In competitive sprint front crawl swimming, athleticism is characterized by high rates of strength and slenderness and a long swimmer's body is well recognized (5,8,21,27–29). The influence of anthropometric properties such as lean body mass (LBM), total length or length of body parts, and further strength and endurance are considered as essential for achievements in age-group swimmers (39,41). These properties in mature swimmers become indispensable factors and are the basis in top-level racing in front crawl (6). In talented swimmers, sporting factors such as body structure, level of endurance and strength, and mechanical efficiency develop unevenly (2). These somatic and functional parameters associated with swimming achievements are related in young swimmers to their biological development; morphological, sexual, and physiological maturity. At the age of puberty and after puberty, we can observe the periods of most rapid growth of body (length) segments, subsequently musculature, anaerobic power, and strength occur (18,36,38). On the other hand, in a swimmer's career, among comprehensively trained, biologically, and physically developed participants, factors associated with body size and physical capacity may lose their power to impact on the results of sprint swimming. This could be caused when strength development is not paired with swimming technique, including changes in movement coordination, or sometimes when comparisons are made between homogeneous peers (9,13,31,36). Nevertheless, higher level swimming means technique optimization which translates to better hydrodynamic efficiency when using increased biomechanical technique proficiency (20). Properties of swimming technique and stroking characteristics can be more decisive for swimmers competing at the top level (8,30).
Existing literature shows that dry-land isotonic or isometric strength tests (12,15–17,32,34,35,37) or water anaerobic tests (10,19,26,28,31,42) are used to evaluate the current physical preparation of competitive swimmers for front crawl sprint performance. In this area of research, 1 statement can be found which argues that in-water testing may be more valuable than testing on dry land (5,13). However, observations on the study of strength properties during swimming, especially during tethering, have been carried out in swimmer groups around the pubertal age, or in groups with high age dispersion.
Bearing in mind the above-outlined reasons, we are going to examine the influence of somatic indices, such as body height—BH, total body length—TBL, arm span—AS, body mass—BM, and lean body mass—LBM on 50-m front crawl sprint swimming speed in 2 male swimming age groups (19,30,36). Moreover, an examination of the general strength of upper and lower limbs measured on dry land (15,16,25,34,35,37) and, on the other hand, specific strength in tethered swimming (10,26,42) was conducted to assess their impact on swimming speed.
Experimental Approach to the Problem
A younger (for the purposes of this study called “Junior”) and an older—(“Youth”) swimmers groups were recruited to compare their (a) somatic characteristic, (b) dry-land isometric muscle strength or anaerobic muscle system motor capability measured in the countermovement jump (CMJ) test, and (c) tethered front crawl swimming strength indices. To learn more about the performance prediction in these 2 age groups, chosen indices and basic swimming kinematic—stroke rate (SR) and stroke length (SL)—and their relationships with front crawl sprinting results were assessed.
We can assume that somatic properties and measured dry-land anaerobic strength and power significantly influence sprint front crawl swimming in Junior and Youth swimming groups but with a higher relationship seen among younger swimmers. The tethered swimming indices will be a better sprint performance predictor than dry-land strength tests.
Thirty-five male swimmers were recruited from 2 university swimming clubs. They were separated into 2 groups with respect to the age category in which they compete, Junior (17–18 years old) or Youth (19–23 years old). This age grouping of participants was taken as the criterion of inclusion to the study. According to this criterion, 15 swimmers qualified for the Junior group and 20 swimmers for the Youth group, their age was 17.3 ± 0.59 and 20.6 ± 1.05, respectively, and they specialized in front crawl or in individual medleys which was another inclusion criterion. The Youth group competed at regional (2 participants), national (16 participants), or international level (2 participants), their personal best results in races amounted to 81.3, 84.8, and 90.1% of senior swimmers' world records, respectively. In the Junior group, the percentage of the 50-m front crawl world record was 77.1% in 2 regional and 82.2% in 13 national swimmers. All of them had licenses from the Polish Swimming Federation and were healthy, which was required. They trained twice a day, 6 days a week. If there was an injury that could affect the results of the study, this was considered to be an exclusion criterion. All swimmers (and their parents) signed an informed consent form for taking part in this research (approved by the Bioethics Commission in Krakow).
