Prediction of running velocity in alpine skiing giant slalom - Aschenbrenner, P.; Erdmann, W. S. (International Congress Mountain & Sport. Updating study and research from laboratory to field. 11th-12th November 2005. Rovereto (TN) - Italy. Programme and book of abstracts, 2005)
Introduction: Since 1993 alpine skiing giant slalom¡¦s running of the entire course was under investigation by sport scientists from the Centre for Locomotion Research in Gdansk, Poland. The first data on tactics of running were obtained for Greek skiers (Erdmann and Giovanis 1997). Next, the best world skiers were investigated during FIS World Cup (Erdmann et al. 2000, 2001, 2002). The aim of this paper was prediction of the alpine skiing course velocity of running based on the geometry of the course and velocity of the best skiers. Material and Method: The best world skiers participated at the FIS Alpine Skiing World Cup ¡V Kranjska Gora (SLO) ¡V 69 skiers, and Saalbach ¡V Hinterglemm (AUT) ¡V 74 skiers, in January 1998. The research approach was based on measuring geometry of the entire course (Fig. 1) and video-recording of running in order to obtain time data from pole to pole. On this basis velocities for every inter-gate distance and mean velocity for the entire course was obtained. Results: Based on data of Kranjska and Saalbach the following equation was obtained for prediction of velocity of running (Aschenbrenner 2002): vi = vi-1 ¡Ñ 0, 499822 + si ¡Ñ 0, 118680 - £_iu ¡Ñ 0,02283 - £_il ¡Ñ 0,019881 ƒyƒn£ci ¡Ñ 0,066392 + 5,918524, where: vi ¡V velocity of distance i, vi-1 ¡V velocity of previous distance i-1, si ¡V length of distance i, £_iu ¡V upper angle of deviation, £_il ¡V lower angle of deviation, £ci ¡V angle of incline. Discussion: In order to qualify given course as difficult (speedy) or not one might use data obtained in this paper. The data will enable quantified description instead of qualified one. If a coach will possess geometrical description of the given course he will be able to prepare competitor¡¦s tactics of running in better way to avoid future accidents. The data of more runnings of alpine skiing courses are needed in order to predict more accurate data of velocities.