts and techniques to live construction projects. Case studies include projects from two of the UK’s largest property developers – the UK Ministry of Defence, and a County Council. SNA is innovative – but potentially inaccessible to project management analysts and practitioners. The author provides clear and relevant explanation and illustration of the possibilities of using SNA in a major project environment. In addition to offering the potential for sophisticated retrospective analysis of a wide range of systems associated with construction and engineering project coalitions, he also looks at how we might apply the network analysis findings to the design and management of project and supply chain networks. Postgraduate students and academic researchers in Project Management and Construction Management, as well as practitioners from professional consultancies and project management companies will find here an excellent exposition of an often inaccessible subject.