In recent years, the use of repeated sprint tests (RSTs) has gained popularity among coaches and athletes as a method of evaluating repeated sprint ability (RSA) (e.g., [1,4,16]). Such tests involve repetitions of short sprints (mainly running and cycling), with variable short recovery periods between the sprints. Different protocols for this test consist, for example, of 8 to 10 5-second sprint repetitions starting every 30 seconds (1), six 40-m maximal sprints starting every 30 seconds (10), or twelve 20-m sprints starting every 20 seconds (30). The specific test protocol can be easily adapted to suit the specific needs and movement patterns of intermittent-type sports or activities. Therefore, RSTs are most commonly used in multisprint sports such as soccer, basketball, and hockey and have been reported to be both valid (5,14) and reliable (10,22).
It has been suggested that a high level of aerobic fitness is a prerequisite for greater performance during repeated-sprint activities (11,12,21). However, the correlation between V[Combining Dot Above]O2max and indices of RSA has been inconsistent. Although some authors have reported significant correlations between the 2 (e.g., [1,9]), others have failed to do so (e.g., ). Possible reasons for this inconsistency may be the use of different protocols, differences in the participants' fitness level, or the different exercise modes used in the various studies. Further research is required to investigate the relationship between aerobic fitness and RSA, especially using modes of exercise other than running or cycling.
To date, most repeated-sprint studies have employed running (1,16) or cycling (5,10) as the exercise mode. Although some studies have investigated the physiological responses of various types of sprint training in swimming (8,26–29), to the best of our knowledge, indices of RST have not been studied in swimmers. Indeed, one can argue that swimming is usually performed as a continuous single effort and therefore is not relevant to the intermittent type of activity performed during RSTs. However, intermittent swimming is performed in water polo, which, similar to other ball-games, is characterized by short bursts of physical activity separated by brief periods of rest (18,24). Repeated short duration sprints are also a widely used training method for increasing the anaerobic capacity of trained swimmers (15). In addition, it is of interest to coaches and researchers to examine the influence of a unique medium (e.g., water) on the physiological responses and the performance indices of RST.
The aim of this study, therefore, was to determine performance indices and physiological responses during RSTs in swimming, to compare these to previous similar running and cycling RSTs, and to examine their relationships to the best single short (100 m, as an index of anaerobic performance) and long-distance (2,000 m, as an index of aerobic performance) swimming results in a group of elite, national level, male swimmers. We were especially interested in swimming because of its unique environment and because, in contrast to running, many swimmers (at all levels) excel in both short and long distances. We hypothesized that swimming RSA would correlate with both short- and long-distance swim times (as indicators of anaerobic and aerobic capacity, respectively).
Experimental Approach to the Problem
The fitness and physiological requirements of repeated sprints have generated much interest among practitioners and researchers. Although practitioners are mainly interested in the association of various fitness attributes to different conditioning programs, researchers have shown that the ability to perform repeated sprints is related to both anaerobic attributes, such as muscle phosphocreatine degradation (6) or muscle buffer capacity (3), and aerobic qualities, such as maximal oxygen uptake (1,30). Moreover, coaches are interested in the simple associations between traditional field fitness and performance tests.
So far, RST studies have used mainly running or cycling as the activity mode to test these associations, whereas other activities, such as swimming, have not been used. Therefore, the RST protocol in this study (8 repetitions of a 15 m all-out sprint, separated by a 30-second rest interval) was chosen to match the duration, the number of repetitions, and the resting interval time of the typical running or cycling RST protocols used in previous studies (e.g., [1,3]). In addition, to compare physiological responses to typical running and cycling RSTs, we measured the heart rate (recorded immediately upon completion of each sprint), fingertip lactate level (measured 2 minutes after the completion of the RST), and rating of perceived exertion during the swimming RST.
To correlate the swimming RST performance indices with anaerobic and aerobic ability, we used the best 100-m swim time as an index of anaerobic performance, and the best 2,000-m swim time as an index of aerobic performance of the swimmers.
