Aim This presentation aimed to summarise the findings from a series of studies in skiing sports (XC skiing and biathlon) that have used Statistical Parametric Mapping (SPM) for the analyses of micro-pacing strategies. SPM is a novel statistical technique which has been promoted for analysis of smooth biomechanical data like speed collected from position system technoliges.1,2 Methods All three discussed studies utilised wearable GNSS sensor technology that recorded athlete position, distance and skiing speed. A trajectory correction and statistical parametric mapping pro cedure was used to determine the course positions (clusters) where instantaneous skiing speed was significantly related to performance. The time differences between the fastest and slowest skier in these clusters were calculated. Results The fastest athletes skied with greater instantaneous speeds in specific clusters, including main ly included uphill sections. In particular, the steepest uphill sections were most strongly related to performance for para sit-skiing and a distance freestyle XC skiing race. However, for biathlon, the largest time gains between the fastest and slowest biathletes were observed in a particular downhill section that was preceded by a 180° turn, where time gains were between 2.9 and 4.1 s in clusters of between just 12 to 62 m. Practical Application SPM analyses are useful to analyse micro-pacing strategies in skiing sports and could be used to guide race pacing strategies and training programmes.
© Copyright 2022 Book of Abstracts. 4th Nordic Winter Sports Conference "Performance in snow sports: Translating science into practice" 3rd-4th October, 2022, Mid Sweden University, Campus Östersund, Sweden. Veröffentlicht von Swedish Winter Sports Research Centre at Mid Sweden University. Alle Rechte vorbehalten.