Body height was measured from the bottom of the feet to the vertex of the head while standing erect. Total body length was measured when lying back, from the tips of the fingers (with arms stretched up above the head) down to the pointed toes (foot plantar flexion). For the AS measurement, participants were standing in an upright orthostatic position with arms and fingers fully extended in lateral abduction at a 90° angle with the trunk. These body segment length measurements were completed using an anthropometer or, in the case of TBL, an extended anthropometer (Sieber Hegner Maschinen AG, Switzerland). Swimmers' BM tests (Sartorius, Germany), and later LBM were calculated after the body fat assessment. Body fat percentage was determined from the estimate of body density. The Durnin and Womersley (11) body density equation with measurement of 4 skinfolds (biceps, triceps, subscapular, and suprailiac) results were used. Skinfold measurement met the criteria of the International Society for the Advancement of Kinanthropometry (40). The results obtained from the equation (that of body fat density) were subsequently taken into the Siri equation to calculate body fat (33). Constant spring pressure of (10 g·mm−2) Harpenden Skinfold Calliper (Holtain Ltd., United Kingdom.) was used for the measurement of skinfold thickness. The anthropometry measurements were conducted with the reliability result of—intraclass coefficient (ICC(3,1)): 0.9994; 95% lower; upper confidence interval (CI): 0.9977 and 0.9998, respectively.
Dry-Land Maximal Power Test
The CMJ measurement was performed with the use of a dynamometric platform (JBA Staniak, Poland). The athlete stood upright on the platform with the weight evenly distributed over both feet. Hands were placed on the hips throughout the test to eliminate them from contributing to energy generation. Work W (J) generated in the concentric muscle contraction phase of the jump (being a result of the CMJ test) was taken as an absolute indicator of anaerobic muscle system motor capabilities. Elevation of the center of mass h (cm) was considered as an indicator of muscle system motor capabilities relative to BM. The best result of the 3 attempts was taken for further calculations. A reliability test of the CMJ force platform measurements was conducted with the reliability result of—ICC(3,1): 0.965; 95% lower; upper CI: 0.936 and 0.983, respectively.
Isometric Muscle Strength Measurement
Maximum isometric muscle strength was measured using an adjustable dynamometer chair—Good Strength Metitur (Metitur Oy, Jyväskylä, Finland). A reliability test of this equipment's measurements was conducted with the reliability result of—ICC (3–1): 0.964; 95% lower; upper CI: 0.924 and 0.983, respectively. Muscle force of extensors and flexors of elbow and knee joints for the right and left sides were measured (Figure 1). All measurements were conducted with the joints at right angles. Three measurements for each muscle group were taken and the highest force value was taken as the result. An average of left- and right-side results was assumed as the maximum isometric muscle strength of a particular muscle group.
Tethered Swimming Test
The tethered test was performed during 25 seconds of all-out front crawl swimming. The participants underwent familiarization trials of tethered swimming during the warm-up session before the tethered test. Validation of such procedures was conducted following the example set by Taylor et al., (38). The swimmer was connected to a 3.6-m steel cable (with waist belt) and a dynamometer (recording at 100 Hz) was fixed to a start block (Figure 2). All recorded data were continuously displayed on the laptop display and stored in the hard disk.
Data were processed by signal processing software (Max 6.0; JBA, Poland) and filtered through a 4.5-Hz cutoff low-pass filter.
For every participant, the following indices were calculated: (a) maximum value of force, (b) average value of force recorded during the 25-second period, (c) maximum value of impulse in a single stroke (Figure 3), and (d) average impulse calculated as the sum of all single-stroke impulses divided by the number of strokes performed during the 25-second period. Stroke rate was calculated on the basis of stroke cycles performed during the 25-second period and converted to cycle·min−1.
Sprint Swimming Test
The all-out swimming 50-m free front crawl speed test using an automatic timing device (Omega, Switzerland) was conducted in a 25-m swimming pool that meets International Swimming Federation standards. To eliminate personal advantage coming from more- or less-skilled block starts and underwater turn phases, the participants were asked to perform in-the-water starts and to shorten the underwater swimming phases after the start and the turn to 10 m. The time achieved by swimmers in this test was taken to calculate the swimming speed. The SR [cycle·min−1]) was determined using a camcorder (Sony HDR-AZ1, Japan at the sampling rate of 60 Hz.) that made recordings of the swimmers' movements from the side view of the pool deck. The SR was taken as the average from 8 stroke cycles (4 consecutive cycles of the middle section of the first and the second laps). The camera was placed at the middle point (12.5 m) of the pool length and attached to a tripod with a rotating head. The SL calculation was based on the data gathered in a 10-m sector during the second lap (i.e., between the 35th and 45th meters) of the distance of 50 m, using a video recorded by 2 Canon Legria HV40 (Japan) camcorders (sampling rate 50 Hz) located on tripods standing on the pool deck. Recordings from these 2 cameras were synchronized with a flash light triggered by the Omega electronic starting device. The Canon camcorders filmed each swimmer's head crossing the 35- and 45-m lines of the distance. The recordings enabled a calculation of the time needed to complete the 10-m sector (Δt), which in turn served as a basis for the calculation of average 10-m swimming speed. Stroke length (SL) was calculated as the average speed in a 10-meter sector (V) to stroke rate (SR) ratio: SL = V/SR [m].
