Hydrodynamic profile of young swimmers: Changes over a competitive season

Does a jammer-type racing swimsuit improve sprint performance during maximal front-crawl swimming?

We investigated the effects of jammer-type racing swimsuits (RS) on swimming performance during arm-stroke-only (pull) and whole-body stroke (swim) in 25-m front-crawl with maximal effort. Twelve well-trained male collegiate swimmers wore RS and a conventional swimsuit (CS) and performed three tests: pull, swim, and pull using the system to measure active drag (MAD pull). Swimming velocity and intra-abdominal pressure (IAP) were determined in all tests. Stroke indices during pull and swim and drag-swimming velocity relationship and maximum propulsive power during MAD pull were also determined. Swimming velocities during pull and swim while wearing an RS (1.59 ± 0.13 and 1.77 ± 0.09 m·s-1, respectively) were significantly higher than those wearing a CS (1.57 ± 0.14 and 1.74 ± 0.08 m·s-1, respectively). Stroke length during pull and swim was significantly greater while wearing an RS (1.68 ± 0.12 and 1.83 ± 0.13 m, respectively) than wearing a CS (1.63 ± 0.10 and 1.81 ± 0.13 m, respectively). However, no significant differences were confirmed between the other variables in all tests. In conclusion, swimming performance is improved when wearing an RS compared with a CS.

Measurement of the active drag coefficient in front-crawl: A stroke-by-stroke analysis

The purpose of this study was to understand the change in active drag coefficient (CDA) over successive stroke cycles in front-crawl and the relationship between swimming speed and CDA. Eighteen national competitive swimmers (nine girls and nine boys with a mean age of 14.91 ± 0.59 years) were recruited. Swimming speed, propulsion (Ftotal) and frontal surface area were measured to calculate the CDA. Swimming speed (F = 1.790, p = 0.182, η2 = 0.07) and CDA (F = 0.907, p = 0.413, η2 = 0.06) did not change significantly over time, but swimming speed showed a decrease between the second and third stroke cycle. On the other hand, the Ftotal changed significantly over time (F = 4.437, p = 0.019, η2 = 0.21). Swimming speed and CDA showed a linear and strong relationship (R2 = 63.8 %). A stroke-by-stroke analysis showed that national level swimmers were able to maintain their hydrodynamic profile during a front-crawl maximal trial. Thus, it can be argued that a decrease in swimming speed can be related to a decrease in Ftotal. Swimming speed and CDA showed an inverse and significant relationship, with lower values of CDA resulting in faster swimming speeds.

Nonlinear Analysis of the Hand and Foot Force-Time Profiles in the Four Competitive Swimming Strokes

Human locomotion on water depends on the force produced by the swimmer to propel the body forward. Performance of highly complex motor tasks like swimming can yield minor variations that only nonlinear analysis can be sensitive enough to detect. The purpose of the present study was to examine the nonlinear properties of the hand/feet forces and describe their variations across the four competitive swimming strokes performing segmental and full-body swimming. Swimmers performed all-out bouts of 25 m in the four swimming strokes, swimming the full-body stroke, with the arm-pull only and with the leg kicking only. Hand/foot force and swimming velocity were measured. The Higuchi's fractal dimension (HFD) and sample entropy (SampEn) were used for the nonlinear analysis of force and velocity. Both the arm-pull and leg kicking alone were found to produce similar peak and mean hand/foot forces as swimming the full-body stroke. Hand force was more complex in breaststroke and butterfly stroke; conversely, kicking conditions were more complex in front crawl and backstroke. Moreover, the arm-pull and kicking alone tended to be more complex (higher HFD) but more predictable (lower SampEn) than while swimming the full-body stroke. There was no loss of force production from segmental swimming to the full-body counterpart. In conclusion, the number of segments in action influences the nonlinear behavior of the force produced and, when combining the four limbs, the complexity of the hand/foot force tends to decrease.

Relationship between swimming speed, intra-cycle variation of horizontal speed, and Froude efficiency during consecutive stroke cycles in adolescent swimmers

The purpose of this study was to investigate the relationship between swimming speed, intra-cycle variation of horizontal speed of displacement (dv), and Froude efficiency (ηF) in front-crawl during three consecutive stroke cycles. The sample consisted of 15 boys aged 16.07 ± 0.77 years and 15 girls aged 15.05 ± 1.07 years. Swimming speed, dv and ηF were measured during a 25 m front-crawl trial. Three consecutive stroke cycles were measured. Swimming speed showed a non-significant stroke-by-stroke effect (F = 2.55, p = 0.087, η2 = 0.08), but a significant sex effect (F = 90.46, p < 0.001, η2 = 0.76). The dv and ηF had the same trend as the swimming speed for the stroke-by-stroke effect, but a non-significant sex effect (p > 0.05). The Spearman correlation matrix between swimming speed and dv, and swimming speed and ηF showed non-significant correlations for the three stroke cycles in both sexes. However, the tendency of the former was not always inverse, and the latter was not always direct. Coaches and swimmers need to be aware that lower dvs are not always associated with faster swimming speeds and vice-versa, and that ηF is a predictor of swimming speed, not dv.

