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Repeated-Sprint Ability and Aerobic Fitness

Thébault, Nicolas1,2; Léger, Luc A1; Passelergue, Philippe2

Journal of Strength and Conditioning Research: October 2011 - Volume 25 - Issue 10 - p 2857-2865
doi: 10.1519/JSC.0b013e318207ef37
Original Research
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Thébault, N, Léger, LA, and Passelergue, P. Repeated-sprint ability and aerobic fitness. J Strength Cond Res 25(10): 2857–2865, 2011—The purpose of this study was to reinvestigate the relationship between aerobic fitness and fatigue indices of repeated-sprint ability (RSA), with special attention to methodological normalization. Soldiers were divided into low (n = 10) and high (n = 9) fitness groups according to a preset maximal aerobic speed (MAS) of 17 km·h−1 (∼60 ml O2·kg−1·min−1) measured with the University of Montreal Track Test (UMTT). Subjects' assessment included the RSA test (3 sets of 5 40-m sprints with 1-minute rest between sprints and 1.5 minutes between sets), a 40-m sprint (criterion test used in the computation of fatigue indices for the RSA test), strength and power measurement of the lower limbs, and the 20-m shuttle run test (20-m SRT) and the UMTT, which are measures of maximal aerobic power. The highest correlation with the RSA fatigue indices was obtained with the 20-m SRT (r = 0.90, p = 0.0001, n = 19), a test with 180° direction changes and accelerations and decelerations. The lower correlation (r = 0.66, p < 0.01, n = 19) with the UMTT (continuous forward running) suggests that some aerobic tests better disclose the importance of aerobic fitness for RSA and that aerobic power is not the sole determinant of RSA. However, neither strength nor vertical jumping power was correlated to the RSA fatigue indices. Subjects with greater MAS were able to maintain almost constant level of speed throughout series of repeated sprints and achieved better recovery between series. A MAS of at least 17 km·h−1 favors constant and high speed level during repeated sprints. From a practical point of view, a high aerobic fitness is a precious asset in counteracting fatigue in sports with numerous sprint repetitions.

1Department of Kinesiology, University of Montreal, Montreal, Canada; and 2Sports Performance Analysis Laboratory, Department of Sports Sciences, University of Pau, Tarbes, France

Address correspondence to Nicolas Thébault, nicolas.thebault@umontreal.ca.

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Introduction

Repeated-sprint ability (RSA) or the ability to repeat short bouts of sprints (40–60 m or 5–8 seconds) with minimal recovery and fatigue between those is an important asset in team sports (37). Understanding its limiting factors is also important. This study focuses on the importance of aerobic fitness for RSA. The article also focuses on the importance of standardizing both the RSA testing protocols and derived Fatigue indices scores and the aerobic protocol and scores as well to get proper results as will be demonstrated by our results.

Repeated-sprint ability and aerobic fitness are 2 general concepts. Each one needs to be operationalized through a protocol and a score value that quantify the results (Figure 1). Obviously, the correlations obtained between RSA and aerobic fitness depend on the protocol and the score formula used on each side of the comparison.

Figure 1

Figure 1

Thus, it is not surprising that some authors suggest no relationship between aerobic fitness and the capacity to perform intermittent high-intensity exercises (1,3,4,9,38), whereas others have demonstrated high correlations between these 2 variables (5,22,33). This issue is important, and we intend to demonstrate that the lack of correlation between RSA fatigue indices and aerobic fitness is because of improper RSA protocol (not enough sprints) or improper aerobic criterion test to compare with because physiological and metabolic responses to repeated-sprint activities are influenced by types of exercise protocols (exercise mode, sprint duration, number of sprint repetitions, recovery time, and training status) (37). In most sports, the increasing fatigue observed toward the end of the game, occurs after many more sprints than the number of sprints (∼5) used in many protocols that measure RSA. Thus, this study investigates and proposes the use of a larger number of sprints and the use of longer and active rest intervals of an exercise protocol that assess RSA. Furthermore, in a game situation, sprints are rarely done with a unique constant work/rest (W/R) ratio. It appears justified to reinvestigate the role of aerobic fitness on RSA using 3 series of 5 × 40 m sprints (with 1-minute rest between sprints and 1.5-minute rest between sets) to somewhat mimic what is happening in sports such as rugby with 4 second/30–80 second W/R ratio (34) or 1/6 to 1/28 W/R ratio (13).

