Macro-Kinematic Differences Between Sprint and Distance Cross-Country Skiing Competitions Using the Classical Technique.

Finn Marsland,Judith Anson,Hans-Christer Holmberg,Dale W Chapman,Gordon Waddington

doi:10.3389/fphys.2018.00570

Finn Marsland, Judith Anson + Show 3 more

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https://doi.org/10.3389/fphys.2018.00570

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Abstract

We compare the macro-kinematics of six elite female cross-country skiers competing in 1.1-km Sprint and 10.5-km Distance classical technique events on consecutive days under similar weather and track conditions. The relative use of double pole (DP), kick-double pole (KDP), diagonal stride (DS), tucking (Tuck) and turning (Turn) sub-techniques, plus each technique’s respective velocities, cycle lengths and cycle rates were monitored using a single micro-sensor unit worn by each skier during the Sprint qualification, semi-final and finals, and multiple laps of the Distance race. Over a 1.0-km section of track common to both Sprint and Distance events, the mean race velocity, cyclical sub-technique velocities, and cycle rates were higher during the Sprint race, while Tuck and Turn velocities were similar. Velocities with KDP and DS on the common terrain were higher in the Sprint (KDP +12%, DS +23%) due to faster cycle rates (KDP +8%, DS +11%) and longer cycle lengths (KDP +5%, DS +10%), while the DP velocity was higher (+8%) with faster cycle rate (+16%) despite a shorter cycle length (-9%). During the Sprint the percentage of total distance covered using DP was greater (+15%), with less use of Tuck (-19%). Across all events and rounds, DP was the most used sub-technique in terms of distance, followed by Tuck, DS, Turn and KDP. KDP was employed relatively little, and during the Sprint by only half the participants. Tuck was the fastest sub-technique followed by Turn, DP, KDP, and DS. These findings reveal differences in the macro-kinematic characteristics and strategies utilized during Sprint and Distance events, confirm the use of higher cycle rates in the Sprint, and increase our understanding of the performance demands of cross-country skiing competition.

Highlights

From its early beginnings in the late 1990s, the cross-country (XC) skiing sprint event (Sprint) has become a regular feature at all levels of International Ski Federation (FIS) international competition
Examining physiological and kinematic responses during a simulated classic Sprint competition on a treadmill, Stöggl et al (2007) concluded that performance depends on physiological factors such as anaerobic capacity and fatigue resistance, and on the technique used as skiers who were able to utilize the double pole (DP) sub-technique longer performed better
There was no statistically significant difference in the mean overall velocity of the skiers participating in the entire 1.1-km Sprint and 10.5-km Distance events, and mean finishing times across the rounds of the Sprint event did not differ (Table 2)

Summary

Introduction

From its early beginnings in the late 1990s, the cross-country (XC) skiing sprint event (Sprint) has become a regular feature at all levels of International Ski Federation (FIS) international competition. Examining physiological and kinematic responses during a simulated classic Sprint competition on a treadmill, Stöggl et al (2007) concluded that performance depends on physiological factors such as anaerobic capacity and fatigue resistance, and on the technique used as skiers who were able to utilize the double pole (DP) sub-technique longer performed better This connection between choice of sub-technique and performance was confirmed by Andersson et al (2010), who reported that during a simulated freestyle Sprint competition on snow the fastest skiers used a “higher gear” (G3 over G2 technique) to a greater extent. These XC skiing macro-kinematic variables – the relative use of each sub-technique, as well as the associated velocities, cycle lengths and cycle rates – are adapted continuously by each competitor in response to the varying terrain and conditions during a competition, within the constraints of their own strengths/weaknesses and/or personal preference (Myklebust et al, 2011; Sandbakk et al, 2011; Marsland et al, 2017)

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