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.
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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 |
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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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