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001 978-3-319-25855-3
003 DE-He213
005 20200421112554.0
007 cr nn 008mamaa
008 151105s2016 gw | s |||| 0|eng d
020 _a9783319258553
_9978-3-319-25855-3
024 7 _a10.1007/978-3-319-25855-3
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aClemente, Filipe Manuel.
_eauthor.
245 1 0 _aSocial Network Analysis Applied to Team Sports Analysis
_h[electronic resource] /
_cby Filipe Manuel Clemente, Fernando Manuel Louren�co Martins, Rui Sousa Mendes.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXII, 93 p. 10 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-530X
505 0 _aIntroduction -- 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: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;}.
520 _aExplaining 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.
650 0 _aEngineering.
650 0 _aSports sciences.
650 0 _aGraph theory.
650 0 _aStatistics.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aGraph Theory.
650 2 4 _aSport Science.
650 2 4 _aStatistics and Computing/Statistics Programs.
700 1 _aMartins, Fernando Manuel Louren�co.
_eauthor.
700 1 _aMendes, Rui Sousa.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319258546
830 0 _aSpringerBriefs in Applied Sciences and Technology,
_x2191-530X
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-25855-3
912 _aZDB-2-ENG
942 _cEBK
999 _c59033
_d59033