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  • Author: Jostein Hallén x
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Thomas Losnegard and Jostein Hallén

Purpose:

Sprint- (≤1.8 km) and distance-skiing (≥15 km) performance rely heavily on aerobic capacity. However, in sprint skiing, due to the ~20% higher speed, anaerobic capacity contributes significantly. This study aimed to identify the possible anthropometric and physiological differences between elite male sprint and distance skiers.

Methods:

Six sprint and 7 distance international-level cross-country skiers completed testing using the V2 skating technique on a roller-ski treadmill. Measurements included submaximal O2 cost (5°, 3 m/s) and a 1000-m time trial (6°, >3.25 m/s) to assess VO2peak and accumulated oxygen (ΣO2) deficit.

Results:

The groups displayed similar O2 cost during the submaximal load. The sprint skiers had a higher ΣO2 deficit (79.0 ± 11.3 vs 65.7 ± 7.5 mL/kg, P = .03, ES = 1.27) and VO2peak in absolute values (6.6 ± 0.5 vs 6.0 ± 0.5 L/min, P = .04, ES =1.23), while VO2peak relative to body mass was lower than in the distance skiers (76.4 ± 4.4 vs 83.0 ± 3.2 mL · kg−1 · min−1, P = .009, ES = 1.59). The sprint skiers were heavier than the distance skiers (86.6 ± 6.1 vs 71.8 ± 7.2 kg, P = .002, ES = 2.07), taller (186 ± 5 vs 178 ± 7 cm, P = .04, ES = 1.25), and had a higher body-mass index (24.9 ± 0.8 vs 22.5 ± 1.3 kg/m2, P = .003, ES = 2.05).

Conclusion:

The elite male sprint skiers showed different anthropometric and physiological qualities than the distance skiers, with these differences being directly related to body mass.

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Håvard Myklebust, Øyvind Gløersen and Jostein Hallén

In regard to simplifying motion analysis and estimating center of mass (COM) in ski skating, this study addressed 3 main questions concerning the use of inertial measurement units (IMU): (1) How accurately can a single IMU estimate displacement of os sacrum (S1) on a person during ski skating? (2) Does incorporating gyroscope and accelerometer data increase accuracy and precision? (3) Moreover, how accurately does S1 determine COM displacement? Six world-class skiers roller-ski skated on a treadmill using 2 different subtechniques. An IMU including accelerometers alone (IMU-A) or in combination with gyroscopes (IMU-G) were mounted on the S1. A reflective marker at S1, and COM calculated from 3D full-body optical analysis, were used to provide reference values. IMU-A provided an accurate and precise estimate of vertical S1 displacement, but IMU-G was required to attain accuracy and precision of < 8 mm (root-mean-squared error and range of displacement deviation) in all directions and with both subtechniques. Further, arm and torso movements affected COM, but not the S1. Hence, S1 displacement was valid for estimating sideways COM displacement, but the systematic amplitude and timing difference between S1 and COM displacement in the anteroposterior and vertical directions inhibits exact calculation of energy fluctuations.

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Thomas Losnegard, Martin Andersen, Matt Spencer and Jostein Hallén

Purpose:

To investigate the effects of an active and a passive recovery protocol on physiological responses and performance between 2 heats in sprint cross-country skiing.

Methods:

Ten elite male skiers (22 ± 3 y, 184 ± 4 cm, 79 ± 7 kg) undertook 2 experimental test sessions that both consisted of 2 heats with 25 min between start of the first and second heats. The heats were conducted as an 800-m time trial (6°, >3.5 m/s, ~205 s) and included measurements of oxygen uptake (VO2) and accumulated oxygen deficit. The active recovery trial involved 2 min standing/walking, 16 min jogging (58% ± 5% of VO2peak), and 3 min standing/walking. The passive recovery trial involved 15 min sitting, 3 min walk/jog (~ 30% of VO2peak), and 3 min standing/walking. Blood lactate concentration and heart rate were monitored throughout the recovery periods.

