Swimming performance has been reported to be dependent on the force and power produced by the swimmers, along with other factors (physiological, psychological, biomechanical) (3,26,36,37). Various dryland exercises have been used as predictors of swimming performance as well as to develop training adaptations and evaluate differences between swimmers (30). Although, strength has usually been measured through isometric and isokinetic tests, more recently, exercises that are commonly found in dryland strength training programs are being studied as predictors of swimming performance (8,30).
Upper-limb dryland strength exercises such as the lat pull-down or the bench press have been correlated with swimming power (7,10,15,29), with the lat pull-down being the exercise that best predicts swimming performance (7,29). The pull-up is another exercise that, like the lat pull-down, involves mainly the latissimus dorsi muscle (24,38), which is the main muscle activated during the swimming stroke (28). Confirming the apparent similarity between these 2 exercises, a significant correlation between the number of repetitions until muscular failure performed in the lat pull-down with the body mass and those of the pull-up exercise has been reported (35), as well as between the 1 repetition maximum (1RM) of both exercises (22). However, despite the correlation between the lat pull-down and swimming performance and the similarity between the lat pull-down and the pull-up exercise, to our knowledge, no previous study has analyzed the validity of the pull-up as a predictor of swimming performance.
The relationship between swimming performance and the lower-limb dryland strength—usually measured through the jump ability—is not clear, as some authors have reported a significant correlation (12,23,26), whereas others have not (15,29). These differences may be based on the inclusion of nonswimming elements such as the start and the turn-flip, as most studies find a relationship between jump ability and performance in nonswimming elements (14,33,43). It has been shown that the leg kick supplies 30% of the total forces produced during sprint swimming (31). Therefore, it would be interesting to study the influence of the lower-limb dryland strength on leg-kick performance—and accordingly in freestyle performance—when isolating the aforementioned nonswimming elements.
Taking into account the aforementioned influence of the strength of the upper and lower limbs on swimming performance, the main aim of this study was to analyze whether performance in common dryland exercises such as the pull-up and the countermovement jump (CMJ) could be valid predictors of swimming performance.
Experimental Approach to the Problem
To analyze the influence of dryland strength on swimming performance, participants presented themselves at the experimental facility on 2 subsequent days at the same time of day. On the first day, the strength of the lower limbs (CMJ tests) and freestyle swimming performance were assessed, and on the second day, the strength of the upper-limb (pull-up tests) and leg-only swimming performance were measured. In each session, the tests were separated by 1 hour and preceded by a 20-minute general warm-up.
Twelve young male swimmers ranging from 16 to 26 years old (19 ± 3 years, 180 ± 6 cm, 75 ± 10 kg, 15 ± 3% fat mass) volunteered to participate in this study. To ensure a homogeneous level of performance, the inclusion criteria were being men, being in the competitive period of their training program, competing at least at regional level and swimming 50-m freestyle in under 30 seconds in that moment of the season. A reduced sample size was included in this study as a consequence of the strict inclusion criteria.
The swimmers presented a homogenous level of performance (50-m freestyle: 26.41 ± 1.44 seconds, coefficient of variance: 5.5%) and competed at regional and national level. The number of hours per week of dryland strength training (3.3 ± 1.4 h·wk−1) and swimming training (14.4 ± 2.3 h·wk−1) in that moment of the season were registered before the experiments through personal interviews with the swimmers. For the duration of the study, subjects were instructed to maintain their normal dietary patterns as well as to refrain from doing intense exercise and from the consumption of ergogenic aids or stimulants during the 48 hours before each testing session. In agreement with the Committee of Ethics of the University of Alcalá, participants signed informed consent after having the procedures explained in verbal and written form. Signed parental or guardian consent was required when the participant was under 18 years old in addition to the signed consent of the subject.