Besides the RSA protocol (Figure 1), the formula used to calculate the fatigue index may also affect the correlation between RSA and aerobic fitness. Attempts to use conventional indices (17) did not yield consistent results with our RSA protocol. Thus, 2 different fatigue indices were developed and calculated for each block of 5 sprints and for the 3 blocks together. The first objective of this study is dual: (a) to compare how these 2 fatigue indices correlate to aerobic fitness and (b) to demonstrate that the importance of aerobic fitness on RSA fatigue indices will increase with the exercise duration or from block 1 to block 2.

The second objective was to determine whether an aerobic testing protocol that is more specific to the RSA exercises would yield better correlation between these 2 variables. Thus, aerobic fitness was measured using 2 different multistage running field tests with (28) and without (25) changes of direction, instead of a less specific laboratory test because it is well known that O2peak values are specific to the muscles used and the type of activity used by subjects in their training regimen (30).

A third objective was to see if the importance of aerobic fitness for RSA was the same in subjects with low and high aerobic fitness. The fourth and last objective was to compare the importance of aerobic fitness on RSA fatigue indices to other aspects of fitness such as muscular strength and power.

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Methods

Experimental Approach to the Problem

To demonstrate the relation between RSA fatigue index and various fitness attributes, the subjects were tested in 4 different sessions with at least 3-day rest in between in the following order:

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Session 1

Criterion sprint time to determine the maximal sprinting speed. This value is used to see the importance of sprinting velocity for the RSA. It is also used to standardize the computation of our RSA fatigue indices.

Multistage aerobic 20-m shuttle run test (28). This test is 1 of the 2 aerobic field tests used to see the importance of aerobic fitness for RSA.

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Session 2

The RSA test. The decrease in velocity of repeated sprints is used to compute 2 different fatigue indices that will be used to establish the importance of all other fitness variables on RSA.

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Session 3

Determination of maximal isometric strength of the quadriceps, vertical squat jump, and countermovement jumps with and without extra load. These muscular tests are also to see their importance for RSA as compared to the 2 aerobic fitness tests.

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Session 4

Multistage aerobic track test with no direction change (25). This is the second, less specific, aerobic field test used to demonstrate the importance of aerobic fitness on RSA. We expect to demonstrate that the less sport-specific protocol is less correlated to RSA than the more specific one.

Another important issue in our experimental approach is the fact that our subjects were also divided in 2 aerobic fitness groups (below and above 17 km·h−1in the multistage aerobic track test) to demonstrate that the relation between RSA and aerobic fitness depends on the aerobic fitness levels of the subjects.

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Subjects

Nineteen healthy and active adult male soldiers with an average estimated O2max of 58 ± 3.5 ml·kg−1·min−1 (25,27) from the Pau Air Base in France were recruited for this study (Table 1).

Table 1

Table 1

All subjects were paratroopers with at least 5 years of experience and were regularly engaged in fitness programs as part of their duties. The tests were done in October outside for the Maximal Aerobic Track Test (no rain and temperature around 20° C) and within an open wall gymnasium for the other tests (∼20° C also) in the morning approximately at the same time of the day. No nutrition and hydration control was made during this study, but subjects were asked to avoid excessive exercise or behavior the day before the testing. None was formerly engaged in a diet regimen or in activities that may cause excessive dehydration or any other impairment that could seriously affect our results, particularly when subjects with maximal aerobic speed (MAS) below and above 17 km·h−1 are compared, 17 km·h−1 being equivalent to 59.5 ml·kg−1·min−1 (27). All subjects were informed of the experimental risks and signed an informed consent document before their participation. All procedures were approved by a university-based Institutional Review Board for the use of human subjects before data collection.