Twenty trained male swimmers (age 18.9 ± 4.0 years, height 179.6 ± 4.7 cm, body mass 73.7 ± kg) participated in this study. Standard calibrated scales and stadiometers were used to determine the height and body mass. All the participants had a background of at least 6 years of competitive swimming training, and competitive experience at an international level. A few of them participated in the previous European swimming championship (personal best results ranges: 100-m freestyle: 51–53 seconds, 400-m freestyle: 3:58–4:08 minutes, 800-m freestyle: 8:15–8:35 minutes). Testing sessions were performed upon completion of the preparatory training period, just before the beginning of specific training for the main competitive season. Therefore, at the time of testing, the participants were in a moderate physical shape but not at their peak performance ability. During this period, an average of 10 swimming sessions, 120 minutes each, was performed by the swimmers every week. The swimmers trained daily, covering distances of about 40–50 km·wk−1. Some training sessions included long interval swimming performed at a comfortable submaximal pace, whereas others included short repetitions performed at a fast, maximal, or close to maximal speed. In addition, the swimmers had 3–4 sessions of strength training every week that included mainly weight lifting of different forms. The swimmers were informed of the experimental procedures and signed an informed consent form. All the procedures were conducted in accordance with the standards of the Institutional Ethics Committee.
The participants performed 3 tests with a 4–5 days' break between each test. The first test consisted of a 100-m swim, the second consisted of a 2,000-m swim, and the third consisted of the swimming RST protocol. All 3 tests were performed in the afternoon, about 3 hours after lunch. All the participants had the same meal at the training complex dining room. The participants were also instructed to drink 500 ml of water 30 minutes before each testing session. None of the participants were taking any food supplements. The tests were conducted in 2 different indoor swimming pools: the 100- and the 2,000-m tests in a 50-m pool, and the RST in a 15-m pool. The water temperature was 26° C and the air temperature was 27–28° C during all tests. To prevent the effects of fatigue on the study results, the swimmers were instructed to avoid intense activity 24 hours before each test. Before each test, the swimmers performed a standard warm-up that included an 800- to 1,000-m swim and 4 × 15-m sprints, and then rested about 15 minutes before starting the test. An electronic timing system (Omega RS 21, Vill, Switzerland), with an accuracy measurement of 1/1,000 seconds, was used for time recording during each swim. The front crawl swimming style was used in all tests.
All the swimmers completed 8 repetitions of a 15-m all-out sprint (8 × 15 m), each separated by a 30-second rest interval. The swimmers started each sprint in the water with a 2-legged push away from the wall. The swimmers were instructed to start swimming immediately after the feet disengaged from the wall and to avoid diving under the water, as usually occurs when jumping off starting blocks. During the rest periods between the sprints, the swimmers swam back slowly to the starting point at an intensity corresponding to about 50% of their maximal 100-m speed. This speed was familiar to the swimmers, because they routinely used it for recovery during interval training sessions. This speed is also considered to be the slowest speed possible with the use of a proper swimming technique (28). After returning to the starting point, the swimmers took the starting position for the next sprint.
The heart rate was recorded immediately on the completion of each sprint using a Polar heart rate monitor (Polar Accurex Plus, Polar Electro, Woodbury, NY, USA). Blood lactate was taken from a fingertip 2 minutes after the completion of the RST using a portable lactate analyzer (Accusport, Boehringer Mannehein, Germany). Rating of perceived exertion (RPE) was determined using the modified 1–10 (1 being the easiest and 10 the hardest) Borg scale (7) immediately upon the completion of the RST.
The 3 measures of the RST were the ideal swim time (IS), the total swim time (TS) of the 8 sprints, and the performance decrement (PD) during the test. Ideal sprint time was calculated as the fastest 15-m swim time multiplied by 8. The total sprint time was calculated as the sum of all sprint times. Performance decrement was used as an indication of fatigue and was calculated as ([TS/IS] × 100) − 100 (10). The test-retest reliability of running the RST was found to be 0.942 for total running time and 0.75 for PD (14,17,23).
The 100- and 2,000-m swim trials were performed according to official competition rules to determine the best performance time for these distances. The swimmers started each trial jumping off starting blocks into the water. To simulate competitive-like conditions, the swimming trials were performed with groups of 4–5 participants according to the swimmers' personal records and current fitness level.
Pearson linear correlation analysis was used to evaluate the relationships between each of the RST indices (IS, TS, and PD) and the 100- and 2,000-m swimming times. Pearson correlation was also used to evaluate the relationship between the 100- and 2,000-m times. In addition, we performed a multiple hierarchical regression between the 100- and the 2,000-m times with the 3 indices of the RST. Statistical significance was set at p ≤ 0.05. Data are presented as mean ± SDs.
