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Record Nr. |
UNINA9910254207003321 |
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Autore |
Clemente Filipe Manuel |
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Titolo |
Social Network Analysis Applied to Team Sports Analysis / / by Filipe Manuel Clemente, Fernando Manuel Lourenço Martins, Rui Sousa Mendes |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
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ISBN |
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Edizione |
[1st ed. 2016.] |
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Descrizione fisica |
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1 online resource (101 p.) |
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Collana |
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SpringerBriefs in Applied Sciences and Technology, , 2191-530X |
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Disciplina |
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Soggetti |
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Applied mathematics |
Engineering mathematics |
Graph theory |
Sports sciences |
Statistics |
Mathematical and Computational Engineering |
Graph Theory |
Sport Science |
Statistics and Computing/Statistics Programs |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Social Network Analysis: Concepts and definitions -- Observational tools to collect data in team sports -- Micro Levels of analysis: P layer’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: |
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Sommario/riassunto |
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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. |
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