Alpine ski races can last between 45 and 150 seconds, and metabolic demand lies above the maximal oxygen consumption (V[Combining Dot Above]O2max) (22,23). This intensity can lead to exceeding 90% of V[Combining Dot Above]O2max within 90 seconds (17). The ability to maintain muscle power output in such situations is interdependent on critical power (CP), anaerobic and aerobic capacities, and the time constant (τ) of aerobic energy production (V[Combining Dot Above]O2 kinetics) (5,6,11). Limits to these parameters determine the imminence and severity of muscular fatigue, which result in reductions in power output and detriments to ski performance.
The 90-second box jump test (BJ90) has been employed to assess performance capacity in alpine skiers because it is supposed to simulate the muscular, coordinational, and metabolic demands of ski racing (4) (see description in Methods). Although one study has reported changes in BJ90 performance with a controlled training intervention (3), no physiological measurements were obtained during the test, so the mechanisms for the improvement were not clear. Furthermore, although often applied in the practice, previous scientific publications, most from the precarving era, have only included performance scores (1,3,4,9) and data on the metabolic character of the test, such as oxygen uptake and its kinetics or contributions of aerobic and anaerobic energy systems, are lacking.
A previous study from our laboratory employed a short concentrated block of high-intensity interval training (HIT) to quickly improve aerobic capacity in elite junior alpine skiers (3). Alongside a 7.5% improvement in V[Combining Dot Above]O2max of male subjects, there was a 9.1% increase in cycling power at the second ventilatory threshold (VT2), which is similar to CP, and significantly improved BJ90 performance (3).
Thus, although it appears that such HIT blocks represent an effective strategy for quickly improving V[Combining Dot Above]O2max and BJ90 performance in skiers, the question remains as to the effect of a HIT block on the energy production pattern during the BJ90, which could relate to the energy production pattern during ski performance. Thus, we designed an experiment to investigate how specifically training the aerobic capacity influences energy production, fatigue, and performance in the BJ90. We hypothesized that, after a HIT block, in parallel to increasing their V[Combining Dot Above]O2max, subjects would generate a larger portion of energy aerobically during the BJ90, which would allow for improved performance.
Experimental Approach to the Problem
This study employed a nonexperimental design. Subjects carried out the training prescribed to them by their coaches, namely an 8-day HIT block designed to increase V[Combining Dot Above]O2max. There was no control group and no additional intervention by the investigators. One day before and 6 days after the training block in a controlled setting at the same time of day, V[Combining Dot Above]O2max test and the BJ90 were carried out, with assistance of the investigators, to see how training-induced changes to V[Combining Dot Above]O2max would affect BJ90 performance (see study timeline in Table 1).
Nine male elite junior alpine skiers from an elite sport school (Nationales Leistungszentrum Engelberg, Switzerland) participated in the study. Their mean ± SD age, body weight, and body fat percentage were 16.8 ± 1.3 years (range 16–18), 70.6 ± 7.0 kg, and 11.2 ± 1.7%. Participants were experienced competitors and voluntarily underwent all testing procedures, which were conducted within the context of their normal performance evaluation, and which complied with the Helsinki's Declarations (Ethical Committee of Canton Lucerne, No. 13,076). Athletes and their parents were informed in detail about all test procedures and risks and gave their oral consent before data collection.
Each subject visited the testing facility once before (pre) and once after the intervention (post), at the same time of day, for a series of measurements. Initially, skinfolds were taken from 7 anatomical sites for the determination of body fat percentage using the equation from Jackson and Pollock (12). Subjects then warmed up at a self-selected intensity on cycle ergometer for 15 minutes.
After the warm-up, subjects performed 3 maximal trials each, separated by 20 seconds, of the countermovement (CMJ) and squat jump (SJ) on a Quattro Jump force plate with accompanying (version 1.07) software (Kistler Instruments, Winterthur, Switzerland). Analyzed parameters for both jumps were jump height (H), maximum concentric power production normalized to body weight (Pmax), both averaged from the 3 trials, and the effect of prestretch (ration of height in CMJ to height in SJ, expressed as percentage).