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Procedures

Maximal Aerobic Power

Maximal aerobic speed was measured using 2 field tests: The University of Montreal maximal multistage running track test (25) and the Léger 20-m shuttle run test that is characterized by numerous acceleration and deceleration phases (26,28). We anticipated better correlation between fatigue resistance and results on the semispecific 20-m shuttle run test. Maximal aerobic speed (km·h−1) was obtained from the running track test and was used to predict O2(ml·kg−1·min−1) using the Léger and Mercier equation (27):

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Forty-meter Sprint Test

Maximal average speed on a 40-m sprint test with a 10-m run-up start was measured with photoelectric cells (Newtest, Oulu, Finland, www.newtest.com/and X SUNX EQ-34, Aichi, Japan, http://sunx.jp/en/products/photoelectric/eq-30/). Subjects completed 3 trials with 6 minutes of recovery in between; the best result was retained and served as the criterion measure to calculate the fatigue indices (see below).

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Maximal Isometric Strength

Isometric strength of the quadriceps was measured with 2 strength gauges (BIOPAC, Goleta, CA, USA, www.biopac.com/) fixed on the “leg extension” machine designed to train the quadriceps. For each leg, a sensor set perpendicularly to the machine base (fixed point) was also attached to the subject ankle (mobile part). Subjects sat with their back firmly attached to the seat at 110° and their knees were flexed at 90°. They were asked to maximally extend both legs at the same time after the tester's signal. Because each leg operated independently, we measured strength of each leg and the total strength of both legs combined. Data were analyzed with the ACKNOWLEDGE software (www.biopac.com/).

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Vertical Jumping Power Measures

Each subject performed squat jumps without extra load, countermovement jumps with and without extra load (20-kg barbell on the shoulders). The best of 3 trials was retained for each movement. A linear encoder (BIOPAC and ACKNOWLEDGE) provided us with the vertical jump height and the Lewis formula (36) was used to compute maximal power:

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Repeated-Sprint Abilility Test and Fatigue Indices

Subjects performed 3 sets of 5 40-m sprints using a 10-m run-up start with 1 minute between each sprint and 1.5 minutes between each set. After each sprint, subjects jogged back slowly to the starting line, put on a linear encoder (BIOPAC and ACKNOWLEDGE) fixed on a waist belt and performed 2 successive countermovement jumps before starting a new sprint.

A fatigue index was computed over the 15 sprints and on each one of the 3 blocks of 5 sprints yielding 4 fatigue index values. As seen in Figure 2, the sprint speed decreased from block to block and within each block. Also, the best sprint of each block was lower than the speed of our reference 40-m sprint. Two different fatigue indices were thus calculated to take into consideration the between-block fatigue (IF-1) and the within-block fatigue (IF-2). The IF-1 was obtained by dividing the average speed of each block and all blocks by the 40-m reference sprint speed, whereas IF-2 was obtained by dividing the difference between the best sprint speed of each block and the speed of the last sprint of each block by the maximal average speed for our reference 40-m sprint. The use of the 40-m reference sprint allowed correction for the subjects who tended to spread their energy over all the series instead of giving their maximal speed right from the first repetitions as it is often the case (37). Besides, our results did demonstrate strong correlations between the criterion maximal speed on single 40-m sprint and the average speed for each block of sprints and all the 15 sprints combined (r = 0.81–0.93).

Figure 2

Figure 2

Because the ability to repeat sprints may increase with MAS (23), these fatigue indices were also computed separately for highly fit and less fit subjects (MAS ≥ 17 vs. MAS < 17 km·h−1 or O2max ≥ 60 vs. O2max < 60 ml·kg−1·min−1) for the multistage track test.