The participants' physiological responses (heart rate and blood lactate concentration), RPE, 100- and 2,000-m swim times, and performance indices from the swimming RST are presented in Table 1.
The relationships between the RST performance indices and the times in the 100-m swimming trials were not significant (Table 2). The relationships between the RST performance indices and the times in the 2,000-m swimming trials were also not significant (Table 2). In contrast, there was a strong correlation between the 100- and 2,000-m swim times (r = 0.74, Figure 1). In addition, we performed a multiple hierarchical regression between the 100- and 2,000-m times with the 3 indices of the RST (IS, TS, and PD). The results indicated that all together, the 3 RST indices contributed 36% of the variance of the 2,000-m swimming time. The 3 RST indices had no significant contribution to the 100-m swimming time (8%).
This study examined the relationships between aerobic swimming performance (measured by 2,000-m swim time) and anaerobic swimming performance (measured by 100-m swim time), and the performance indices of an 8 × 15-m swimming RST. The correlations between the RST performance indices and both the 100- and 2,000-m swimming results were not significant. Although the test measures RSA, when all 3 indices of the test were combined in a multilinear regression analysis, they showed a significant contribution (36%) to the 2,000 m but not to the 100-m swim time. Interestingly, we found a strong significant correlation (r = 0.74) between the 100- and 2,000-m swim times among the study participants (Figure 1).
This study describes performance indices and physiological responses of an 8 × 15-m swimming RST. The total sprint time, the number of repetitions, and the length of the rest interval of the present swimming RST protocol were chosen to resemble typical running and cycling RST protocols. These variables are also similar to the movement patterns that characterize typical water polo games (18). Although total sprint time and ideal sprint time depend on the specific RST protocol (length and number of repetitions), the PD value that was found in the present swimming study (4.7%) is similar to PD values (4–6%) that have been reported in previous running or cycling RST studies (e.g., [1,22]).
Despite similar PD values, the physiological responses after the swimming RST were lower than the responses to a typical running or cycling RST. The mean peak heart rate after the present swimming RST (168 b·min−1) was lower than, for example, that after a 12 × 20-m (184 b·min−1) or a 6 × 40-m (179 b·min−1) running RST in trained soccer players (16). The lower heart rate during swimming might be the result of the horizontal swimming position (19), the cooling effect of the water, or the smaller recruited muscle mass (20). It is also possible that because maximal heart rate in the water is reduced, the relative heart rate response to the swimming RST is not different than in running or cycling RST (unfortunately, maximal heart rate in the water was not determined in the participants of this study). The mean peak blood lactate level after the present swimming RST (5.5 mmol·L−1) was also lower than the level found in previous running (10–14 mmol·L−1) (16) or cycling (9–12 mmol·L−1) (10) RST. In line with this, blood lactate concentration was found to be as low as 3 mmol·L−1 after forty 25-m swims at a 100-m race pace in highly trained swimmers (13). Once again, the lower lactate values are likely, at least partially, attributed to the recruitment of a smaller muscle mass during swimming.
In contrast to our hypothesis, we found no significant relationships between the 2,000-m time (an index of aerobic performance) and the RST indices. However, using a multiple regression model, we found that all 3 indices of the RST contributed 36% of the variance of the 2,000-m swim time. These findings are in line with the nonsignificant to low correlations (0.42 < r < 0.56) that were reported between V[Combining Dot Above]O2max and performance indices in some running and cycling RST studies (1,16,30). Nevertheless, the correlation values reported in these studies involving running or cycling exercise, and these in the present swimming study, are lower than might be expected. For example, it has been documented that the resynthesis of phosphocreatine and the recovery of sprint performance are controlled by the rate of oxidative metabolism within the muscle (6,25), which suggests that aerobic fitness (as assessed by V[Combining Dot Above]O2max) might be highly related to performance restoration and to total power during repeated maximal exercise. However, the absence of stronger correlations between V[Combining Dot Above]O2max and RSA may be related to the belief that the primary factor limiting V[Combining Dot Above]O2max is the ability of the cardiorespiratory system to deliver oxygen to the exercising muscle (2), whereas PCr resynthesis may be primarily determined by peripheral muscle factors (e.g., mitochondrial function). It has also been previously pointed out that factors other than V[Combining Dot Above]O2max are important for the total work score and the recovery of power output during repeated sprints. For example, Bishop et al. (3) suggested that the ability to buffer H+ may be a more important determinant of repeated sprint performance than V[Combining Dot Above]O2max. It has also been suggested that the restoration of power output during repeated sprints may be influenced by the distribution of muscle fibers, the level of the lactate threshold, and the duration of the recovery period between sprints (25).
