Publication
Title
Towards personalised performance prediction in road cycling through machine learning
Author
Abstract
We study the feasibility of applying machine learning to predict the performance of road cyclists using publicly available data. The performance is investigated by predicting the presence or absence in the top places of next year’s ranking based on a rider’s characteristics and results in the current and previous years. We apply several classification algorithms and obtain that random forest is the best-performing model. Our work is a first step towards creating personalised performance models in professional road cycling.
Language
English
Source (book)
13th World Congress of Performance Analysis of Sport and 13th International Symposium on Computer Science in Sport, 10-13 September, 2022, Vienna, Austria
Source (series)
Advances in Intelligent Systems and Computing ; 1448
Publication
Cham : Springer , 2023
ISBN
978-3-031-31771-2
978-3-031-31772-9
DOI
10.1007/978-3-031-31772-9_20
Volume/pages
p. 93-96
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identifier
Creation 29.04.2024
Last edited 30.04.2024
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