Countermovement push-up test to assess the upper extremity force-time characteristics in swimmers during a macrocycle

Although it is known that swimming training can improve upper extremity performance, the force-time characteristics of the upper extremity during different training periods are not well understood. The objective of this study was to measure changes in the force-time characteristics of the upper extremity of young swimmers during different training periods within a season. Seventeen young swimmers, comprising 5 males (age: 15.4 ± 0.54 years); 12 females (16.4 ± 2.6 years) participated in this study. They were tested at four experimental test time points: baseline (E1), post-general preparation (E2), post-specific preparation (E3), and taper season (E4). The countermovement push-up test was performed using a force plate to measure force time parameters. Differences in force, time, velocity and impulse parameters were evaluated between the different periods. The study found that vertical take off velocity significantly increased across the assessed periods (F = 11.79; p = .001; η2 = .424), with significant increases from E1 to E2 (p < .001) and from E3 to E4 (p = .016). Flight Time also significantly increased across the assessed periods (F = 11.79; p = .001; η2 = .424), with significant increases from E1 to E2 (p < .001), from E1 to E4(p = .001), and from E3 to E4 (p = .005). The Force Impulse significantly increased throughout the assessed periods (F = 5.84; p = .012; η2 = .267), with significant increases from E1 to E2, (p = .006), from E1 to E3 (p = .016), and from E1 to E4 (p = .003). As this study shows, periods of increased training intensity can affect athletic progression, even though training aims to improve strength, speed, and performance. While some practical aspects such as strength, flight time, and impulse parameters may change during a macrocycle, the countermovement push-up test can provide trainers with an alternative and convenient way to monitor anaerobic force, speed, and performance, as well as measure explosive force-time performance in the upper body.

Identifying Differences in Swimming Speed Fluctuation in Age-Group Swimmers by Statistical Parametric Mapping: A Biomechanical Assessment for Performance Development

The aim of this study was to compare the assessment of swimming speed processed as a discrete variable and as a continuous variable in young swimmers. One-hundred and twenty young swimmers (60 boys: age = 12.91 ± 0.86 years; 60 girls: age = 12.46 ± 0.94 years) were analysed. The dataset for each sex was divided into three tiers: (i) tier #1 - best-performing swimmers; (ii) tier #2: intermediate-performing swimmers, and; (iii) tier #3 - poorest-performing swimmers. As a discrete variable, swimming speed showed significant sex and tier effects, and a significant sex*tier interaction (p < 0.001). Speed fluctuation showed a non-significant sex effect (p > 0.05), a significant tier effect (p < 0.001), and a non-significant sex*tier interaction (p > 0.05). As a continuous variable, the swimming speed time-curve presented significant sex and tier effects (p < 0.001) throughout the stroke cycle, and a significant sex*tier interaction (p < 0.05) in some moments of the stroke cycle. Swimming speed fluctuation analysed as a discrete variable and as a continuous variable can be used in a complementary way. Nonetheless, SPM can provide deeper insight into differences within the stroke cycle. Thus, coaches and practitioners should be aware that different knowledge about the swimmers' stroke cycle can be learned by assessing swimming speed using both methods.

The Effects of 6-Week Training Cessation on Anthropometrics, in-Water Force, Performance, and Kinematics of Young Competitive Swimmers: A Maturity Development Approach

PURPOSE

To examine the effects of 6 weeks of training cessation on young swimmers' anthropometrics, in-water force, performance, and kinematics according to biological maturation.

METHODS

Eighteen swimmers (7 girls: 12.43 [0.73] y old; 11 boys: 13.27 [0.79] y old) were assessed pretest and posttest 6 weeks apart. Body mass, stature, arm span, and hand surface area were measured as anthropometric parameters, and biological maturation was estimated (ie, peak height velocity [PHV]). The in-water force was retrieved during 2 bouts of 25-m front crawl, allowing the estimation of the symmetry index. The time to complete the 25-m was considered the performance outcome, whereas velocity, stroke rate, stroke length, stroke index, and arm stroke efficiency were used as kinematic parameters.

RESULTS

All anthropometric parameters increased during the detraining period. Although the in-water force remained unchanged, the magnitude of the effects was large for the symmetry index (P = .021; d = 0.87). For the pooled sample, neither performance nor kinematics changed after detraining, but the stroke index increased (P = .054; d = 0.27). Pre-PHV swimmers showed unchanged values in all parameters, despite natural growth. Mid-PHV swimmers showed a similar trend in addition to reductions in stroke rate (P = .040; d = 0.60) and increases in stroke length (P = .043; d = 1.00).

CONCLUSIONS

In-water force, performance, and kinematics (25-m front crawl) were not impaired after 6 weeks of training cessation in a group of young swimmers. Given interindividual and intraindividual differences according to maturity status, coaches should be aware that distinct trends within the group can be found.

Agreement between Different Methods to Measure the Active Drag Coefficient in Front-Crawl Swimming

The aim of this study was to analyze the agreement of the active drag coefficient measured through drag and propulsion methods. The sample was composed of 18 swimmers (nine boys: 15.9 ± 0.9 years; nine girls: 15.3 ± 1.2 years) recruited from a national swimming team. The velocity perturbation method was used as the drag measurement system and the Aquanex system as the propulsion system. For both sexes combined, the frontal surface area was 0.1128 ± 0.016 m2, swim velocity 1.54 ± 0.13 m.s-1, active drag 62.81 ± 11.37 N, propulsion 68.81 ± 12.41 N. The level of the active drag coefficient agreement was calculated based on the mean values comparison, simple linear regression, and Bland Altman plots. The mean data comparison revealed non-significant differences (p > 0.05) between methods to measure the active drag coefficient. Both the linear regression (R2 = 0.82, p < 0.001) and Bland Altman plots revealed a very high agreement. The active drag coefficient should be the main outcome used in the interpretation of the swimmers' hydrodynamic profile, because it is less sensitive to swimming velocity. Coaches and researchers should be aware that the active drag coefficient can also be calculated based on propulsion methods and not just based on drag methods. Thus, the swimming community can now use different equipment to measure the hydrodynamics of their swimmers.