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Statistical Analyses

Statistics were performed with SPSS software (USA, www.spss.com/). Simple and multiple correlations between each fitness test (aerobic indices and muscular ones) and the 2 fatigue indices were computed to see the respective strength of the link between each RSA fatigue index and each fitness or physiological variable or a combination of those. To be more specific, we believe that each fatigue index used in this study has a specific and different signification. In the same line of thinking, we also think that using a multiple regression to relate both fatigue indices to each aerobic fitness test would yield better correlation than the single correlations. As we shall see, that approach will demonstrate that aerobic fitness may be more important for RSA when different fatigue indices are combined. The nonparametric Wilcoxon test and analysis of variance (ANOVA) for repeated measures with Duncan post hoc tests were used to assess the significant differences between the criterion sprint velocity and any of the 15 sprints of the RSA protocol and to also assess differences between the first sprint of each block on one side and any subsequent sprint speeds within each block of 5 sprints. These analyses were done separately for the whole group and each 1 of the 2 subgroups of subjects (MAS < and >17 km·h−1). Both Wilcoxon test and ANOVA tests revealed similar significant differences between repetitions. A 2 way ANOVA (3 Blocks of sprints and 5 Sprints within a Block) for repeated measures was also done for all subjects groups. A 2-way ANOVA (sprint block and subject group for repeated measures on 1 factor was used to assess fatigue indices and speed differences between sprint blocks and subject groups. A unilateral unpaired t-test was also used to detect difference between subjects with MAS below and above 17 km·h−1 for each one of the 4 fatigue indices. Level of significance was set at p ≤ 0.05 in this study.

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Results

Except for the first block of sprints, the subjects with MAS >17 km·h−1 had better IF-2 than the subjects with MAS <17 km·h−1 (Table 2). Except for body weight and obviously for aerobic fitness (Table 1), no other biometric and fitness difference (p > 0.05) was found between the 2 groups of subjects. Compared to the speed of the first sprint (Figure 2), the average speed decreased from block to block and from the beginning to the end of the 15 sprints in both fitness groups and in the combined group (p < 0.001). The decrease in speed is also smaller (p < 0.03) in the fit group in the third block of sprints, whereas it is not in the less fit group (p > 0.05); this could also be seen from Figure 2 where the speed stays almost constant in block 3.

Table 2

Table 2

Except for the first block of sprints, both multistage aerobic field tests were well correlated with both FI, separately or altogether using multiple regression analysis (Table 4). A similar pattern was obtained using each IF separately, but the magnitude of the correlation was lower (Table 4). Although both multistage aerobic field tests were well correlated among themselves (Table 5), the 20-m shuttle run test with direction changes was better correlated with IF-1 and IF-2 (Table 4). The magnitude of the correlation between the 2 aerobic field tests and fatigue indices increases from the first to the last block of sprints (Tables 3 and 4). None of the neuromuscular variables was significantly correlated to any of the RSA fatigue indices. No decrease in performance was observed for the countermovement jumps done during the active rest intervals.

Table 3

Table 3

Table 4

Table 4

Table 5

Table 5

As expected, our results also demonstrated strong correlations between the highest criterion speed on single 40-m sprint and the average speed either during all 15 sprints combined or during the 3 separate blocks (0.90, 0.93, 0.97, 0.81, respectively, p < 0.01).

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Discussion

Our repeated-sprint test protocol was chosen to roughly mimic rugby type of play. This explains our choice of 3 sets of 5 sprints. With 1-minute rest between sets, subjects were able to achieve higher speed at the beginning of each block. For that reason, there was no regular decrease in speed over all the 15 repetitions. Furthermore, our subjects tended to save energy to counteract fatigue as can be seen from the first repetitions of each subset that was slower than our criterion maximal single 40-m sprint. As mentioned earlier, the fact that the maximal criterion speed was highly correlated to the average time of each one of the 3 sets of sprints supports that assertion. As expected, conventional fatigue indices (i.e., decrement in speed from the first sprint to the last one either expressed in % of the first sprint or as the decrement slope) were not appropriate and did not yield any significant correlations with fitness components (unreported results). This indicates that the choice of a formula to determine a fatigue index could be a very crucial point and could lead to false conclusions such as minimizing the role of aerobic fitness on RSA. With our RSA test made of 3 blocks of 5 sprints, it can be clearly seen that speed decreases from block to block and within a block (Figure 2). Two different kinds of fatigue indices were thus necessary to quantify these phenomena, and the fact that the 2 fatigue indices altogether yielded better correlation with the 20-m shuttle aerobic test than each one of these 2 fatigue indices taken separately (r = 0.90 vs. r = 0.71 and −0.84, Table 4) indicates that each fatigue index measure a different aspect of RSA.