This study also failed to find any significant relationships between 100-m swim times (an index of anaerobic performance) and the RST performance indices, even when combined in a multilinear regression model. This is in contrast to a previous study that reported significant correlations between RST performance indices and anaerobic power (9). A possible explanation for this discrepancy is that although Dawson et al. (9) used short anaerobic tests (10- and 40-m running time, lasting <10 seconds), the 100-m swim time that was used in this study lasted about 56 seconds. Thus, although further research is required, RSA (in both swimming and running) may be more strongly correlated with “anaerobic power” (all-out tests lasting <10 seconds) than with “anaerobic capacity” (all-out tests lasting 30–60 seconds). This could be assessed in future research by correlating the performance indices derived from the current RST protocol with a 25-m sprint time. It is also possible that stronger correlations might be found if different RST protocols, such as these with longer sprint intervals, are used. The short RST intervals (15 m) were chosen in the present swimming study for comparison with common sprint duration in previous running or cycling RST studies and also to better reflect water polo swimming characteristics.
We did, however, find a strong significant correlation (r = 0.74) between the 100- and 2,000-m swim times. This phenomenon may result from the similarity of training regimens among all swimmers, regardless of the event specialty and their possible influence on individual performance (all the swimmers in this study performed heavy aerobic training of 40–50 km·wk−1). In addition, although not determined in this study, swimming times are largely affected by swimming technique and by the swimmers' size (particularly limb length) (15). These may, at least partially, mask metabolic differences between swimmers, enabling technically skilled and tall swimmers to excel at all swimming distances. These relationships are unique for swimming, and this assumption can be supported by the past records of top world class-swimmers such as Ian Thorpe (world record holder in 100-m relays and individual 200, 400, and 800 m) and Grant Hackett (world record holder in 200-m relays and individual 400, 800, and 1,500 m), and others who excel in both short and long swimming distances. A similar phenomenon is very uncommon among runners. To the best of our knowledge, this relationship between short- and long-distance swimming performances has not been reported previously in the scientific literature.
In summary, no significant correlations were found between the 100-m swim time and the 8 × 15-m RST performance indices. Similarly, no significant correlations were found between the 2,000-m swim time and the 8 × 15-m RST performance indices. A strong correlation was found between the 100- and the 2,000-m distance swimming performances among elite male swimmers.
Physiological responses to swimming RST are lower than similar typical running and cycling RST.
The lack of correlations between the short- or the long-distance swimming times and the 8 × 15-m RST performance indices indicates that RSA in swimmers is a specific entity that cannot be used as indicator of short- or long-distance swim times.
The significant unique strong correlation between the 2,000- and 100-m swim times among elite swimmers may suggest that swimming times are largely affected by swimming technique and by the swimmers' physique. Therefore, coaches may consider these criteria for the selection of talented swimmers. It may also encourage coaches to focus more on technique-oriented training. Moreover, the strong correlation between short- and long-distance performance of the trained swimmers may reflect training regimens characterized by aerobic predominance. This raises the possibility that more specific training programs (in particularly for sprinters) may be needed for each swimming event, to improve the specific swimmer's physiological capacities.
The authors wish to thank all the swimmers and their coaches for taking the time and effort to participate in this study. No external financial support was received for the study.
1. Aziz AR, Chia M, Teh KC. The relationship between maximal oxygen uptake and repeated sprint performance indices in field hockey and soccer players. J Sports Med Phys Fitness 40–200: 195–200, 2000.
2. Bassett DR, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc 32: 70–84, 2000.
3. Bishop D, Edge J, Goodman C. Muscle buffer capacity and aerobic fitness are associated with repeated-sprints ability in woman. Eur J Appl Physiol 92: 540–547, 2004.
4. Bishop D, Lawrence S, Spencer M. Predictors of repeated-sprint ability in elite female hockey players. J Sci Med Sport 6: 199–209, 2003.
5. Bishop D, Spencer M, Duffield R, Lawrence S. The validity of a repeated sprint ability test. J Sci Med Sport 4: 19–29, 2001.
6. Bogdanis GC, Nevill ME, Boobis LH, Lakomy HKA. Contribution of phosphocreatine and aerobic metabolism to energy supply during repeated sprint exercise. J Appl Physiol 80: 876–884, 1996.
7. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 14: 377–382, 1982.
8. Buchheit M, Al Haddad H, Chivot A, Lepretre PM, Ahmaidi S, Laursen PB. Effect of in- versus out-of-water recovery on repeated swimming sprint performance. Eur J Appl Physiol 108: 321–327, 2010.
9. Dawson BT, Fitzsimons M, Ward D. The relationship of repeated sprint ability to aerobic power and performance measures of anaerobic work capacity and power. Aust J Sci Med Sport 25: 88–92, 1993.
10. Fitzsimons M, Dawson BT, Ward D, Wilkinson A. Cycling and running tests of repeated sprint ability. Aust J Sci Med Sport 25: 82–87, 1993.
11. Glaister M. Multiple-sprint work: Physiological responses, mechanisms of fatigue and the influence of aerobic fitness. Sports Med 35: 757–777, 2005.
12. Glaister M. Multiple-sprint work: Methodological, physiological, and experimental issues. Int J Sports Physiol Perform 3: 107–112, 2008.
13. Gullstrand L, Lawrence S. Heart rate and blood lactate response to short intermittent work at race pace in highly trained swimmers. Aust J Sci Med Sport 19: 10–14, 1987.
14. Impellizzeri FM, Rampinini E, Castagna C, Bishop D, Ferrari Bravo D, Tibaudi A, Wisloff U. Validity of a repeated-sprint test for football. Int J Sports Med 29: 899–905, 2008.
15. Maglischo E. Swimming Fastest. Champaign, IL: Human Kinetics, 2003.
16. Meckel Y, Machnai O, Eliakim A. Relationship among repeated sprint tests, aerobic fitness and anaerobic fitness in elite adolescent soccer players. J Strength Cond Res 23: 163–169, 2009.
17. Oliver JL. Is a fatigue index a worthwhile measure of repeated sprint ability? J Sci Med Sport 12: 20–23, 2009.
18. Platanou T. Cardiovascular and metabolic requirements of water polo. Serb J Sports Sci 3: 85–97, 2009.
19. Poliner LR, Dehmer GJ, Lewis SE. Left ventricular performance in normal subjects: A comparison of the responses to exercise in upright and supine positions. Circulation 62: 528–533, 1980.
20. Poul MB, McNaughton LR. The physiological responses to running and walking in water at different depths. Res Sports Med 11: 63–78, 2003.
21. Spencer M, Bishop D, Dawson B, Goodman C. Physiological and metabolic responses of repeated-sprint activities: specific to field-based team sports. Sports Med 35: 1025–1044, 2005.
22. Spencer M, Fitzsimons M, Dawson B, Bishop D, Goodman C. Reliability of a repeated-sprint test for field-hockey. J Sci Med Sport 9: 181–184, 2006.
23. Stewart AM, Hopkins WG. Consistency of swimming performance within and between competitions. Med Sci Sports Exerc 32: 997–1001, 2000.
24. Tan F, Polglaze T, Dawson B. Activity profiles and physical demands of elite women's water polo match play. J Sports Sci 27: 1095–1104, 2009.
25. Tomlin DL, Wenger HA. The relationship between aerobic fitness and recovery from high intensity intermittent exercise. Sports Med 31: 1–11, 2001.
26. Toubekis AG, Douda HT, Tokmakidis SP. Influence of different rest intervals during active or passive recovery on repeated sprint swimming performance. Eur J Appl Physiol 93: 694–700, 2005.
27. Toubekis AG, Peyrebrune MC, Lakomy HK, Nevill ME. Effects of active and passive recovery on performance during repeated-sprint swimming. J Sports Sci 26: 1497–1505, 2008.
28. Toubekis AG, Smilios I, Bogdanis GC, Mavridis G, Tokmakidis SP. Effect of different intensities of active recovery on sprint swimming performance. Appl Physiol Nutr Metab 31: 709–716, 2006.
29. Toubekis AG, Tsolaki A, Smilios I, Douda HT, Kourtesis T, Tokmakidis SP. Swimming performance after passive and active recovery of various durations. Int J Sports Physiol Perform 3: 375–386, 2008.
30. Wadley G, Le Rossignol P. The relationship between repeated sprint ability and the aerobic and anaerobic energy systems. J Sci Med Sport 1: 100–110, 1998.