The AdMos receiver from Advanced Sport Instruments is a global navigation satellite system (GNSS) frequently used in alpine ski racing, with users from national and professional teams. Therefore, a validation was conducted for use of the AdMos in alpine skiing, using data from both recreational and competitive skiers. Athletes skied a total of 60 km in different measurement and skiing conditions, while carrying both an AdMos and a differential GNSS, which was used as the gold standard. From the GNSS position data, speed, acceleration, turn radius, trajectory incline and impulse were calculated as instantaneous and turn average measures for both GNSS systems and errors between the systems were calculated. The median and interquartile range (IQR) for the instantaneous errors were below 3.5 (3.5) m for horizontal plane position and below 7.0 (4.3) m for the 3D position. The median and IQR for instantaneous errors and turn average errors, respectively, were below 0.04 (0.24)/0.04 (0.16) m/s for speed, below 0.23 (1.06)/0.35 (0.63) m/s² for acceleration, below 0.47 (5.65)/0.73 (5.3) m for turn radius, and below 0.043 (1.96)/0.42 (1.42) degrees for trajectory incline. The median and IQR for turn average impulse were 0.025 (0.099) BWs. The position error changed gradually and randomly over time, with low noise levels causing smooth trajectories of similar shape but spatially shifted from the true trajectory that allowed the position–time derivation of the performance parameters, and detection of turns with 3% median and 5% IQR error. The accuracy assessment revealed that (1) the error levels were comparable to other consumer-grade standalone GNSS units designed for sport; (2) the trajectories closely resembled the true trajectories but with a random shift that changed over time and had a low noise level; (3) there was a very low instantaneous speed error that may allow the detection of many performance aspects of skiing and other sports; and (4) there were larger instantaneous errors for the remaining performance parameters, which decreased substantially when averaged over a turn.

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 $\tau$. For this study using dGNSS, $\tau$ amounted to $0.01$$\mathrm{s}$⁻¹, regardless of hill size and performance level. While the absolute value of $\tau$ 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.

The purpose of this investigation was to examine the performance strategy of three ski jumpers during the steady glide phase and explain how different strategical solutions can lead to jumps of roughly the same length. In this study, a total of 24 jumps performed by two World Cup (WC) athletes and one Continental Cup (COC) athlete were measured with a differential Global Navigation Satellite System (dGNSS) on a large ski jumping hill. For each athlete, the continuous position data, velocity, aerodynamic forces and lift-to-drag ratio (LD-ratio) were averaged and compared for the steady glide phase to examine individual jump strategies. The dGNSS yielded accurate measurements of trajectory, velocity and aerodynamic forces, revealing clear differences between the athletes. The largest differences were found between the WC athletes and the COC athlete. The WC athletes focused on maximizing horizontal velocity while the COC athlete minimized vertical velocity. This difference may be explained by the different hill sizes the athletes normally compete on. One of the WC athletes consistently increased their horizontal velocity during the end of the steady glide phase by maintaining a high LD-ratio, which highlights the effect of aerodynamics on the resulting velocity, trajectory and jump length.