The free and tethered front crawl tests were preceded by a self-selected warm-up, similar to the one performed before a competition, including at least 1,000-meter swimming using front crawl and other swimming techniques. All tests were conducted approximately 1 week after the main competition in the yearly season (Polish Swimming Championships).
Basic descriptive statistics were calculated and all variables were examined for normal distribution using the Shapiro-Wilk test. For age-group swimmers (or the all-combined group, for comparison of 50 m free and tethered swimming data), comparisons of Student's t-test was used for normally distributed data and equal variances, the Student's t-test with Cochran-Cox adjustment in the case of normally distributed data but unequal variances and the Mann-Whitney U-test for non-normally distributed data. To determine differences between SR of 50-m free front crawl swimming and SR of tethered swimming, a t-test for dependent groups was carried out.
Pearson correlation coefficients were computed between swimming speed (Vcrawl) and all variables: (a) somatic indices, (b) functional indices, (c) isometric force indices, (d) tethered front crawl indices, and (e) 50-m free front crawl basic kinematics in 2 age-group swimmers as well as in the combined group made up of all swimmers. To further evaluate mean differences, Cohen's effect size (d) was calculated to express such differences relative to the pooled SD. Cohen's categories were used to evaluate the magnitude of these effect sizes (small if 0 ≤ |d| ≤ 0.5, medium if 0.5 <, |d| ≤ 0.8, and large if |d| > 0.8). Statistical significance was set as p ≤ 0.05. All tests were computed using STATISTICA ver. 12 software (StatSoft, Inc.).
The 50-m front crawl swimming speed (VCrawl) for the age-group swimmers was 1.92 ± 0.06 m·s−1 for Youth and 1.82 ± 0.06 m·s−1 for Junior swimmers, respectively. Figure 4 shows VCrawl results dispersion with significant difference between groups (t(df = 33) = 4.78, p < 0.001). Cohen's effect size of the VCrawl average differences was large for this comparison, d = 1.665.
All other gathered indices in this study are presented for age-group swimmers as well as their group differences and the Pearson correlations with VCrawl. To show the overall relationship of those indices on VCrawl, additional correlation calculations were made of their entire influence on swimming speed (together with the effect of maturity, mastery of technique, and experience) in combined groups of all swimmers (n = 35).
Table 1 includes somatic indices of both swimmers' groups and correlation results with their Vcrawl. A significant, very high correlation between LBM with VCrawl was only noted in Junior swimmers, and significant and high for BM, BH, TBL, and AS with VCrawl. Correlations in the combined group with Vcrawl (1.88 ± 0.07 m·s−1) were weaker but still significant for BM (77.93 ± 5.37), r = 0.51, p = 0.002; LBM (69.47 ± 4.88), r = 0.59, p < 0.001; BH (183.26 ± 6.29), r = 0.37, p = 0.03; and TBL (254.44 ± 9.12), r = 0.43, p = 0.01.
Significant differences were noted between BM and LBM indices in Junior and Youth groups. By analyzing the dispersion of LBM, in particular, we can see that this is the factor that mostly influences VCrawl as shown in Figure 5. The Cohen's effect size (d) of LBM average differences was large, d = 1.037 (similar to that for BM, d = 1.208).
Similarly, in the case of functional indices of the maximal power test—CMJ, the elevation of the center of mass and work generated in the concentric muscle contraction phase were significantly highly interrelated with VCrawl, with the highest relationship of absolute indicator (CMJ J), but only in Junior swimmers (Table 2). Significant group differences were noted in CMJ cm·kg−1, with large Cohen's effect size, d = 0.801, which enabled them to jump higher. There was no significant relationship of CMJ indicators with VCrawl in the combined group.
The results of isometric strength of elbow joints in swimmers did not show any relationship with VCrawl, and there were no differences between groups (Table 3). Only the generated force of knee joint muscle flexors (Knee-Flx) and extensors (Knee-Ext) as absolute indicators was significantly correlated with VCrawl, again only in the Junior group of swimmers (Table 4). The developed strength of flexors and extensors of the lower limbs was greater in the Junior group, but significantly higher in the case of Knee-Flx N·kg−1 with large Cohen's effect size, d = 0.926. There was no significant relationship of isometric strength indicators with VCrawl in the combined group.
