Predicting the personal-best times of speed skaters using case-based reasoning

Speed skating is a form of ice skating in which the skaters race each other over a variety of standardised distances. Races take place on specialised ice-rinks and the type of track and ice conditions can have a significant impact on race-times. As race distances increase, pacing also plays an important role. In this paper we seek to extend recent work on the application of case-based reasoning to marathon-time prediction by predicting race-times for speed skaters. In particular, we propose and evaluate a number of case-based reasoning variants based on different case and feature representations to generate track-specific race predictions. We show it is possible to improve upon state-of-the-art prediction accuracy by harnessing richer case representations using shorter races and track-adjusted finish and lap-times.
© Copyright 2020 Case-Based Reasoning Research and Development. ICCBR 2020. Published by Springer. All rights reserved.

Bibliographic Details
Subjects:
Notations:endurance sports
Tagging:maschinelles Lernen
Published in:Case-Based Reasoning Research and Development. ICCBR 2020
Language:English
Published: Cham Springer 2020
Series:Lecture Notes in Computer Science, 12311
Online Access:https://doi.org/10.1007/978-3-030-58342-2_8
Pages:112-126
Document types:book
Level:advanced