Growing up and reaching for the top: A longitudinal study on swim performance and its underlying characteristics in talented swimmers

The present study strived to gain a more profound understanding of the distinctions in development between swimmers who are considered to be on track to the elite level at late junior age (males aged 16; females aged 15) compared to those who are not. In this effort, swimmers were followed during their pubertal years (males aged 13-15; females aged 12-14), which marks a period when performance development aligns with maturation. Longitudinal data of 90 talented sprint and middle-distance swimmers on season best times (SBT) and underlying performance characteristics (anthropometrics, maximal swimming velocity, stroke index [SI] and countermovement jump [CMJ]) were collected over three swimming seasons. Based on their SBT at late junior age (males aged 16; females aged 15), swimmers were classified as high-performing late juniors or lower-performing late juniors. Retrospectively studying these swimmers, we found that all but two high-performing late juniors were already on track to the elite level at early junior age (males aged 13; females aged 12), evidenced with faster SBT throughout puberty compared to their lower-performing peers (p < 0.05). Independent sample t-tests revealed that high-performing late juniors significantly outscored their lower-performing peers when they were early juniors on maximal swimming velocity (males aged 13-15 and females aged 12-14), SI (males aged 13 and 14; females aged 12), CMJ (females aged 14) and height (females aged 13 and 14, p < 0.05). Additionally, multilevel models showed faster rates of development for high-performing late juniors on maximal swimming velocity (males and females) and SI (males) compared to lower-performing peers throughout puberty (p < 0.05). Higher initial levels of SBT and underlying performance characteristics at early junior age as well as the faster rates of development on SBT, maximal swimming velocity and SI (males only) during the pubertal years, may be crucial factors in maintaining the trajectory towards the elite level after puberty.

Identification of key somatic features that are common and the ones that differ between swim strokes through allometric modeling

Introduction

The aim of this study was to explore which key somatic features are common to four swim strokes and medley, and specifically to identify which characteristics benefit only specific strokes.

Methods

The sample was composed of 130 swimmers (95 males aged 19.5 ± 2.9 years and 35 females aged 18.4 ± 2.8 years). A set of anthropometric variables was used to predict swimming speed in the four swimming strokes and medley.

Results

A multiplicative model with allometric body size components was used to identify the demographic and anthropometric predictors of swimming speed. Trunk height and waist circumference were the only variables significantly different among swimming strokes (p < 0.05). Associations between swimming speed and arm length were similar in breaststroke and medley, and in freestyle, backstroke and butterfly (R2 = 60.9%). The model retained as swimming speed predictors the age2, upper body circumference, hand breadth, waist circumference, and subscapular skinfold thickness (these last two had negative associations).

Conclusion

All these predictors were common to all four swim strokes and medley. Arm length was also retained as a significant predictor, but this one varied significantly between the four different swim strokes and medley. These findings highlight the importance of having a "V-shape" trunk, longer upper limbs, and large hands as predictors of swimming performance.

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.

The Effect of Growth and Body Surface Area on Cardiopulmonary Exercise Testing: A Cohort Study in Preadolescent Female Swimmers

BACKGROUND

The performance of young swimmers is the result of a multifactorial process that is influenced by anthropometric characteristics and biological maturation. The purpose of our study was to investigate the effect of stages of biological maturation and body surface area on cardiopulmonary fitness indicators in preadolescent female swimmers, for whom menstruation has not started.

METHODS

Thirty female preadolescent swimmers (age 13.4 ± 1.0 years) participated in this study. We recorded anthropometric and morphological characteristics, stages of biological maturation, and pulmonary function parameters, and the swimmers underwent cardiopulmonary exercise testing.

RESULTS

The cut-off was set for body surface area (BSA) at 1.6 m2 and for biological maturation stages at score 3. The BSA results showed differences in variabilities in maximal effort oxygen pulse (p < 0.001), oxygen uptake (p < 0.001), ventilation (p = 0.041), tidal volume (p < 0.001), and oxygen breath (p < 0.001). Tanner stage score results showed differences in variabilities in maximal effort breath frequency (p < 0.001), tidal volume (p = 0.013), and oxygen breath (p = 0.045). Biological maturation stages and BSA were correlated during maximal effort with oxygen breath (p < 0.001; p < 0.001), oxygen uptake (p = 0.002; p < 0.001), and oxygen pulse (p < 0.001; p < 0.001).

CONCLUSIONS

In conclusion, the findings of our study showed that the girls who had a smaller body surface area and biological maturation stage presented lower values in maximal oxygen uptake and greater respiratory work.

Interaction of Kinematic, Kinetic, and Energetic Predictors of Young Swimmers' Speed

PURPOSE

The aim of this study was to assess the interaction of kinematic, kinetic, and energetic variables as speed predictors in adolescent swimmers in the front-crawl stroke.

DESIGN

Ten boys (mean age [SD] = 16.4 [0.7] y) and 13 girls (mean age [SD] = 14.9 [0.9] y) were assessed.