Methodological Considerations in the Kinematic and Kinetic Analysis of Human Movement among Healthy Adolescents: A Scoping Review of Nonlinear Measures in Data Processing

Nonlinear measures have increasingly revealed the quality of human movement and its behaviour over time. Further analyses of human movement in real contexts are crucial for understanding its complex dynamics. The main objective was to identify and summarize the nonlinear measures used in data processing during out-of-laboratory assessments of human movement among healthy adolescents. Summarizing the methodological considerations was the secondary objective. The inclusion criteria were as follows: According to the Population, Concept, and Context (PCC) framework, healthy teenagers between 10 and 19 years old that reported kinetic and/or kinematic nonlinear data-processing measurements related to human movement in non-laboratory settings were included. PRISMA-ScR was used to conduct this review. PubMed, Science Direct, the Web of Science, and Google Scholar were searched. Studies published between the inception of the database and March 2022 were included. In total, 10 of the 2572 articles met the criteria. The nonlinear measures identified included entropy (n = 8), fractal analysis (n = 3), recurrence quantification (n = 2), and the Lyapunov exponent (n = 2). In addition to walking (n = 4) and swimming (n = 2), each of the remaining studies focused on different motor tasks. Entropy measures are preferred when studying the complexity of human movement, especially multiscale entropy, with authors also carefully combining different measures, namely entropy and fractal analysis.

Plasma Amino Acids and Acylcarnitines Are Associated with the Female but Not Male Adolescent Swimmer's Performance: An Integration between Mass Spectrometry and Complex Network Approaches

The main aim of this study was to compare the performance over different distances, the critical velocity (CV), and plasma acylcarnitines/amino acids of male and female adolescent swimmers. Moreover, we applied the complex network approach to identify which molecules are associated with athletes' performances. On the first day under a controlled environment, blood samples were collected after 12 h of overnight fasting. Performance trials (100, 200, 400, and 800-m) were randomly performed in the subsequent four days in a swimming pool, and CV was determined by linear distance versus time mathematical function. Metabolomic analyses were carried out on a triple quadrupole mass spectrometer performing electrospray ionization in the positive ionization mode. No difference was observed between the performance of male and female swimmers. Except for 200-m distance (p = 0.08), plasma tyrosine was positively and significantly associated with the female times during the trials (100-m, p = 0.04; 400-m, p = 0.04; 800-m, p = 0.02), and inversely associated with the CV (p = 0.02). The complex network approach showed that glycine (0.406), glutamine (0.400), arginine (0.335), free carnitine (0.355), tryptophan (0.289), and histidine (0.271) were the most influential nodes to reach tyrosine. These results revealed a thread that must be explored in further randomized/controlled designs, improving the knowledge surrounding nutrition and the performance of adolescent swimmers.

The Mechanical and Efficiency Constraints when Swimming Front Crawl with the Aquanex System

The aim of this study was to compare the mechanical and efficiency constraints between free swim and swimming with differential pressure sensors (Aquanex System). These conditions were also analysed to understand the differences between sexes. Thirty young swimmers, 14 boys and 16 girls (12.31 ± 0.67 years) performed three 25-m front crawl maximal bouts under each condition: free swim and swimming with sensors. Under the condition with sensors, swimmers carried the Aquanex System composed of two hand pressure sensors (v.4.1, Model DU2, Type A, Swimming Technology Research, Richmond, VA, USA). The 25-m time (T25) was assessed as a swimming performance variable. The swimming velocity (v), stroke rate (SR), and stroke length (SL) were assessed and calculated as stroke mechanics variables. Thereafter, the stroke index (SI) and arm stroke efficiency (η F) were estimated for swimming efficiency. Statistical significance was set at p ≤ 0.05. Swimming performance was impaired when swimmers swam with sensors (overall: p = 0.03, d = 0.14; Δ = 1.30%) and a significant decrease in v was found for overall (p = 0.04, d = 0.14; Δ = 1.42%) and the girls’ group (p < 0.01, d = 0.39; Δ = -1.99%). The remaining stroke mechanics variables showed no differences between conditions, as well as for swimming efficiency. Furthermore, there were no differences between girls and boys in free swim and with sensors for all variables. Swimming with the Aquanex System seems not to impose constraints in the mechanics and efficiency of young swimmers, despite differences in swimming performance and v.

Numerical and experimental methods used to evaluate active drag in swimming: A systematic narrative review

Introduction: In swimming, it is necessary to understand and identify the main factors that are important to reduce active drag and, consequently, improve the performance of swimmers. However, there is no up-to-date review in the literature clarifying this topic. Thus, a systematic narrative review was performed to update the body of knowledge on active drag in swimming through numerical and experimental methods.

Methods: To determine and identify the most relevant studies for this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was used.

Results: 75 studies related to active drag in swimming and the methodologies applied to study them were analyzed and kept for synthesis. The included studies showed a high-quality score by the Delphi scale (mean score was 5.85 ± 0.38). Active drag was included in seven studies through numerical methods and 68 through experimental methods. In both methods used by the authors to determine the drag, it can be concluded that the frontal surface area plays a fundamental role. Additionally, the technique seems to be a determining factor in reducing the drag force and increasing the propulsive force. Drag tends to increase with speed and frontal surface area, being greater in adults than in children due to body density factors and high levels of speed. However, the coefficient of drag decreases as the technical efficiency of swimming increases (i.e., the best swimmers (the fastest or most efficient) are those with the best drag and swimming hydrodynamics efficiency).

