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Some Issues in Distance Construction for Football Players Performance Data

Akhanli, SE; Hennig, CM; (2017) Some Issues in Distance Construction for Football Players Performance Data. Archives of Data Science , 2 (1) 10.5445/KSP/1000058749/09. Green open access

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Abstract

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.

Type: Article
Title: Some Issues in Distance Construction for Football Players Performance Data
Open access status: An open access version is available from UCL Discovery
DOI: 10.5445/KSP/1000058749/09
Publisher version: http://dx.doi.org/10.5445/KSP/1000058749/09
Language: English
Additional information: This is an Open Access article published under a Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) licence (https://creativecommons.org/licenses/by-sa/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/1557272
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