Results:

The increased 800-m time between heat 1 and heat 2 was trivial after active recovery (effect size [ES] = 0.1, P = .64) and small after passive recovery (ES = 0.4, P = .14). The 1.2% ± 2.1% (mean ± 90% CL) difference between protocols was not significant (ES = 0.3, P = .3). In heat 2, peak and average VO2 was increased after the active recovery protocol.

Conclusions:

Neither passive recovery nor running at ~58% of VO2peak between 2 heats changed performance significantly.

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Matt Spencer, Thomas Losnegard, Jostein Hallén and Will G. Hopkins

Analyses of elite competitive performance provide useful information for research and practical applications.

Purpose:

Here the authors analyze performance times of cross-country skiers at international competitions (World Cup, World Championship, and Olympics) in classical and free styles of women’s and men’s distance and sprint events, each with a total of 410–569 athletes competing in 1–44 races at 15–25 venues from seasons 2002 to 2011.

Methods:

A linear mixed model of race times for each event provided estimates of within-athlete race-to-race variability expressed as a coefficient of variation (CV) after adjustment for fixed or random effects of snow conditions, altitude, race length, and competition terrain.

Results:

Within-athlete variability was similar for men and women over various events for all athletes (CV of 1.5–1.8%) and for the annual top-10 athletes (1.1–1.4%). Observed effects of snow conditions and altitude on mean time were substantial (~2%) but mostly unclear, owing to large effects of terrain (CV of 4–10% in top-10 analyses). Predictability of performance was extremely high for all athletes (intraclass correlations of .90–.96) but only trivial to poor for top-10 athletes (men .00–.03, women .03–.35).

Conclusion:

The race-to-race variability of top-ranked skiers is similar to that of other elite endurance athletes. Estimates of the smallest worthwhile performance enhancement (0.3× within-athlete variability) will help researchers and practitioners evaluate strategies affecting performance of elite skiers.

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Thomas Losnegard, Håvard Myklebust, Øyvind Skattebo, Hans Kristian Stadheim, Øyvind Sandbakk and Jostein Hallén

Purpose:

In the double-poling (DP) cross-country-skiing technique, propulsive forces are transferred solely through the poles. The aim of the current study was to investigate how pole length influences DP performance, O2 cost, and kinematics during treadmill roller skiing.

Methods:

Nine male competitive cross-country skiers (24 ± 3 y, 180 ± 5 cm, 72 ± 5 kg, VO2max running 76 ± 6 mL · kg–1 · min–1) completed 2 identical test protocols using self-selected (84% ± 1% of body height) and long poles (self-selected + 7.5 cm; 88% ± 1% of body height) in a counterbalanced fashion. Each test protocol included a 5-min warm-up (2.5 m/s; 2.5°) and three 5-min submaximal sessions (3.0, 3.5, and 4.0 m/s; 2.5°) for assessment of O2 cost, followed by a selfpaced 1000-m time trial (~3 min, >5.0 m/s; 2.5°). Temporal patterns and kinematics were assessed using accelerometers and 2D video.

Results:

Long poles reduced 1000-m time (mean ± 90% confidence interval; –1.0% ± 0.7%, P = .054) and submaximal O2 cost (–2.7% ± 1.0%, P = .002) compared with self-selected poles. The center-of-mass (CoM) vertical range of displacement tended to be smaller for long than for self-selected poles (23.3 ± 3.0 vs 24.3 ± 3.0 cm, P = .07). Cycle and reposition time did not differ between pole lengths at any speeds tested, whereas poling time tended to be shorter for self-selected than for long poles at the lower speeds (≤3.5 m/s, P ≤ .10) but not at the higher speeds (≥4.0 m/s, P ≥ .23).

Conclusions:

DP 1000-m time, submaximal O2 cost, and CoM vertical range of displacement were reduced in competitive cross-country skiers using poles 7.5 cm longer than self-selected ones.