The results of tethered front crawl swimming are shown in Table 5, whereas in the last column the SR achieved in free front crawl. No significant relationship was found between those indices in Youth, Junior, and VCrawl. A significant difference between the groups was noted only in the case of SR free front crawl swimming. Furthermore, SR (paired t test) comparison showed that the SR kinematic was significantly lower in both swimmers' groups during tethered than free 50-m front crawl swimming (Youth t(19) = 7.17, p < 0.001; Junior t(14) = 3.55; p = 0.003). In the overall combined swimmers' group, a significant relationship was noted between SR tethered (52.18 ± 3.53 cycle·min−1) and VCrawl (r = 0.34, p = 0.044), and SR 50 (56.24 ± 4.16) and VCrawl (r = 0.41, p = 0.014). The difference between SR tethered and SR 50 in the combined group was significant (t(df = 34) = 7.45, p < 0.001) with a large Cohen's effect size, d = 2.55. Stroke length results 1.91 ± 0.12 m in Youth and 1.96 ± 0.16 m in Junior swimmers were not significantly different and not significantly correlated with anthropometric variables or strength indices when considering it as age-group index, or when combined for all swimmers.
Furthermore, to examine Favr generation in limb movement cycles (for all combined swimmers; 120.32 ± 28.24 N)—a main result of tethered swimming, we computed the correlation of this index with SR tethered and Fmax (321.63 ± 90.43 N). This interplay was statistically significant with SR r = 0.39, p = 0.021, and with Fmax 0.88, p < 0.001.
In this study, results of analyzing the influence of selected body properties on VCrawl showed that body size such as BM, LBM, and body length indices played an important role as a basis for propulsion generation only in the group of Junior swimmers, which supports other studies where participants were at a similar age or younger (8,19,21,29). During the hypothesis stage, we expected that this relationship in the Youth swimmers' group would be weaker. Indeed, results showed no significant impact of anthropometric variables on VCrawl in this group. Although the significance of this relationship was retained after the merger of the 2 groups, it becomes obvious that this is more attributable in Youth swimmers to the differences of swimming kinematic optimization. Furthermore, this statement is additionally supported by the scheme of relationship noted between all general dry-land and specific water strength indices which had faint dependence on VCrawl in older Youth swimmers. Relationship of VCrawl and strength indices was still not significant after the merger of the 2 groups. Our results did not reveal an implication of upper limb strength on VCrawl. Other studies have shown significant impact of direct (34) or indirect (28) arm strength measurement results on sprinting front crawl performance, but in younger swimmers than in both our groups. Considering correlations gathered herein in Youth swimmers in comparison with research conducted by Rohrs et al. (31), in male swimmers at a similar age, we can see that the anaerobic muscle system motor capability evaluated in vertical jump (cm) was highly connected (r = 0.66) to 50-yard speed. In the same study and what is further partially in line with ours, it was found that neither 30-second peak nor mean force-tethered front crawl swimming results were significantly correlated with 25, 50, or 100-yard front crawl speed. Similarly, in an experiment performed by Aspenes et al. (1), the improvement achieved after training intervention in tethered swimming force did not cause improvement in 50- or 100-m front crawl results. Rohrs et al. (31) discussed the possibility that faster swimmers have a more powerful lower body than slower swimmers. Although they did not clearly state it, looking through the results obtained in the same study, it seems that 30-second both arm or single pull biokinetic power, Margaria-Kalamen stair climb or arm cranking peak power test results significantly influenced swimming speed. In our study, it could be so in the Junior group because here a significant influence was noted of absolute indices of CMJ and Knee-Flx and Knee-Ext on VCrawl. This is partially in accordance with the study conducted by Loturco et al. (22), where the researchers found a very high correlation (r = 0.7) between jump squat and the performance of 50-m swimming in junior swimmers at the age of 17.0 ± 0.7 years. A similar correlation was also shown in another piece of research conducted using the CMJ test (35).
It is interesting to observe the lowering influence of anthropometric indices and strength on front crawl swimming speed in Youth and Junior age-group swimmers as was partially found earlier by Strzała et al., (36). They noted the decreasing influence of somatic properties and functional strength (CMJ) or anaerobic endurance of arms and legs on sprint front crawl in swimmers at the age of 15 and nearly 17 years. A similar scheme was found in a research by Garrido et al. (13) where the relationship between handgrip isometric strength and 100-m front crawl swimming performance was found to decrease from younger to older swimmers (juvenile, junior, and senior).