Lower-Limb Strength Testing
The maximal power and the fatigue resistance of the lower limbs were determined through 2 different CMJ tests. The height of each jump was calculated from flight time through a photoelectrical contact platform (OptoGait Version 184.108.40.206, Microgait, Italy). Participants were instructed to try to reach the maximum height during each jump. During the CMJ, participants were instructed to place their hands on their hips while performing a downward movement to reach approximately 90° of knee flexion, trying to reach the maximum height in each jump. Subjects were also instructed not to flex their knees during the flight phase or the landing to avoid an overestimation of the flight time.
After a 20-minute warm-up that included 10 minutes of light jogging and 10 minutes of mobility exercises, subjects performed 5 CMJs separated by 1 minute of recovery. From the 5 CMJs, the highest and the lowest jumps were eliminated, and the mean height (CMJH) of the other 3 was calculated. After this CMJ test, participants recovered actively for 15 minutes and performed 30 CMJs separated by 2 seconds marked with an acoustic signal. The mean height (CMJMH) during this test and the relative loss—expressed as a percentage—between the mean height reached in the first and the last 15 jumps (CMJHL) were determined.
Upper-Limb Strength Testing
For the measurement of the maximal power and fatigue resistance of the upper limbs, 2 different pull-up tests were performed. Participants were required to start all pull-ups hanging from a bar with pronated grip and with their elbows fully extended, with pull-ups only considered correct if the participant reached the bar with his chin. Performance in the ascending phase of the pull-ups was recorded through a lineal force transducer (4010/4020e MuscleLab Version 7.18, Ergotest Innovation A.S., Norway) attached to the subjects' hips through a harness.
After the corresponding warm-up, each subject performed 5 pull-ups with a 1-minute rest between them. Participants were instructed to try to perform each pull-up as quickly as possible. As for the CMJH determination, the pull-ups that elicited the greatest and the lowest mean velocity values were eliminated, and the mean of the other 3 was calculated. The mean velocity (PUV), the absolute (PUAF) and relative force (PURF), and the absolute (PUAP) and relative power (PURP) were determined, as well as the peak velocity (PUPV) and the time to reach it (PUTpV). Then, 15 minutes later, participants performed all the pull-ups that they could until muscular failure (PUF), with each pull-up being preceded by an acoustic signal made by the researcher to ensure that all pull-ups were performed correctly. This test was considered concluded when the subject was not able to reach the bar with his chin. The number of correct pull-ups performed (PUFR), the mean velocity during the test (PUFV) and the relative loss of mean velocity between the first and the second half of the test (PUFVL) were determined.
One hour after the corresponding dryland strength tests, for the determination of swimming performance, participants swam a maximal 50-m freestyle on the first day and performed a maximal 50-m legs-only swimming using a kick board on the second day, both tests in a 50-m swimming pool. Whereas the 50-m freestyle test was initiated from the block and therefore included diving, the 50-m legs-only swimming was initiated from inside the water—the subject was not allowed to push the wall at the start—and finished when the kick board touched the opposite wall. Each test was preceded by a typical precompetition warm-up of approximately 1,000 m.
The beginning of the tests was marked with an acoustic and visual signal, and 2 experienced trainers recorded the swimming time in the 50-m freestyle (50F) and legs-only (50L) tests by using a stopwatch (3 × 100, Finis, Livermore, CA, USA). The tests were recorded with a camera placed on the lateral side of the swimming pool (HDR-AS20, SONY, Japan, frequency: 60 frames·s−1) and analyzed with the software Kinovea 0.8.15 (Kinovea, France) to determine the stroke frequency (SF) during the 50-m freestyle test and the relative stroke frequency loss (SFL) between the first and last 25 m.
Data are presented as mean ± SD. The normal distribution (Shapiro-Wilk test) of the data was checked before any statistical treatment. Pearson product-moment correlation coefficients (r) and the typical error of measurement were calculated to determine the association between the different variables and swimming performance, and are presented along with 90% confidence intervals (CIs). In addition, a stepwise multiple linear regression analysis was used to predict 50-m freestyle swimming performance. The independent variables that correlated most significantly with the 50-m freestyle swimming time were entered into the stepwise procedure. Correlation coefficients of 0.1, 0.3, 0.5, 0.7, and 0.9 were considered small, moderate, large, very large, and extremely large, respectively (6,21). The Bland-Altman´s limits of agreement between the actual and estimated values were calculated as 1.96 × SD. An alpha level of p ≤ 0.05 was set as the minimal level of significance. The statistical analysis was conducted using a statistical software package (SPSS 20.0, USA).
