This study investigated the explanatory power of a sensor fusion of two complementary methods to explain performance and its underlying mechanisms in ski jumping. A differential Global Navigation Satellite System (dGNSS) and a markerless video-based pose estimation system (PosEst) were used to measure the kinematics and kinetics from the start of the in-run to the landing. The study had two aims; firstly, the agreement between the two methods was assessed using 16 jumps by athletes of national level from 5 m before the take-off to 20 m after, where the methods had spatial overlap. The comparison revealed a good agreement from 5 m after the take-off, within the uncertainty of the dGNSS (±0.05m). The second part of the study served as a proof of concept of the sensor fusion application, by showcasing the type of performance analysis the systems allows. Two ski jumps by the same ski jumper, with comparable external conditions, were chosen for the case study. The dGNSS was used to analyse the in-run and flight phase, while the PosEst system was used to analyse the take-off and the early flight phase. The proof-of-concept study showed that the methods are suitable to track the kinematic and kinetic characteristics that determine performance in ski jumping and their usability in both research and practice.

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The purpose of this study was to find a generic method to determine the aerial phase of ski jumping in which the athlete is in a steady gliding condition, commonly known as the ‘stable flight’ phase. The aerial phase of ski jumping was investigated from a physical point mass, rather than an athlete–action-centered perspective. An extensive data collection using a differential Global Navigation Satellite System (dGNSS) was carried out in four different hill sizes. A total of 93 jumps performed by 19 athletes of performance level, ranging from junior to World Cup, were measured. Based on our analysis, we propose a generic algorithm that identifies the stable flight based on steady glide aerodynamic conditions, independent of hill size and the performance level of the athletes. The steady gliding is defined as the condition in which the rate-of-change in the lift-to-drag-ratio (LD-ratio) varies within a narrow band-width described by a threshold τ. For this study using dGNSS, τ amounted to 0.01s−1, regardless of hill size and performance level. While the absolute value of τ may vary when measuring with other sensors, we argue that the methodology and algorithm proposed to find the start and end of a steady glide (stable flight) could be used in future studies as a generic definition and help clarify the communication of results and enable more precise comparisons between studies.