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- Andersson, Erik P., 1984-, et al.
(författare)
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Physiological responses and performance factors for double-poling and diagonal-stride treadmill roller-skiing time-trial exercise
- 2023
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Ingår i: European Journal of Applied Physiology. - : Springer. - 1439-6319 .- 1439-6327. ; 123:11, s. 2495-2509
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To compare physiological responses between a self-paced 4-min double-poling (DP) time-trial (TTDP) versus a 4-min diagonal-stride (DS) time-trial (TTDS). The relative importance of peak oxygen uptake (V ˙ O2peak), anaerobic capacity, and gross efficiency (GE) for projection of 4-min TTDP and TTDS roller-skiing performances were also examined. Methods: Sixteen highly trained male cross-country skiers performed, in each sub-technique on separate occasions, an 8 × 4-min incremental submaximal protocol, to assess individual metabolic rate (MR) versus power output (PO) relationships, followed by a 10-min passive break and then the TTDP or TTDS, with a randomized order between sub-techniques. Results: In comparison to TTDS, the TTDP resulted in 10 ± 7% lower total MR, 5 ± 4% lower aerobic MR, 30 ± 37% lower anaerobic MR, and 4.7 ± 1.2 percentage points lower GE, which resulted in a 32 ± 4% lower PO (all P < 0.01). The V ˙ O2peak and anaerobic capacity were 4 ± 4% and 30 ± 37% lower, respectively, in DP than DS (both P < 0.01). The PO for the two time-trial (TT) performances were not significantly correlated (R 2 = 0.044). Similar parabolic pacing strategies were used during both TTs. Multivariate data analysis projected TT performance using V ˙ O2peak, anaerobic capacity, and GE (TTDP, R 2 = 0.974; TTDS, R 2 = 0.848). The variable influence on projection values for V ˙ O2peak, anaerobic capacity, and GE were for TTDP, 1.12 ± 0.60, 1.01 ± 0.72, and 0.83 ± 0.38, respectively, and TTDS, 1.22 ± 0.35, 0.93 ± 0.44, and 0.75 ± 0.19, respectively. Conclusions: The results show that a cross-country skier’s “metabolic profile” and performance capability are highly sub-technique specific and that 4-min TT performance is differentiated by physiological factors, such as V ˙ O2peak, anaerobic capacity, and GE.
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| 2. |
- Andersson, Erik P., 1984-, et al.
(författare)
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The Anaerobic Capacity of Cross-Country Skiers : The Effect of Computational Method and Skiing Sub-technique
- 2020
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Ingår i: Frontiers in Sports and Active Living. - : Frontiers Media SA. - 2624-9367. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Anaerobic capacity is an important performance-determining variable of sprint cross-country skiing. Nevertheless, to date, no study has directly compared the anaerobic capacity, determined using the maximal accumulated oxygen deficit (MAOD) method and gross efficiency (GE) method, while using different skiing sub-techniques.Purpose: To compare the anaerobic capacity assessed using two different MAOD approaches (including and excluding a measured y-intercept) and the GE method during double poling (DP) and diagonal stride (DS) cross-country skiing.Methods: After an initial familiarization trial, 16 well-trained male cross-country skiers performed, in each sub-technique on separate occasions, a submaximal protocol consisting of eight 4-min bouts at intensities between ~47–78% of V.V.O2peak followed by a 4-min roller-skiing time trial, with the order of sub-technique being randomized. Linear and polynomial speed-metabolic rate relationships were constructed for both sub-techniques, while using a measured y-intercept (8+YLIN and 8+YPOL) or not (8–YLIN and 8–YPOL), to determine the anaerobic capacity using the MAOD method. The average GE (GEAVG) of all eight submaximal exercise bouts or the GE of the last submaximal exercise bout (GELAST) were used to calculate the anaerobic capacity using the GE method. Repeated measures ANOVA were used to test differences in anaerobic capacity between methods/approaches.Results: A significant interaction was found between computational method and skiing sub-technique (P < 0.001, η2 = 0.51) for the anaerobic capacity estimates. The different methodologies resulted in significantly different anaerobic capacity values in DP (P < 0.001, η2 = 0.74) and in DS (P = 0.016, η2 = 0.27). The 8-YPOL model resulted in the smallest standard error of the estimate (SEE, 0.24 W·kg−1) of the MAOD methods in DP, while the 8-YLIN resulted in a smaller SEE value than the 8+YLIN model (0.17 vs. 0.33 W·kg−1) in DS. The 8-YLIN and GELAST resulted in the closest agreement in anaerobic capacity values in DS (typical error 2.1 mL O2eq·kg−1).Conclusions: It is discouraged to use the same method to estimate the anaerobic capacity in DP and DS sub-techniques. In DP, a polynomial MAOD method (8-YPOL) seems to be the preferred method, whereas the 8-YLIN, GEAVG, and GELAST can all be used for DS, but not interchangeable, with GELAST being the least time-consuming method.
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| 3. |
- Lögdal, Nestor, et al.
(författare)
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Individual Fluctuations in Blood Lactate Concentration During an Ice Hockey Game; Differences Between Player Positions
- 2022
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Ingår i: International Journal of Exercise Science. - : Western Kentucky University. - 1939-795X. ; 15:6, s. 985-993
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Tidskriftsartikel (refereegranskat)abstract
- International Journal of Exercise Science 15(6): 985-993, 2022. The main purpose of the current study was to provide an in-depth description of individual player’s intra-game physiological responses during an ice hockey game. A secondary aim was to compare these responses between forwards and defensemen. Six elite junior ice hockey players, three forwards and three defensemen, median (interquartile range) 17 (17–17) years, 182 (180– 185) cm, and 78 (74– 80) kg were recruited to participate in the study. Capillary blood samples were taken following each shift and analyzed for blood lactate concentration (BLC). Heart rate (HR) was registered continuously throughout the game. The game was filmed and shift lengths were determined retrospectively using a time-motion analysis. All players had BLC ranging between 1.8 and 10.7 mmol/L (mean = 5.5 mmol/L), with forwards reaching a significantly higher value than defensive players (F1,32 = 75.2, p < 0.0001), a significant effect of time was also observed (F2,25 = 6.4, p = 0.0058). During the game, the players accumulated 11:18 ± 5:04 (minutes:seconds) above 90% of their maximal heart rate (HRmax), but the majority of the time was below 80% of HRmax. The fluctuations in BLC and heart rate demonstrate that the intensity is highly variable during games and challenges both aerobic and anaerobic metabolic pathways. The higher BLC of forwards might indicate that they perform more high-intensity work during games than defensive players.
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