Conclusion: Active drag was studied through numerical and experimental methods. There are significantly fewer numerical studies than experimental ones. This is because active drag, as a dynamical phenomenon, is too complex to be studied numerically. Drag is greater in adults than in children and greater in men than in women across all age groups. The study of drag is increasingly essential to collaborate with coaches in the process of understanding the fundamental patterns of movement biomechanics to achieve the best performance in swimming. Although most agree with these findings, there is disagreement in some studies, especially when it is difficult to define competitive level and age. The disagreement concerns three main aspects: 1) period of the studies and improvement of methodologies; 2) discrimination of methodologies between factors observed in numerical vs. experimental methods; 3) evidence that drag tends to be non-linear and depends on personal, technical, and stylistic factors. Based on the complexity of active drag, the study of this phenomenon must continue to improve swimming performance.

Reliability of the active drag assessment using an isotonic resisted sprint protocol in human swimming

The purpose of the presents study was to investigate the reliability of the active drag (D_a) assessment using the velocity perturbation method (VPM) with different external resisted forces. Eight male and eight female swimmers performed 25 m sprints with five isotonic loads (1–2–3–4–5 kg for females; 1–3–5–7–9 kg for males), which were repeated twice on different days. The mean velocity and semi-tethered force were computed for each condition, and the free-swimming maximum velocity was estimated with load-velocity profiling. From the obtained variables, D_a at the maximum free-swimming condition was calculated using VPM. Absolute and typical errors and the intra-class correlation (ICC) were calculated to assess test–retest reliability. 95% confidence interval (95% CI) lower bound of ICC was larger than 0.75 in 3, 4 (females only) and 5 kg trials in both sexes (corresponding to 37–60 N additional resistance; all p < 0.001), which also showed small absolute and relative typical errors (≤ 2.7 N and ≤ 4.4%). In both sexes, 1 kg load trial (16–17 N additional resistance) showed the lowest reliability (95% CI of ICC; − 0.25–0.83 in males and 0.07–0.94 in females). These results suggested that a tethered force of 37–60 N should be used to assess D_a using VPM.

Young Swimmers' Classification Based on Performance and Biomechanical Determinants: Determining Similarities Through Cluster Analysis

The aim of this study was to classify and identify young swimmers' performance, and biomechanical determinant factors, and understand if both sexes can be clustered together. Thirty-eight swimmers of national level (22 boys: 15.92 ± 0.75 years and 16 girls: 14.99 ± 1.06 years) were assessed. Performance (swim speed at front crawl stroke) and a set of kinematic, efficiency, kinetic, and hydrodynamic variables were measured. Variables related to kinetics and efficiency (p < .001) were the ones that better discriminated the clusters. All three clusters included girls. Based on the interaction of these determinant factors, there are girls who can train together with boys. These findings indicate that not understanding the importance of the interplay between such determinants may lead to performance suppression in girls.

Numerical simulations of a swimmer's head and cap wearing different types of goggles

The aim of this study was to analyse the effect of swimming goggles on swimming hydrodynamics by numerical simulations. An elite swimmer volunteered for this research. The swimmer's head was scanned both without goggles, and while wearing 3 different types of goggles (Nikko, Ankor and Swedish). Numerical simulations were conducted at 2 m/s with the Fluent code. The condition without goggles showed the highest viscous drag (1.65 N), followed by the Ankor (1.64 N), Swedish (1.63 N) and Nikko (1.62 N) goggles, respectively. The highest pressure drag was found in the situation without goggles (11.34 N), followed by the Ankor (10.87 N), Nikko (10.78 N) and Swedish (10.20 N) goggles. The condition without goggles presented the highest total drag (12.99 N), followed by the Ankor (12.52 N), Nikko (12.40 N) and Swedish (11.83 N) goggles. Thus, Swedish goggles yields the best hydrodynamics, followed by the Nikko and Ankor goggles and lastly without goggles. Thus, goggles minimise the swimmer's drag comparing to not wearing any. The design of the goggles may impose varying drag forces and therefore it is advised to use goggles at least in competition.

Biophysical Follow-up of Age-Group Swimmers During a Traditional Three-Peak Preparation Program

Zacca, R, Azevedo, R, Ramos, VR, Abraldes, JA, Vilas-Boas, JP, Castro, FAdS, Pyne, DB, and Fernandes, RJ. Biophysical follow-up of age-group swimmers during a traditional three-peak preparation program. J Strength Cond Res 34(9): 2585-2595, 2020-The aim of this study was to quantify changes and contributions of bioenergetic, technique, and anthropometric profiles across a traditional 3-peak swimming season. Twenty-four age-group swimmers (11 boys: 15 years 6 months ± 1 year 1 month; 13 girls: 14 years 5 months ± 10 months) of equal maturational stage were monitored through a 400-m test in front crawl (T400). Bioenergetic, technique, and anthropometric characteristics were compared before and after macrocycles I, II and III. Sex interaction was verified only for amplitude of the fast oxygen uptake component and height (moderate). Multiple linear regressions and principal component analysis were used to identify the most influential variables and the relative contribution of each domain (bioenergetics, technique, and anthropometrics) to changes in swimming performance of T400. The relative contributions for the performance of T400 after macrocycles I, II, and III were, respectively, 6, 18, and 27% for bioenergetics, 88, 69, and 54% for technique, and 6, 13, and 20% for anthropometrics. Technique was the biggest contributor (71%) for changes in the performance of T400 over the training season, followed by bioenergetics (17%) and anthropometrics (12%). Technique played the main role during the competitive season, regardless of gradual increase in the contribution of bioenergetics and anthropometrics. Despite that, bioenergetics and technique are closely connected, thus a powerful and endurable metabolic base and cannot be overlooked. Changes and contribution of bioenergetics, technique, and anthropometrics on age-group swimmers' performance over a traditional 3-peak swimming season could be described by the T400 swimming test, providing a comprehensive biophysical overview of the main contributors to swimming performance.

