In alpine ski racing, a few hundredths of a second can determine the winner. Analysing the start performance could lead to minor yet significant improvements and thus possibly enhances the overall race performance of skiers. This thesis aims to investigate the start performance by analysing how changes in launch technique, pole length and acceleration strategy affect run time and speed. Additionally, it interprets these results biomechanically and compares the time measurement system and wearable sensor used in an experimental setup. Through a case study, these three factors are varied on a flat slope of 45 meters. To evaluate the start performance, sector times are recorded with four light curtains, the path trajectory with a GNSS sensor and the kinematics of the human movement by two synchronized cameras running on OpenCap. The analysis results indicate that lengthening the poles from 128 to 133 cm reduces the total run time by an average of 0.13 seconds. Changes in the acceleration strategy, which depends on the slope characteristics, lead to smaller time differences, while no difference is found when altering the launch technique. The kinematic findings from OpenCap reveal speed differences that contradict the initial data analysis, requiring further research as this software only focuses on the push-off start phase. Hardware analysis shows that the wearable sensor effectively tracks position but lacks velocity accuracy. The implementation of these findings into the training of the start phase training may improve the overall race performance of skiers. This study demonstrates the value of employing new technology in field experiments, paving the way for future research.
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