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Some Issues in Distance Construction for Football Players Performance Data

Akhanli, Serhat Emre; Hennig, Christian

For mapping football (soccer) player information by using multidimensional scaling, and for clustering football players, we construct a distance measure based on players’ performance data. The variables are of mixed type, but the main focus of this paper is how count variables are treated when defining a proper distance measure between players (e.g., top and lower level variables). The distance construction involves four steps: 1) representation , 2) transformation, 3) standardisation, 4) variable weighting. Several distance measures are discussed in terms of how well they match the interpretation of distance and similarity in the application of interest, with a focus on comparing Aitchison and Manhattan distance for variables giving percentage compositions. Preliminary outcomes of multidimensional scaling and clustering are shown.

Volltext §
DOI: 10.5445/KSP/1000058749/09
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationswirtschaft und Marketing (IISM)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2017
Sprache Englisch
Identifikator ISSN: 2363-9881
KITopen-ID: 1000066924
Erschienen in Archives of Data Science, Series A (Online First)
Band 2
Heft 1
Seiten 17 S. online
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