Relationship between thrust, anthropometrics, and dry-land strength in a national junior swimming team

Objectives: This study aimed to (i) assess an anthropometric and thrust inter-limb asymmetry, and; (ii) determine the contribution of anthropometrics, and dry-land upper-body strength and power to the thrust of talented adolescent swimmers. Methods: Eighteen talented adolescent swimmers (12 boys and 6 girls: 15.81 ± 1.62 years old) were evaluated. A set of anthropometric, dry-land upper-body strength and power, and in-water thrust were assessed. Results: Despite the fact that the dominant side presented higher values in anthropometrics (except for the hand surface area) and thrust, non-significant inter-limb differences were found. The symmetry index indicated a symmetry between upper-limbs. Hierarchical linear modeling retained as main predictors of each upper-limb thrust the respective hand surface area (dominant upper limb: estimate = 0.293, 95CI: 0.117; 0.469, p = 0.005; non-dominant upper limb: estimate = 0.295, 95CI: 0.063; 0.526, p = 0.025). The full stroke cycle retained the upper-body dry-land strength as main predictor (estimate = 0.397, 95CI: 0.189; 0.605, p = 0.002). Conclusion: The hand surface area and upper-body strength were the main predictors of each upper-limb and full stroke cycle thrust, respectively. Hence, coaches and practitioners should aim to carefully maximize the hand surface area (by finger spreading) while performing the stroke, as well as dry-land upper-body strength in order to enhance the performance.

The Influence of the Coaches' Demographics on Young Swimmers' Performance and Technical Determinants

The purpose of this study was to understand the relationship between the coaches’ demographics (academic degree and/or coaching level and/or coaching experience) and young swimmers’ performance and technical ability. The sample was composed by 151 young swimmers (75 boys and 76 girls: 13.02 ± 1.19 years old, 49.97 ± 8.77 kg of body mass, 1.60 ± 0.08 m of height, 1.66 ± 0.09 m of arm span), from seven different clubs. Seven coaches (one per club) were responsible for the training monitoring. Performance and a set of biomechanical variables related to swim technique and efficiency were assessed. The swimmers’ performance was enhanced according to the increase in the coaches’ academic degree (1: 75.51 ± 10.02 s; 2: 74.55 ± 9.56 s; 3: 73.62 ± 7.64 s), coaching level (1: 76.79 ± 11.27 s; 2: 75.06 ± 9.31 s; 3: 73.65 ± 8.43 s), and training experience (≤5-y training experience: 75.44 ± 9.57 s; >5-y training experience: 74.60 ± 9.54 s). Hierarchical linear modeling retained all coaches’ demographics characteristics as main predictors (being the academic degree the highest: estimate = -1.51, 95% confidence interval = -0.94 to -2.08, p = 0.014). Hence, it seems that an increase in the demographics of the coaches appears to provide them with a training perspective more directed to the efficiency of swimming. This also led to a higher performance enhancement.

Upper-limb kinematics and kinetics imbalances in the determinants of front-crawl swimming at maximal speed in young international level swimmers

Short-distance swimmers may exhibit imbalances in their upper-limbs’ thrust (differences between the thrust produced by each upper-limb). At maximal speed, higher imbalances are related to poorer performances. Additionally, little is known about the relationship between thrust and swim speed, and whether hypothetical imbalances exist in the speed achieved while performing each upper-limb arm-pull. This could be a major issue at least while swimming at maximal speed. This study aimed to: (1) verify a hypothetical inter-upper limb difference in the determinants related to front-crawl at maximal swim speed, and; (2) identify the main predictors responsible for the swim speed achieved during each upper-limb arm-pull. Twenty-two male swimmers of a national junior swim team (15.92 ± 0.75 years) were recruited. A set of anthropometric, dry-land strength, thrust and speed variables were assessed. Anthropometrics identified a significant difference between dominant and non-dominant upper-limbs (except for the hand surface area). Dry-land strength presented non-significant difference (p < 0.05) between the dominant and non-dominant upper-limbs. Overall, thrust and speed variables revealed a significant difference (p < 0.05) between dominant and non-dominant upper-limbs over a 25 m time-trial in a short-course pool. Swimmers were not prone to maintaining the thrust and speed along the trial where a significant variation was noted (p < 0.05). Using multilevel regression, the speed achieved by each upper-limb identified a set of variables, with the peak speed being the strongest predictor (dominant: estimate = 0.522, p < 0.001; non-dominant: estimate = 0.756, p < 0.001). Overall, swimmers exhibit significant differences between upper-limbs determinants. The upper-limb noting a higher dry-land strength also presented a higher thrust, and consequently higher speed. Coaches should be aware that sprint swimmers produce significant differences in the speed achieved by each one of their upper-limbs arm-pull.

How does 11-week detraining affect 11-12 years old swimmers' biomechanical determinants and its relationship with 100 m freestyle performance?

