Social Network Analysis Applied To Team Sports Analysis
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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 in Sport Research
Author: Marion E. Hambrick
language: en
Publisher: Cambridge Scholars Publishing
Release Date: 2019-03-27
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.
Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference
This covers the PACSS 2021 which approached interdisciplinary collaboration between theoretical computer science and practical performance analysis though an online workshop and conference. Readers find in this book the peer-reviewed and discussed evidences on how computer scientists and performance analysts can and have worked together to solve both applied and research-based problems in elite sport, using the methods of computer science. In this edition, we organize the content according to four major topics: machine learning, text mining, best practice and interdisciplinary collaboration. This is a refined material written by leading experts with up-to-date overview of research in the multidisciplinary field of computer science and elite sport performance analysis.