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.

Autorentext
Filipe Manuel Clemente (Instituto Politécnico de Viana do Castelo, Escola Superior de Desporto e Lazer and Instituto Politécnico de Coimbra, Escola Superior de Educação de Coimbra, Portugal), Fernando Manuel Lourenço Martins (Instituto de Telecomunicações, Delegação da Covilhã and Instituto Politécnico de Coimbra, Escola Superior de Educação de Coimbra, Portugal) and Rui Sousa Mendes (Instituto Politécnico de Coimbra, Escola Superior de Educação de Coimbra, Portugal) have published more than 30 articles in journals indexed on Web of Knowledge about team sports analysis based on technological and mathematical approaches. In the last five years, the research group have published five articles on network analysis applied to team sports analysis. In addition, they have been working on a software (Performance Analysis Tool) to increase the possibilities of network analysis in the field of match analysis.

Inhalt
Introduction.- Social Network Analysis: Concepts and definitions.- Observational tools to collect data in team sports.- Micro Levels of analysis: Player's centralities in the team.- Meso Level of analysis: Subgroups in Teams.- Macro Levels of analysis: Network of the team.- Argentina's Network Analysis in FIFA World Cup 2014: A case study. / Style Definitions / table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}