In our study, absolute general (dry-land) or specific strength abilities were not different between Junior and Youth swimmers, and when considering it per BM it was higher in younger participants in the case of some indices (CMJ cm·kg−1; Knee-Flx N·kg−1). Costill et al. (9) suggested that in a similar situation, factors other than strength account for differences in sprint swimming. In our study, VCrawl difference between Junior and Youth was influenced by technique, specifically by basic kinematic—SR 50 which was significantly higher in the Youth group and revealed (correlation r = 0.41, p = 0.014) a relationship with VCrawl after the combination of both groups. Faster Youth swimmers used simultaneously nonsignificantly shorter SL kinematic. In accordance with other studies, it showed an implication of sprint front crawl swimming with basic technique index—higher SR and upper limb coordination with a lower time of nonpropulsive phases (8,30,35). In Taylor et al.'s (39) study, although conducted in swimmers of pubertal age, the authors' conclusions suggest a relation of swimming results which coincide with significant increases in mean force production. However, the influence of technical ability and motor skill development cannot be ignored. In our study, tethered Fmax and Favr were comparable to those measured by others, but we found no relationship with VCrawl, which was noted by others (12,22,26,42). Nevertheless, we expected in our study that even small differences in the properties of the force generated in the water while swimming tethered would have an impact on the achievements in the sprint free front crawl, but we failed to prove this. A similar phenomenon has been well commented on by Costill et al., (9). They mentioned during their earlier observations that there was no significant association between biokinetic arm strength and sprint swimming in homogenous swimmers' groups. They expressed, however, that having markedly different swimming and strength abilities in heterogeneous groups, this relationship becomes much more obvious than in less differentiated homogenous samples. We could not find tethered force relationship with VCrawl after the merger of both age groups comprising athletes of different skills. In our observations only in the Junior group, with the correlation at the level (r = 0.35), could statistical power analysis be achieved with the required sample size of 81 cases, which is far below the results recorded recently by Loturco et al., (22). Instead therefore, considering the lack of relationship of tethered swimming results on VCrawl, we simply asked our swimmers about the difference in feeling during tethered swimming compared with swimming freely. They answered that it was not possible to accelerate arms in the same manner as in free swimming nor was it as easy to gain momentum through the push. Our results confirm this description as in both age groups, and in the combined group, the SR tethered was significantly lower than during free swimming (SR 50). Diminished SR and other stroke pattern changes affected tethered front crawl mechanics which was also observed in the study conducted by Maglischo et al., (23). Perhaps power output measured in swimming corresponding to more real conditions is more valuable, as was observed elsewhere (3), where power output generated when swimming with a towing perturbation buoy was the key factor in explaining the speed of sprint swimming. We also know from the observations made in this study that Favr production was significantly dependent on the higher SR. In real competition conditions, the SR is even higher in world-top junior or senior sprint swimming than noted in this study (see Haljand, www.swim.ee). Furthermore, according to Gerard et al. (14), what is important to achieve a high swimming speed over short distances is possessing a higher value of percentage area of type IIA and type IIB muscle fibers—the fast twitch muscle fibers, which in turn coincide with higher values of leg power and strength. That is consistent with the high metabolic and contractile demands of sprint swimming in the case of the best swimmers (31). Even if these somatic and functional conditions are met, the need to complement them with the technique of swimming is crucial (4,7,24). Despite this, we can agree that the force obtained in tethered swimming may be a good evaluator of sprint swimming performance, especially in younger swimmers in which the formation of long SL is important (3,25).
In this study, it was observed that anthropometric properties (BM, LBM, BH, TBL, and AS) and general dry-land strength of muscle system motor capabilities as measured in the CMJ test or lower extremity isometric strength of knee joint muscle flexors (Knee-Flx) and extensors (Knee-Ext) were better predictors of VCrawl in Junior swimmers than in Youth swimmers. We can state that the factor which has a greater impact on the results of sprint swimming in more experienced, older Youth swimmers is the technique of swimming. In these observations, it was characterized only by 1 basic kinematic parameter, a higher SR in more skilled Youth swimmers, which is the limitation to this study. In future studies, the evaluation of swimmers' aptitudes should be conducted with the use of additional sprint swimming technique detail descriptors.
This study demonstrates that the evaluation of front crawl sprint swimming aptitudes performed on the basis of somatic traits and properties of strength, measured on dry land and in water, should be complemented by measurements of real sprint swimming technique parameters. Analysis of factors affecting the efficiency of swimming may be more difficult and more sophisticated in the selection of indicators in older, more advanced swimmers. In-depth evaluation of swimming efficiency may require simultaneously control of strength properties and individualized analysis of the basic kinematic indicators supplemented with body motion analysis or limb movement coordination analysis.
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