The validity of different mechanical variables of the 2 pull-up tests performed (PU and PUF) for the prediction of swimming performance is shown in Table 1. As can be seen, different upper-limb explosive strength markers such as PUV (0.78 ± 0.18 m·s−1, Figure 1A), PUAP (637 ± 197 W, Figure 1B), PURP (8.48 ± 2.24 W·kg−1), and PURF (10.76 ± 0.33 N·kg−1) were significantly correlated with 50F (26.41 ± 1.44 seconds). However, 50F was not correlated with PUAF (807 ± 113 N), PUPV (1.42 ± 0.57 m·s−1), or PUTpV (0.58 ± 0.17 seconds).
As for the fatigue resistance indexes of the upper limbs, a strong correlation (Table 1) was found between 50F and PUFV (0.57 ± 0.15 m·s−1, Figure 2A) and PUFVL (26.4 ± 6.7%, Figure 2B), but no correlation was found with PUFR (11.6 ± 4.0 reps). Stroke frequency (55.5 ± 4.7 strokes per minute) and SFL (8.1 ± 5.6%) were not significantly correlated with any variable of swimming performance (50F or 50L) or upper or lower-limb strength.
No significant relationship was found between measures of lower-limb strength values assessed through the CMJ tests and swimming performance, with no significant correlations between CMJH (36.8 ± 4.4 cm), CMJMH (30.1 ± 3.4 cm) or CMJHL (8.5 ± 3.3%) with 50F or with 50L. Nevertheless, a strong correlation (r = 0.78; 90% CI = 0.45 to 0.92; R2 = 0.60; p = 0.03) was found between 50F and 50L (40.59 ± 5.18 seconds).
The stepwise multiple linear regression analysis with 50F as a dependent variable showed that 50L and PUFVL as a two-factor combination predictor accounted for 84.3% (p = 0.0002) of the performance variance. The following equation determines the relationship: 50F = 15.9237 + 0.18846 × 50L + 0.1074 × PUFVL.
The aim of this study was to analyze the relationship between swimming performance and the dryland strength of the upper and lower limbs, using 2 classical and practical exercises, the pull-up and the CMJ, for this purpose.
Force or power values during different commonly used dryland exercises such as the lat pull-down, the bench press, or throwing a weighted ball have been previously correlated with swimming power (7,10,15,29) and, based on the relationship between swimming power and swimming performance (11), those values could therefore be proposed as predictors of swimming performance. However, some studies have found a correlation between dryland strength and swimming forces but not swimming performance (7,29).
A relationship between the maximum mean propulsive power (r = 0.68, ) and the 1RM (r = 0.64, ) in the lat pull-down exercise and swimming performance has been previously reported. We hypothesized that the pull-up, another dryland exercise that also involves the activation of an important muscle in swimming, the latissimus dorsi (24,38), and which has been related with performance in the lat pull-down (22,35), might also be a valid predictor of swimming performance.
The main finding of this study was the strong correlation between swimming performance and different mechanical variables of the ascending phase during one single pull-up (velocity and power) or during a series of PUF (mean velocity and resistance to the loss of velocity). All these variables, especially the mean velocity during the test of maximum number of pull-ups, presented a stronger correlation (r = 0.88) than those previously reported for the lat pull-down (7,29). Nevertheless, it must be emphasized that the maximum number of repetitions to muscular failure was not a good predictor of swimming performance. Therefore, these results support the validity of analyzing the mechanics during the pull-up to predict swimming performance but not the total number of pull-ups that the athlete can perform.