Next, subjects performed a graded exercise test (GXT) to exhaustion on an Ergometrics 800S cycle ergometer (ergoline GmbH, Bitz, Germany) whereas spirometric data were gathered using the Oxycon Alpha spirometry system (Erich Jaeger GmbH, Höchberg, Germany). After 2 minutes of rest and 3 minutes at 25 W, resistance was increased in a ramp-like fashion by 5 W every 10 seconds, until the subject could no longer maintain a pedaling cadence of 60 revolutions per minute (3). Heartrate (HR) was measured telemetrically with a Polar RS400 HR monitor (Polar Electro Oy, Kempele, Finland), and blood lactate concentration (BLa) was taken at the finger at 2-minute intervals during the GXT and immediately and 2 minutes after the GXT using the Lactate Pro analyzer (Arkray Factory Inc., AxonLab AG, Baden, Switzerland). Concurrent with BLa measurements, subjects were asked to rate their perceived exertion according to the 6–20 Borg's scale.
Maximal oxygen uptake (V[Combining Dot Above]O2max) and respiratory exchange ratio before test end (RERmax) were defined as the highest 30-second compiled values; the former was expressed in absolute (ml·minute−1) and relative (ml·minute−1·kg−1) terms. Maximal power output (POmax, W) was the final work rate attained. Maximal HR (HRmax, per minute) was the highest 5-second compiled value. Pulmonary gas exchange data were compiled into 15-second averages for determination of ventilatory thresholds (VT1, VT2). The VT1 was identified initially by the V-slope method and confirmed by a concurrent rise in VE·V[Combining Dot Above]O2−1 but not VE·V[Combining Dot Above]CO2−1 relative to power output (PO). The VT2 was identified by a further steepening of VE·V[Combining Dot Above]O2−1 concurrent with a rise in VE·V[Combining Dot Above]CO2−1 relative to PO. As such, both VT could be expressed in terms of absolute and relative (% max) V[Combining Dot Above]O2 (V[Combining Dot Above]O2VT), PO (POVT), HR (HRVT), and through linear interpolation, BLa (BLaVT).
Ten minutes after completing the GXT, subjects performed the BJ90. This test involved completing as many jumps as possible onto a box (width: 50 cm, height: 44 cm) while alternating right-to-left on jumping down. Subjects performed the test while connected to the same spirometric analysis system as before. The BLa was taken at the finger 1 minute before and 2 and 4 minutes after the test. The BJ90 was familiar to all subjects.
Total jumps in the BJ90 were tallied after 30, 60, and 90 seconds. Fatigue indices were calculated as the percent change in jumps per 30-second segment. The V[Combining Dot Above]O2 was measured breath-by-breath beginning 1 minute before the test began. The data were filtered of measurements lying more than 3 SD apart from the previous breath. Data up until test end were then mathematically transformed to a best-fit exponential curve by minimizing residuals based on the following formula for the determination of V[Combining Dot Above]O2 on-kinetics:
where V[Combining Dot Above]O2 (t) is V[Combining Dot Above]O2 at time t; V[Combining Dot Above]O2base is baseline V[Combining Dot Above]O2 during the minute preceding the test; A is the amplitude of V[Combining Dot Above]O2 increase that is peak V[Combining Dot Above]O2 – V[Combining Dot Above]O2base; TD is the time delay; and τ is the time constant.
For 4 of the 9 subjects, V[Combining Dot Above]O2 off-kinetics were calculated in the same manner, whereby V[Combining Dot Above]O2 base was taken from the last 30 seconds of the test. Excess postexercise O2 consumption was measured over the initial 5 minutes of recovery (EPOC5). Based on pilot data, EPOC5 provides the best estimate of the O2 deficit and therefore the anaerobic energy production in supramaximal exercise of this intensity and duration (15). Thus, we also compared total O2 consumption during the test to EPOC5 to express proportions of aerobic and anaerobic energy. The other 5 subjects performed additional CMJ 3 minutes before and 1 minute after the BJ90 to determine the degree of muscular fatigue induced by the BJ90 (7).
Beginning the day after pretesting, subjects completed an 8-day HIT block, consisting of 10 HIT sessions (3,19–21). Sessions consisted either of four 4-minute intervals or 2 sets of 10 × 30 seconds–on/30 seconds–off, based on the protocol of Helgerud et al. (10). Training modes was either cycling, an obstacle course including agility drills, or running. This was followed by 5 days of light recovery training before to posttesting (Table 1).
Data from pre- and post-tests were compared using repeated-measures t-tests with Microsoft Excel software. The level of significance was set at p = 0.05. Pearson's correlations were performed with SPSS statistical software (Version 19; IBM, Armonk, NY, USA). Effect sizes (d) of individual parameters were calculated as the absolute value of changes to the group mean divided by the pretest, between-subject SD. Results are reported as mean ± SD.
