The purpose of this study was to develop a method which uses positioning data to analyse player-specific skating characteristics and to investigate the possibility to use a cost function to generate new individual and game-specific training drills. Positioning data and video from a game for professional ice hockey team in the Swedish Hockey League were synchronized, and nine different skating characteristics were manually identified and tagged for two forward players. A cost function was developed to generate individual, continuous skating sequences and to create new individual and game-specific skating drills. Skating forward was the most commonly used skating characteristic for both player but the numbers of times the players used the different skating characteristics varied, (H(8) = 23.2, p = 0.003). The number of skating characteristics between the two players differed, (?2 (8, N = 688) = 3 4.0, p < 0.001). While the total average time spent in a skating characteristic was 2.01 ± 1.13 s, time spent within each skating characteristic varied (p < 0.001). The presented method could generate individual skating drills with different attributes and shows promising results for creating individual and game-specific tests and training drills for ice hockey players, based on individual and game-specific skating characteristics.
© Copyright 2022 Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference. PACSS 2021. Advances in Intelligent Systems and Computing, vol 1426. Published by Springer. All rights reserved.