Authors:
Christoph Thorwartl
1
;
2
;
Thomas Grah
1
;
Harald Rieser
1
;
Günter Amesberger
2
;
Stefan Kranzinger
1
;
Thomas Stöggl
2
;
3
;
Helmut Holzer
4
and
Thomas Finkenzeller
2
Affiliations:
1
Human Motion Analytics, Salzburg Research Forschungsgesellschaft m.b.H., Salzburg, Austria
;
2
Department of Sport and Exercise Science, University of Salzburg, Hallein/Rif, Austria
;
3
Red Bull Athlete Performance Center, Thalgau, Austria
;
4
Atomic Austria GmbH, Altenmarkt, Austria
Keyword(s):
Edging, Performance Analysis, Skiing Technique, Sonification, Wearable Sensors.
Abstract:
In alpine skiing, the way a ski engages with the snow surface – particularly at the beginning of a turn – plays a key role in determining performance. This study introduces Edging Velocity (EV) as a novel metric to quantify how quickly the ski is tipped onto its edge during turn initiation. Building upon sensor-based motion analysis using the “Connected Boot” system, we investigated three distinct skiing techniques: race carving, moderate carving, and parallel ski steering. An expert skier performed multiple turns for each technique, and EV was computed from edge angle progression. Results show that EV was highest during race carving, followed by moderate carving, and lowest during parallel ski steering. All pairwise differences were statistically significant (p < 0.001 or p < 0.01). These findings highlight EV’s potential as a performance-relevant parameter for optimizing edge engagement. Integrated into real-time feedback systems, EV may support learning and refinement of skiing te
chnique, particularly in the critical early phase of a turn.
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