The aim of this study was to analyse the detraining process that occurs during a season break, and its influence on the performance, anthropometrics, and biomechanics of young swimmers. The sample included 54 young swimmers (22 boys: 12.79 ± 0.71 years; 32 girls: 11.78 ± 0.85 years). Performance for the 100 m freestyle and anthropometric and biomechanical variables were evaluated as main determinants. Performance impaired significantly for boys (2.17%) and girls (1.91%). All anthropometric variables increased between moments of assessment for boys and girls. Overall, the boys enhanced all biomechanical variables during the detraining period, and girls showed mixed results. For both sexes, the stroke index was the variable with the highest increase (boys: Δ = 16.16%; d = 0.89; p = 0.001; girls: Δ = 19.51%; d = 1.06; p = 0.002). Hierarchical linear modelling showed that the height retained the amount of impairment in the performance. One unit of increase in the height (cm) led to less 0.41 s impairment in the performance. Present data indicated that during an 11-weeks detraining period, young swimmers impaired their performance, but the determinant factors showed an impaired relationship. This increase in the determinant factors is mainly related to the increase in the swimmers' anthropometrics. Moreover, the increase in height was responsible for retaining the performance impairment.

Multigenerational performance development of male and female top-elite swimmers-A global study of the 100 m freestyle event

BACKGROUND

The present study investigated longitudinally the performance development of a multigenerational sample of competitive swimmers. The aim of the study was to provide unique insight into the junior toward senior performance development of those few who reached top-elite level. Season Best Times (SBT) of 100 m freestyle performance of international swimmers, (1.305 males, aged 12-26 and 1.841 females, aged 12-24) competing in at least five seasons between 1993 and 2018, were corrected for the prevailing world record (WR). Swim performance was defined as a relative measure: relative Season Best Time=(SBT/WR) × 100. Based on rSBT, four performance groups were defined: top-elite, elite, sub-elite, and high-competitive.

RESULTS

Univariate analyses of variance showed that male top-elite swimmers outperformed high-competitive swimmers from the age of 12, sub-elite swimmers from the age of 14 and elite swimmers from the age of 18 while female top-elite swimmers outperformed high-competitive and sub-elite swimmers from the age of 12 and elite swimmers from the age of 14 (P < .05). Frequency analysis showed that male top-elite swimmers for the first time achieved top-elite level between the 17 and 24 years old (mean age of 21) while female top-elite swimmers started to perform at top-elite level between the 14 and 24 years old (mean age of 18).

CONCLUSION

Male and female top-elite swimmers are characterized by a high-performance level from 12 years on and progressively outperform swimmers from similar age. However, this goes together with a large variety in the individual pathways toward top-elite level within and between sexes.

Monitoring Changes Over a Training Macrocycle in Regional Age-Group Swimmers

Our aim was to analyze physiological, kinematical and performance changes induced by swimming training in regional age‐group athletes. Subjects (15.7 ± 2.2 years old) performed a 4 x 50‐m front‐crawl test at maximal velocity (10 s rest interval) in weeks 2, 4, 9 and 12 of a 15‐week macrocycle. Descriptive statistics were used and the percentage of change and smallest worthwhile change (moderate, 0.6‐1.2, and large, > 1.2) were measured. Lactate concentration in the third, seventh and twelfth minute of recovery decreased significantly between weeks 2‐9 (14.1, 15.7 and 17.6%) and increased between weeks 9‐12 (18.2, 18.6 and 19.8%), with the HR presenting only trivial variations during the training period. Stroke length showed a large decrease in the first 50‐m trial between weeks 4‐9 (6.2%) and a large increase between weeks 9‐12 (3.1%). The stroke rate (in all 50‐m trials) increased significantly between weeks 4‐9 (3‐ 7%) and the stroke index had a moderate to large increase in the first and third 50‐m trial (3.6 and 7.1%, respectively) between weeks 9‐12. The overall time decreased by 1.1% between weeks 2‐12, being more evident after week 4. We concluded that physiological, kinematical and performance variables were affected by the period of training in regional age‐group swimmers.

Physiological and Biomechanical Evaluation of a Training Macrocycle in Children Swimmers

Physiological responses related to 400-m front crawl performance were examined in a 11-week training macrocycle in children 11.6 ± 1.2 years old. Fourteen girls and twenty-nine boys completed a maximum intensity 400-m test, at the beginning (Τ1) and at the end of four weeks of general preparation (Τ2), four weeks of specific preparation (Τ3), and three weeks of the competitive period (Τ4). Blood lactate (La), blood glucose (Glu) and heart rate were measured post effort. Stroke rate (SR), stroke length (SL) and stroke index (SI) were measured during the test. The 400-m time was decreased at T2, T3, and T4 compared to T1 by 4.2 ± 4.9, 7.5 ± 7.0, and 8.6 ± 7.3% (p < 0.05) and at T3 and T4 compared to T2 by 3.1 ± 4.3 and 4.2 ± 4.6%, respectively (p < 0.05). La was not different between tests (p > 0.05) and Glu was decreased at T3 compared to other testing moments (p < 0.05). SR, SL, and SI were higher at T3 and T4 compared to T1 (p < 0.05). SL and SI were also increased at T4 compared to T2 (p < 0.05). Performance changes from T1 to T2 were related to SL and SI changes (r = 0.45 and 0.83, p < 0.05), and subsequent changes between T2 to T3 were related to SR, SI, La, and Glu changes (r = 0.48, 0.68, 0.34, and 0.42, p < 0.05). Performance change from T3 to T4 was related to SL, SI, and La modifications (r = 0.34, 0.70, and 0.53, p < 0.05). Performance gains may be related to various biomechanical or physiological changes according to training macrocycle structure.