As mentioned above, the 1RM in the lat pull-down has been related to that in the pull-up (22) and with swimming performance (7). Regarding the relationship between velocity and %RM (18), it can be stated that in this study, swimming performance was correlated with the relative RM, although we cannot discern whether it was also correlated with a higher absolute RM. In addition, as performance in a test of maximum number of pull-ups is related to that of the maximum number of lat pull-down repetitions with the body mass (35), the analysis of the mean velocity during the latter may also be useful to predict performance.
This study also reports a strong correlation between leg kick and swimming performance. The leg kick positively affects swimming by stabilizing the trunk, increasing propulsion, and maintaining an horizontal position, which results in an improved hydrodynamic position (19). Confirming these results, leg kick has been shown to represent 30% of the total propulsive forces produced during swimming sprints (31) and to influence performance in swimming 25 (9) and 200 m (32) by approximately 10%.
Taking into account this relationship between the leg kick and swimming performance, we aimed to analyze the influence of the dryland strength of the lower limbs on leg-kick–only and freestyle swimming performance, using the CMJ as a valid predictor of the lower limbs' power (27). Our results show no correlation between any of the analyzed lower-limb strength markers and leg-kick–only or freestyle swimming performance. This lack of relationship has been previously reported in studies in which the participants started swimming from inside the water (15,29). Curiously, Morouço et al. (29) found a significant correlation between the work performed during the CMJ or the maximum mean propulsive power on the squat jump with the force produced during tethered swimming but not with swimming velocity, which reinforces the idea that other technical factors such as body position or leg-kick effectiveness play more important roles than the lower-limb strength (8).
On the other hand, the explosive strength of the lower limbs could be determinant for the performance on “non-swimming elements” such as the start or the flip turn. Performance during the start has been closely linked to performance, especially in short distances (41,42). Thus, previous studies have reported a moderate correlation between vertical jump ability and performance in the starts (14,43). Contrary to our study, some authors have reported a significant correlation between dryland lower-limb strength and swimming performance (12,23,26), although these differences may be due to the inclusion of flip turns because the tests were performed in a short swimming pool. Therefore, based on this and previous studies, the dry-land strength of the lower limb may not be a valid predictor of swimming or leg-kick only performance, although it may be a determinant of performance in nonswimming elements such as the start or the flip turn.
Resistance training has been shown to be a potent stimulus for the improvement of performance in various cyclic sports such as running, cycling, or rowing (2,13,39). Specifically, strength training has been reported to be especially useful for the improvement of performance in young athletes such as the sample analyzed in this study (20,25). Dryland strength training has been shown to improve force and power (30) and to reduce the muscle imbalances (5) usually found in this sport (4). Most studies in which a dryland strength training program has been added to the general swimming sessions have reported significant improvements in performance (2,17,34). However, it must be emphasized that an increase in strength does not necessarily mean an improvement in swimming performance because of the importance of technical factors, as swimmers have to not only develop high levels of force but also apply them in an effective way to maximize propulsion. Reinforcing this idea, some authors have reported increased force after a dryland strength training program with minor or no changes in swimming velocity (7,16,40). Therefore, these results confirm the importance of including an appropriate dryland strength training program in combination with swimming and technical training for the improvement of swimming performance in young athletes.
This study shows that the analysis of the mechanics (i.e., velocity and power) during one single maximal pull-up or during a test of maximum number of PUF could be used to predict swimming performance in short distances in competitive swimmers, which confirms the important role of the upper-limb strength in this sport. However, the maximum number of pull-ups or the jump height performed, which are commonly used by coaches to assess the swimmer's strength and power, were not good predictors. These results also highlight the necessity of including dryland strength training in the program of swimmers, making the pull-up a suitable exercise to be performed.
The authors acknowledge Juan Camus (head coach of SEK swimming club) and Ivan Quiroga (head coach of Gredos San Diego Alcalá swimming club), as well as all the swimmers who took part in the study, for their excellent disposition. They also thank María Valdivieso from Centro Médico Complutense and the Sports Science laboratory of the University of Alcalá for their material support. The authors have no conflicts of interest to disclose.
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