Supporting athlete selection and strategic planning in track cycling omnium: A statistical and machine learning approach

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Ofoghi, Bahadorreza, Zeleznikow, John, MacMahon, Clare and Dwyer, Dan (2013) Supporting athlete selection and strategic planning in track cycling omnium: A statistical and machine learning approach. Information Sciences, 233. pp. 200-213. ISSN 0020-0255

Abstract

We demonstrated an in-depth data analytical process to facilitate the decision-making procedure in track cycling omnium that includes utilization of statistical, machine learning-based, and probabilistic approaches. We considered both interomnium and intra-omnium procedures.

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/22254
DOI https://doi.org/10.1016/j.ins.2012.12.050
Official URL http://www.sciencedirect.com/science/article/pii/S...
Subjects Historical > FOR Classification > 0801 Artificial Intelligence and Image Processing
Historical > FOR Classification > 1106 Human Movement and Sports Science
Historical > Faculty/School/Research Centre/Department > School of Management and Information Systems
Historical > Faculty/School/Research Centre/Department > Institute of Sport, Exercise and Active Living (ISEAL)
Current > Division/Research > College of Sports and Exercise Science
Keywords ResPubID26708, Leave-One-Out Cross-Validation, LOOCV, decision support, track cycling omnium, statistical analysis, decision support, Bayesian network, machine learning
Citations in Scopus 14 - View on Scopus
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