Skillful Swimming in Age-Groups Is Determined by Anthropometrics, Biomechanics and Energetics

The aim was to compare the anthropometrics, biomechanics and energetics in young swimmers of different competitive levels. Seventy-five boys aged between 11 and 13 years-old with a broad range of performances were ranked based on their personal best time in the men’s 100m freestyle event and then split-up into three tiers (Tier-1, i.e., top-tier, best performers; Tier-2, mid-tier; Tier-3, lower-tier). A set of anthropometric features was measured (height, body mass, arm span and trunk transverse surface area). Stroke kinematics (speed, stroke length, stroke frequency) was assessed by a Speedo-meter. Swim efficiency was then estimated (stroke index, speed fluctuation, Froude efficiency). Hydrodynamics assessment encompassed the estimation of active drag and drag coefficient by velocity perturbation method and a set of dimensionless numbers (Froude, hull speed, Reynolds). Mechanical power (to overcome drag, transfer of kinetic energy to water, external power) and power input were derived. There was a significant variation with moderate effect sizes in all anthropometric features but the trunk transverse surface area. Tier-1 swimmers were taller, heavier and with longer limbs than remaining counterparts. There were also significant variations in the stroke kinematics with moderate-large effect sizes. Tier-1 swimmers showed higher stroke frequency, stroke length, speed, stroke index and propelling efficiency but lower speed fluctuations. Reynold number, Froude number and hull speed were significantly higher in Tier-1 swimmers, denoting large effect sizes. The mechanical power and power input delivered were significantly higher in tier-1 swimmers, showing moderate effect sizes. As a conclusion, it was noted significant variations, with moderate-large effect sizes, among the three tiers, for the vast majority of the selected variables. The better performances by tier-1 swimmers were related to their anthropometrics, biomechanics and energetics.

Autonomic modulations of heart rate variability are associated with sports injury incidence in sprint swimmers

OBJECTIVES

Young athletes' participation in competitive sports is becoming increasingly common, and this increased involvement raises concerns about the occurrence of overtraining and sports injuries. Since these issues are poorly understood, this study analyzed heart rate variability, stress/recovery relationship, and sports injury incidence during a training macrocycle of young sprint and endurance swimmers.

METHODS

Thirty teenage swimmers (aged 12 to 17 years) were divided into two groups as follows: Sprint (n = 17) and Endurance (n = 13). Subjects were evaluated over 20 weeks, based on the following three schedules: general, specific, and competitive. In addition to heart rate variability and sports injury incidence, the Recovery-Stress-Questionnaire of Athletes was used to analyse stress/recovery states in athletes. All procedures were developed at the initial moment and at the end of each periodization step.

RESULTS

The Sprint group presented a reduced standard deviation of normal-normal beats (73.0 ± 6.6 vs. 54.1 ± 3.5 ms; p < 0.05) and root mean square of the successive differences (55.3 ± 6.2 vs. 42.0 ± 3.7 ms; p < 0.01) from the period of general preparation until the time of competition. Recovery-stress monitoring was affected only by the swimming training periodization (p < 0.05). During the general period, differences between recovery and stress scales were correlated directly with the root mean square of the successive differences (r = 0.576; p = 0.001), the standard deviation of instantaneous variability beat-to-beat (r = 0.521; p = 0.003) and the triangular index (r = 0.476; p = 0.008). Differences between general recovery and stress scales were inversely correlated with geometric indexes after the specific training period. Moreover, the Sprint group showed a higher incidence of sports injury than the Endurance group (0.0214 ± 0.0068 vs. 0.0136 ± 0.0050 cases/1000 hours).

CONCLUSION

Sprint training was associated with progressive activation of the sympathetic nervous system as well as a higher incidence of sports injury in comparison to endurance swimming during a training macrocycle.

The transfer of strength and power into the stroke biomechanics of young swimmers over a 34-week period

The purpose of this study was to learn the interplay between dry-land strength and conditioning, and stroke biomechanics in young swimmers, during a 34-week training programme. Twenty-seven swimmers (overall: 13.33 ± 0.85 years old; 11 boys: 13.5 ± 0.75 years old; 16 girls: 13.2 ± 0.92 years old) competing at regional- and national-level competitions were evaluated. The swimmers were submitted to a specific in-water and dry-land strength training over 34 weeks (and evaluated at three time points: pre-, mid-, and post-test; M1, M2, and M3, respectively). The 100-m freestyle performance was chosen as the main outcome (i.e. dependent variable). The arm span (AS; anthropometrics), throwing velocity (TV; strength), stroke length (SL), and stroke frequency (SF; kinematics) were selected as independent variables. There was a performance enhancement over time (M1 vs. M3: 68.72 ± 5.57 s, 66.23 ± 5.23 s; Δ = -3.77%; 95% CI: -3.98;-3.56) and an overall improvement of the remaining variables. At M1 and M2, all links between variables presented significant effects (p < .001), except the TV-SL and the TV-SF path. At M3, all links between variables presented significant effects (p ≤ .05). Between M1 and M3, the direct effect of the TV to the stroke biomechanics parameters (SL and SF) increased. The model predicted 89%, 88%, and 92% of the performance at M1, M2, and M3, respectively, with a reasonable adjustment (i.e. goodness-of-fit M1: χ²/df = 3.82; M2: χ²/df = 3.08; M3: χ²/df = 4.94). These findings show that strength and conditioning parameters have a direct effect on the stroke biomechanics, and the latter one on the swimming performance.