Using the descriptive data of the metabolic character of the BJ90, rough comparisons were made to the previously published data characterizing the metabolic demands of race-like ski runs. In this way, the validity of the BJ90 as a ski-specific performance test could be considered.
No significant changes occurred in subjects' anthropometric characteristics.
A 90-Second Box Jump
There was no change in BJ90 in terms of total jumps (pre: 90 ± 7, post: 91 ± 4, p = 0.56, d = 0.2), and only 3 of 9 subjects improved performance. During posttesting, BLa was higher at the onset of BJ90 (pre: 11.4 ± 1.7 mmol·L−1, post: 12.6 ± 1.7 mmol·L−1, p = 0.01), but not different at either 2 minutes (pre: 14.8 ± 0.9 mmol·L−1, post: 15.5 ± 1.0 mmol·L−1, p = 0.12) or 4 minutes after the BJ90 (pre: 14.5 ± 0.8 mmol·L−1, post: 14.7 ± 0.8 mmol·L−1, p = 0.66). In posttesting, subjects performed significantly fewer jumps in the first 30 seconds (pre: 35 ± 2, post: 33 ± 2, −5.3 ± 5.2%, p = 0.01, d = 1.0), which tended to be correlated (r = −0.59, p = 0.1) with somewhat slower V[Combining Dot Above]O2 mean response times (pre: 14.9 ± 2.1, post: 16.3 ± 1.9 seconds, p = 0.06, d = 0.7). However, fatigue indices between the first and second 30-second segments (pre: −16.4 ± 7.5%, post: −8.9 ± 5.1%, p = 0.03), as well as V[Combining Dot Above]O2peak (pre: 3,904 ± 499 ml·minute−1, post: 4,095 ± 558 ml·minute−1, +4.9 ± 5.2%, p = 0.03) were improved after training. Otherwise, there were no changes in V[Combining Dot Above]O2 response variables (Table 2).
During the BJ90, energy provided from aerobic sources was unaltered by training and represented 63.3 ± 2.8% of total energy (pooled pre- and post-data from 4-subject subgroup, see Figure 1). Energy demand corresponded to 126 ± 2% of cycling V[Combining Dot Above]O2max (pooled pre- and post-data from 4-subject subgroup, see Figure 2). Peak V[Combining Dot Above]O2 attained during the BJ90, when expressed in relation to cycling V[Combining Dot Above]O2max, was similar before and after training and corresponded to 92.7 ± 3.5% and 94.8 ± 5.4% of V[Combining Dot Above]O2max, respectively (n = 9). Although there were no significant correlations between physiological measures and performance, there were certain strong tendencies (p < 0.1) for performance to be related to some O2 consumption parameters (n = 18, Table 2).
Graded Exercise Test
In posttesting, subjects cycled 23 ± 22 seconds longer (+3.0%, p = 0.01) in the GXT, which produced higher POmax values (pre: 406 ± 33 W, post: 418 ± 38 W, +2.8 ± 2.7%, p = 0.01, d = 0.4). The V[Combining Dot Above]O2max (pre: 58.8 ± 2.0 ml·minute−1·kg−1, post: 61.4 ± 2.3 ml·minute−1·kg−1, +4.3 ± 3.2%, p = 0.004, d = 1.3) and BLa (pre: 11.7 ml·minute−1·kg−1, post: 14.8 mmol·l−1, +27.9 ± 17.2%, p = 0.001, d = 2.4) were both significantly higher after training. Power output at VT1 increased by 20 ± 23 W (p = 0.03), whereas PO at VT2 was unchanged.
There was a tendency (p = 0.08) for reduced Pmax in CMJ (pre: 54.9 ± 5.6 W·kg−1, post: 53.5 ± 4.5 W·kg−1, d = 0.2), but no change in jump height (pre: 51 ± 3.6 cm, post: 50.6 ± 3.3 cm, d = 0.1) after the training intervention. No changes occurred in SJ height or Pmax. The effect of prestretch on jump performance was also reduced from 9.2 ± 7.2% to 5.7 ± 5.0% (p = 0.05) after training.
Countermovement jump height (−4.2 ± 2.1 cm, −8.4 ± 4.2%, p = 0.0002, d = 1.2) and Pmax (−2.7 ± 2.4 W·kg−1, −4.7 ± 4.3%, p = 0.007, d = 0.6, n = 5) were reduced acutely by the BJ90. However, when the fatigue-induced performance decrements were compared pre- and post-intervention, there was no significant effect of training either in terms of CMJ jump height (Table 3) or CMJ Pmax (Table 4). Comparison of the metabolic character of the BJ90 and references from the previous publications on actual ski runs are displayed in Table 5.