Our RSA fatigue indices were well correlated to the performance of both aerobic field tests. As expected however (30,37), the correlations were better for the semispecific 20-m shuttle run test (Table 3). Furthermore, when computed on each set of sprints, the fatigue indices were significantly correlated only on the last 2 sets of sprints (Tables 3 and 4). Thus, the role of aerobic capacity to counteract fatigue may be more important only after a certain number of sprints or eventually toward the end of a given sport game. In this line of thinking, studies that reported nonsignificant correlation between aerobic fitness and RSA are often based on only 5 or 6 repetitions (1,3,6,12) and could be misleading because that number of repetitions is not representative of what is occurring in most intermittent sports. When the number of sprints was sufficient (>10) however, aerobic fitness seemed important (8,22) except in 1 study (35). However, in the latter case, the subjects were too homogeneous (O2max = 53 ± 2 ml·kg−1·min−1) to expect any significant correlation.

As fatigue becomes more important with repetitions, the aerobic energy sources may also become more important in resynthesizing phosphocreatine (PCr) stores both during sprints and recovery time may explain this phenomenon, whereas anaerobic glycolysis appears to be less involved (2,7,14,31). Furthermore, the amount of oxidative fibers is better correlated to the capacity to repeat sprints as opposed to the percentage of fast-twitch fibers because of the importance of recovery between each work interval during team sport games (10).

Although we attempted to mimic rugby with our RSA protocol, we did not test rugby players. Our results are however supported by the work of Maso et al. (29) who found that the lighter back ball carriers of the national French rugby team had better O2max estimates (same track test as ours) than heavier line forwards (61.1 and 54.8 ml·kg−1·min−1, n = 10 + 10) and also better covered distance in an RSA test made of 6 repetitions of a 30-second shuttle run sprint (35-second rest) on a shuttle run course of increasing distance in 5-m multiples (755 and 736 m, n = 10 + 10). In that respect, McLean (32) reported that blood lactate rarely exceeded 9.8 mmol·L−1 during games of first league division in Scotland, indicating, again, a possible role for aerobic capacity to counteract acidosis. A blood lactate value of 8.5 mmol·L−1 has also been reported by Maso et al. (29).

We also know that fatigue is correlated to the concentration of free inorganic phosphate (Pi) that affects muscular contraction by blocking calcium ions release from the sarcoplasmic reticulum when pH increases after adenosine triphosphate (ATP) hydrolysis (39,40). Rapid resynthesis of PCr and Pi caption linked to aerobic energy delay muscular fatigue and increases the capacity to repeat high-intensity sprints.

In most studies, including ours, aerobic fitness corresponds to O2max, maximal aerobic power or MAS as measured during laboratory or field test. But aerobic fitness is more than just maximal aerobic power. In this regard, Dupont et al. (11) reported that a shorter time constant for the fast component of O2 kinetics (r = 0.80) was a better indicator of RSA than O2max itself (r = 0.71).

The importance of aerobic fitness for RSA is further demonstrated by the fact that subjects with MAS >17 km·h−1 had better IF-2 than subjects with MAS below 17 km·h−1 (Table 2). Compared to subjects with MAS < 17 km·h−1, those with MAS > 17 km·h−1 also showed much less decrease in sprint speed during the RSA test, particularly during the last block of sprints (Figure 2). This suggests that an MAS around 17 km·h−1 or a O2max of 60 ml·kg−1·min−1 may be a critical value to achieve in team sports such as rugby, at least for the lighter back ball carriers.

Even if our 17 km·h−1 cut-off was chosen arbitrarily by splitting the group into 2 and had no a priori particular meaning, it is interesting to note that this cut-off yielded mean MAS values of 15.5 and 17.6 km·h−1 for the low and high fit groups of our study (Table 1), values that are almost identical to the ones reported for the heavier line forwards and lighter back ball carriers of the French national rugby team (29). These results are in agreement with those of Hamilton et al. (22) who observed that endurance athletes have a lower decrease in performance than do team sport athletes (−4.2 vs. −10.0%) while repeating 10 sprints of 6 seconds with a 30-second recovery in between.