Butterfly Sprint Swimming Technique, Analysis of Somatic and Spatial-Temporal Coordination Variables

The aim of this study was to investigate somatic properties and force production of leg extensor muscles measured in the countermovement jump test (CMJ), as well as to analyse kinematic variables of sprint surface butterfly swimming. Thirty-four male competitive swimmers were recruited with an average age of 19.3 ± 1.83 years. Their average body height (BH) was 183.7 ± 5.93 cm, body fat content 10.8 ± 2.64% and body mass (BM) 78.3 ± 5.0 kg. Length measurements of particular body segments were taken and a counter movement jump (CMJ) as well as an all-out 50 m butterfly speed test were completed. The underwater movements of the swimmers’ bodies were recorded with a digital camera providing side-shots. We registered a significant relationship between body mass (r = 0.46), lean body mass (r = 0.48) and sprint surface butterfly swimming (VSBF). The anaerobic power measured in the CMJ test, total body length (TBL) as well as upper and lower extremity length indices did not influence swimming speed significantly. The temporal entry-kick index (the time ratio between the first kick and arm entry) significantly influenced VSBF (r = -0.45). Similarly, medium power of the coefficient was indicated between a) stroke rate kinematics (SR), b) duration of the first leg kick (LP1), c) air phase duration of arm recovery (Fly-arm), and VSBF (r = 0.40; r = 0.40 and r = 0.41, respectively). The entry-kick temporal index showed that, in the butterfly cycle, an appropriately early executed initial kick when compared to arm entry was associated with a longer arm propulsion phase, which in turn was associated with minimizing resistive gliding phases and enabled relatively longer and less resistive air arm recovery (higher value of the fly-arm index). The higher value of SR kinematic was another important element of the best butterfly results in this study.

The changes in classical and nonlinear parameters after a maximal bout to elicit fatigue in competitive swimming

The aim was to assess the effect of fatigue on linear and nonlinear parameters in swimming. Twenty-four fitness-oriented swimmers performed a maximal bout of 100 m at front-crawl to elicit fatigue. Before (pre-) and immediately after (post-test) the bout, participants swam an all-out 25 m to derive the speed fluctuation (dv), approximate entropy (ApEn) and fractal dimension (FD) from the speed-time series collected by a speedo-meter. Swim speed was 10.85% slower in the post-test than in the pre-test (p < .001, η² = 0.72). There was an effect of the fatigue on the dv with a moderate effect size. The dv increased shifting the 95CI band from 0.116-0.134 to 0.140-0.161. The ApEn showed non-significant variations between the pre- and post-test having the 95CI of pre- and post-test overlapped (pre: 0.659-0.700; post: 0.641-0.682). The FD showed as well a significant variation (the 95CI moved from 1.954-1.965 to 1.933-1.951). It can be concluded that in swimming there are changes in classical and nonlinear parameters under fatigue.

Comparison of Classical Kinematics, Entropy, and Fractal Properties As Measures of Complexity of the Motor System in Swimming

The aim of this study was to compare the non-linear properties of the four competitive swim strokes. Sixty-eight swimmers performed a set of maximal 4 × 25 m using the four competitive swim strokes. The hip's speed-data as a function of time was collected with a speedo-meter. The speed fluctuation (dv), approximate entropy (ApEn) and the fractal dimension by Higuchi's method (D) were computed. Swimming data exhibited non-linear properties that were different among the four strokes (14.048 ≤ dv ≤ 39.722; 0.682 ≤ ApEn ≤ 1.025; 1.823 ≤ D ≤ 1.919). The ApEn showed the lowest value for front-crawl, followed by breaststroke, butterfly, and backstroke (P < 0.001). Fractal dimension and dv had the lowest values for front-crawl and backstroke, followed by butterfly and breaststroke (P < 0.001). It can be concluded that swimming data exhibits non-linear properties, which are different among the four competitive swimming strokes.

A Comparison of Experimental and Analytical Procedures to Measure Passive Drag in Human Swimming

The aim of this study was to compare the swimming hydrodynamics assessed with experimental and analytical procedures, as well as, to learn about the relative contributions of the friction drag and pressure drag to total passive drag. Sixty young talented swimmers (30 boys and 30 girls with 13.59±0.77 and 12.61±0.07 years-old, respectively) were assessed. Passive drag was assessed with inverse dynamics of the gliding decay speed. The theoretical modeling included a set of analytical procedures based on naval architecture adapted to human swimming. Linear regression models between experimental and analytical procedures showed a high correlation for both passive drag (Dp = 0.777*Df+pr; R2 = 0.90; R2a = 0.90; SEE = 8.528; P<0.001) and passive drag coefficient (CDp = 1.918*CDf+pr; R2 = 0.96; R2a = 0.96; SEE = 0.029; P<0.001). On average the difference between methods was -7.002N (95%CI: -40.480; 26.475) for the passive drag and 0.127 (95%CI: 0.007; 0.247) for the passive drag coefficient. The partial contribution of friction drag and pressure drag to total passive drag was 14.12±9.33% and 85.88±9.33%, respectively. As a conclusion, there is a strong relationship between the passive drag and passive drag coefficient assessed with experimental and analytical procedures. The analytical method is a novel, feasible and valid way to gather insight about one's passive drag during training and competition. Analytical methods can be selected not only to perform race analysis during official competitions but also to monitor the swimmer's status on regular basis during training sessions without disrupting or time-consuming procedures.