The main goal of this study was to assess training-induced effects of a short HIT block and their consequences on BJ90 performance and metabolism. After an 8-day HIT block, comprising 10 sessions, cycling V[Combining Dot Above]O2max and POmax were significantly improved in junior development alpine skiers. However, in contrast to our hypothesis, we observed neither an increase in aerobic energy production nor an improvement in performance in the BJ90 after training. Similarly, the degree of muscular fatigue attributable to the BJ90, assessed by comparing single CMJ immediately before and after the test, did not appear to be affected by training.
The 4.3% improvement in V[Combining Dot Above]O2max was less than that observed by Breil et al. (3) after their 15-session, 11-day HIT block; however, considering to the number of HIT sessions performed, the effects appear to agree (0.43% per session in this study, compared with 0.5%). Nonetheless, unlike subjects in this study, the 9 male subjects in the study of Breil et al., (3) who increased V[Combining Dot Above]O2max by 7.5%, significantly improved BJ90 performance (pre 93 ± 6 jumps, post 97 ± 3 jumps, p ≤ 0.05). Thus, it is possible that the present intervention was not strong enough to affect aerobic energy contribution, fatigue, or performance in the BJ90. However, another explanation for the unchanged aerobic energy contribution, despite improved aerobic capacity, could be the more conservative even-paced strategy that the athletes autonomously adopted in posttesting (2 fewer jumps in the first 30 seconds). Indeed, it has been shown that a fast-start or all-out pacing (adopted by the present subjects in pretesting) increases O2 consumption in the first 2 minutes of high-intensity exercise and enhances exercise tolerance (2,13). Inversely, an even-paced approach, more similar to that adopted in posttesting in this study, increases the accumulated oxygen deficit (13) and reduces the aerobic contribution to total energy production (2). Thus, our subjects could well have inadvertently masked a training-induced improvement in their capacity for aerobic energy provision or indeed for a performance improvement (instead, both remained the same) by changing their pacing strategy. It is also possible that systemic exhaustion after the GXT was greater in posttesting (indicated by higher maximal BLa).
Regarding the unchanged effects of the BJ90 on CMJ parameters, we recognize that with only the subgroup of 5 subjects, statistical power was low; indeed, the probabilities of accepting a false null hypothesis were 92 and 75% for jump height and Pmax, respectively (analysis performed post hoc with PASS 11 software; NCSS, LLC, Kaysville, UT, USA). Thus, relatively small effects, if real, could have easily been overlooked.
In addition to the main findings, metabolic measures which characterize the BJ90 were obtained in this study. These data confirm the test's practicality for simulating the physiological demands of ski racing. Indeed, especially comparable with the technical events, the test demands good bilateral coordination, explosive leg power, and large amounts of eccentric leg work, as well as near maximal aerobic and anaerobic energy production. Physiological data from this study compare well with data gathered elsewhere for the BJ90 (1) and during actual race-like skiing (Table 5). Although calculations for energy turnover and the aerobic proportion of energy production differ from the cited studies, differences are most likely because of shorter runs and different calculation methods used elsewhere (18,22,23). Indeed, our data suggesting that 63 ± 3% of energy comes from aerobic sources in the 90-second test correspond very well to the expected value for maximal exercise of this duration (8,14). Moreover, peak V[Combining Dot Above]O2 was similar to measurements during skiing.
This study shows that a compact 8-day training block, comprising 10 high-intensity 4 × 4–minute interval sessions, improves V[Combining Dot Above]O2max in elite junior alpine skiers with relatively similar effectiveness as other block concepts. Considering the many other time-demanding components of skiers' conditioning, this sort of compact and specific high-intensity training block is a time-efficient way to improve their aerobic capacity. Additionally, the study employed a mix of training modes during the interval sessions, which may reduce training monotony during the block. Moreover, this study provides important physiological data characterizing the BJ90, showing that this indoor performance test mimics the metabolic demands of ski racing quite well.
The authors thank the Swiss Olympic Committee for partially funding this project and the coaches at the Nationales Leistungszentrum in Engelberg for their cooperation.
1. Andersen RE, Montgomery DL. Physiology of Alpine skiing
. Sports Med 6: 210–221, 1988.