The importance of aerobic fitness is not supported in all studies. The way RSA exercises are done may sometimes explain those discrepancies. In some of the studies, the W/R ratio was often around 6/24 seconds (1 sprint every 30 seconds), which may also decrease the importance of aerobic fitness, although such a ratio is not often seen in most intermittent game sports. The recovery length between sprints also affects RSA (7). With sufficiently long recovery, RSA is dependent on muscle ATP and on PCr depletion and resynthesis during recovery phases, which, in turn, is limited by lack of oxygen (15,24,42). If recovery is too short to allow PCr repletion, the contribution of anaerobic glycolysis is increased as reflected by higher lactate levels (20).

In our study, we introduce a new kind of RSA protocol and also 2 new fatigue indices. Although we did not measure the reliability of these new fatigue indices–RSA combinations, Fatigue indices and RSA tests are quite common and generally show no familiarization particularly when running is involved and when the rest intervals are strictly controlled whether the length or the time and the number of sprints and rest intervals are small or large (16,21,41). Coefficient of variation (CV) and intraclass correlation coefficient (ICC) are generally quite good ranging from 1.34 to 2.24% for CV and from 0.79 to 0.94 for ICC (16,18,19,41). If these new fatigue indices were not reliable, they could not be well correlated with aerobic fitness variable as we found in this study.

Concerning the strength and muscular power variables, no significant difference was observed between the 2 fitness groups (Table 2), and no significant correlation was seen between fatigue indices (Table 3) and aerobic fitness tests (Table 5). Vertical jumping power was calculated using the Lewis formula, but we obtained similar correlations (n.s.) using Sayers' prediction power formula (36) as expected from almost perfect correlation between these formulae (36). Therefore, performing repeated sprints differs from performing a single sprint.

The statistical approach used in this study does not establish a causal link between aerobic power and RSA. The importance of aerobic power for RSA is based on logical deductions from physiological knowledge and on the fact that the correlation link between the 2 variables is quite strong. A more definitive causal and effect link would be to traine and improve aerobic fitness of subjects and to demonstrate that aerobic improvement is significantly correlated to RSA improvement.

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Practical Applications

Repeated sprint ability tests are commonly used to measure fitness of team sport athletes. There is however a need to standardize the tests and to make those more specific to the sport. The common 5-rep test is surely not a typical performance encountered in most team sports. With a more specific test, this study has demonstrated without a doubt a strong link between aerobic power and RSA. Thus, team sports requiring repetitions of high-intensity sprints should not neglect the development of aerobic capacity in favor of exclusive anaerobic and muscular training. Our results indicate that the capacity to counteract fatigue after many sprints is much better in subjects with MAS >17 km·h−1. This suggests that team sport athletes with an MAS of at least 17 km·h−1 or a predicted O2max of at least 60 ml·kg−1·min−1 would benefit more from their aerobic capacity. In addition, our study shows that aerobic fitness may be more important to counter fatigue as the game goes on because the correlation of fatigue indices and aerobic fitness was significant only for the last 2 sets of 5 repetitions. That may also negate conclusions from previous studies that stated that aerobic fitness was not important in intermittent sports, especially because results were derived from 5 sprint repetitions only. Finally, with the type of RSA protocol used in this study (W/R ratio of ∼5.5/60 seconds with 10–15 repetitions or more), our results are particularly relevant to sports such as rugby. To be meaningful, RSA tests and fatigue indices computed from the results of the RSA protocols need to be normalized. More specifically, the number and duration of sprints must mimic as much as possible the type of action observed in competition. The fatigue index is just a simple mathematical value that describes the fatigue occurring during the RSA protocol. However, the formula used to compute a fatigue index needs to reflect the observed decrease in sprint performance during the RSA protocol. As a summary, coaches need to keep in mind that (a) Aerobic training is important in team sports where fatigue tends to increase after many sprints repetitions or toward the end of the game, and (b) Proper and specific RSA and Aerobic tests are necessary for the follow-up and physical training of team sport athletes.

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Acknowledgments

We would like to acknowledge the participation of the members of the Pau Air Force in France. More specifically, we would like to thank Warrant Officers Patrick Salé and Fabrice Morales whose kind collaboration has permitted the completion of this study. The authors have no undisclosed professional relationships with companies or manufacturers that would benefit from the results of this study. The results of this study do not constitute endorsement of the product by the authors or the National Strength and Conditioning Association.

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Keywords:

rugby; aerobic; muscular; power; strength; fatigue

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