2. Bishop D, Bonetti D, Dawson B. The influence of pacing strategy on VO2 and supramaximal kayak performance. Med Sci Sports Exerc 34: 1041–1047, 2002.
3. Breil FA, Weber SN, Koller S, Hoppeler H, Vogt M. Block training periodization in alpine skiing
: Effects of 11-day HIT on VO2max and performance. Eur J Appl Physiol 109: 1077–1086, 2010.
4. Brown SL, Wilkinson JG. Characteristics of national, divisional, and club male alpine ski racers. Med Sci Sports Exerc 15: 491–495, 1983.
5. Busso T, Chatagnon M. Modelling of aerobic and anaerobic energy production in middle-distance running. Eur J Appl Physiol 97: 745–754, 2006.
6. Chatagnon M, Busso T. Modelling of aerobic and anaerobic energy production during exhaustive exercise on a cycle ergometer. Eur J Appl Physiol 97: 755–760, 2006.
7. Cormack SJ, Money MM, Morgan W, McGuigan MR. Influence of Neuromuscular fatigue
on accelerometer load in elite Australian football players. Int J Sports Physiol Perform 8: 373–378, 2013.
8. Gastin PB. Energy system interaction and relative contribution during maximal exercise. Sports Med 31: 725–741, 2001.
9. Heikkinen D. Physical Testing Characteristics and Technical Event Performance of Junior Alpine Ski Racers. Master's Thesis, Graduate School, University of Maine, May, 2003.
10. Helgerud J, Hoydal K, Wang E, Karlsen T, Berg P, Bjerkaas M, Simonsen T, Helgesen C, Hjorth N, Bach R, Hoff J. Aerobic high-intensity intervals improve VO2max more than moderate training. Med Sci Sports Exerc 39: 665–671, 2007.
11. Heubert RA, Billat VL, Chassaing P, Bocquet V, Morton RH, Koralsztein JP, di Prampero PE. Effect of a previous sprint on the parameters of the work-time to exhaustion relationship in high intensity cycling. Int J Sports Med 26: 583–592, 2005.
12. Jackson AS, Pollock ML. Generalized equations for predicting body density of men. Br J Nutr 40: 497–504, 1978.
13. Jones AM, Wilkerson DP, Vanhatalo A, Burnley M. Influence of pacing strategy on O2 uptake and exercise tolerance. Scand J Med Sci Sports 18: 615–626, 2008.
14. Laursen PB. Training for intense exercise performance: High-intensity or high-volume training? Scand J Med Sci Sports 20(Suppl. 2): 1–10, 2010.
15. Märzendorfer PJ. Reliability of EPOC-O2 deficit relationship and total energy consumption during a 90-second supramaximal performance test & functional aspects and tolerability of six weeks beta-alanine supplementation. Thesis for Master of Science in Exercise Science, Swiss Federal Institute of Technology, Zurich, Switzerland, 2011.
16. Neumayr G, Hoertnagl H, Pfister R, Koller A, Eibl G, Raas E. Physical and physiological factors associated with success in professional alpine skiing
. Int J Sports Med 24: 571–575, 2003.
17. Rognmo Ø, Helgerud J, Hoff J. Aerobic Demands in Giant Slalom Skiing. Department of Sports Sciences, Norwegian University of Science and Technology, 2002.
18. Saibene F, Cortili G, Gavazzi P, Magistri P. Energy sources in alpine skiing
(giant slalom). Eur J Appl Physiol Occup Physiol 53: 312–316, 1985.
19. Stöggl T, Stieglbauer R, Sageder T, Müller E. High-intensity interval training
(HIT) and speed training in soccer. Leistungssport 40: 43–49, 2010.
20. Stolen T, Chamari K, Castagna C, Wisloff U. Physiology of soccer: An update. Sports Med 35: 501–536, 2005.
21. Storen O, Bratland-Sanda S, Haave M, Helgerud J. Improved VO2max and time trial performance with more high aerobic intensity interval training
and reduced training volume: A case study on an elite national cyclist. J Strength Cond Res 26: 2705–2711, 2012.
22. Veicsteinas A, Ferretti G, Margonato V, Rosa G, Tagliabue D. Energy cost of and energy sources for alpine skiing
in top athletes. J Appl Physiol 56: 1187–1190, 1984.
23. Vogt M, Puntschart A, Angermann M, Jordan K, Spring H, Müller E, Hoppeler H. Metabolic consequences of a competition-like slalom training session in junior alpine skiers. Leistungssport 35: 48–54, 2005.