METHODS

The swimming performance indicator was a 25-m sprint. A set of kinematic, kinetic (hydrodynamic and propulsion), and energetic variables was established as a key predictor of swimming performance. Multilevel software was used to model the maximum swimming speed.

RESULTS

The final model identified time (estimate = -0.008, P = .044), stroke frequency (estimate = 0.718, P < .001), active drag coefficient (estimate = -0.330, P = .004), lactate concentration (estimate = 0.019, P < .001), and critical speed (estimate = -0.150, P = .035) as significant predictors. Therefore, the interaction of kinematic, hydrodynamic, and energetic variables seems to be the main predictor of speed in adolescent swimmers.

CONCLUSIONS

Coaches and practitioners should be aware that improvements in isolated variables may not translate into faster swimming speed. A multilevel evaluation may be required for a more effective assessment of the prediction of swimming speed based on several key variables rather than a single analysis.

Performance Tiers within a Competitive Age Group of Young Swimmers Are Characterized by Different Kinetic and Kinematic Behaviors

The present study aimed to analyze swimmers' in-water kinetic and kinematic behaviors according to different swimming performance tiers within the same age group. An amount of 53 highly trained swimmers (girls and boys: 12.40 ± 0.74 years) were split up into 3 tiers based on their personal best performance (i.e., speed) in the 50 m freestyle event (short-course): lower-tier (1.25 ± 0.08 m·s^-1); mid-tier (1.45 ± 0.04 m·s^-1); and top-tier (1.60 ± 0.04 m·s^-1). The in-water mean peak force was measured during a maximum bout of 25 m front crawl using a differential pressure sensors system (Aquanex system, Swimming Technology Research, Richmond, VA, USA) and defined as a kinetic variable, while speed, stroke rate, stroke length, and stroke index were retrieved and considered as kinematic measures. The top-tier swimmers were taller with a longer arm span and hand surface areas than the low-tier, but similar to the mid-tier. While the mean peak force, speed and efficiency differed among tiers, the stroke rate and stroke length showed mixed findings. Coaches should be aware that young swimmers belonging to the same age group may deliver different performance outcomes due to different kinetic and kinematic behaviors.

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.

Monitoring weekly progress of front crawl swimmers using IMU-based performance evaluation goal metrics

Technical evaluation of swimming performance is an essential factor in preparing elite swimmers for their competitions. Inertial measurement units (IMUs) have attracted much attention recently because they can provide coaches with a detailed analysis of swimmers’ performance during training. A coach can obtain a quantitative and objective evaluation from IMU. The purpose of this study was to validate the use of a new phase-based performance assessment with a single IMU worn on the sacrum during training sessions. Sixteen competitive swimmers performed five one-way front crawl trials at their maximum speed wearing an IMU on the sacrum. The coach recorded the lap time for each trial, as it remains the gold standard for swimmer’s performance in competition. The measurement was carried out once a week for 10 consecutive weeks to monitor the improvement in the swimmers’ performance. Meaningful progress was defined as a time decrease of at least 0.5 s over a 25 m lap. Using validated algorithms, we estimated five goal metrics from the IMU signals representing the swimmer’s performance in the swimming phases (wall push-off, glide, stroke preparation, free-swimming) and in the entire lap. The results showed that the goal metrics for free-swimming phase and the entire lap predicted the swimmer’s progress well (e.g., accuracy, precision, sensitivity, and specificity of 0.91, 0.89, 0.94, and 0.95 for the lap goal metric, respectively). As the goal metrics for initial phases (wall push-off, glide, stroke preparation) achieved high precision and specificity (≥0.79) in progress detection, the coach can use them for swimmers with satisfactory free-swimming phase performance and make further improvements in initial phases. Changes in the values of the goal metrics have been shown to be correlated with changes in lap time when there is meaningful progress. The results of this study show that goal metrics provided by the phase-based performance evaluation with a single IMU can help monitoring swimming progress. Average velocity of the lap can replace traditional lap time measurement, while phase-based goal metrics provide more information about the swimmer’s performance in each phase. This evaluation can help the coach quantitatively monitor the swimmer’s performance and train them more efficiently.

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.

Young Swimmers' Anthropometrics, Biomechanics, Energetics, and Efficiency as Underlying Performance Factors: A Systematic Narrative Review

Introduction: In youth swimming, researchers are interested in understanding how anthropometry and parameters related to swimming technique (biomechanics, energetics, and efficiency) influence the performance. However, there is not any review in the literature that consolidates the body of knowledge of this topic. The objective of this study was to review systematically the current body of work on the influence of determinant factors related to swimming technique (biomechanics, energetics, and efficiency) and anthropometry in the young performance of swimmers.

Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to identify relevant studies.

Results: After screening, 240 studies were analyzed and 59 related to swimming performance, and its determinant factors were retained for synthesis. Studies revealed a high-quality index by PEDro scale (mean score was 7.17 ± 1.40). Twenty-five studies were longitudinal designs and the remaining 34 cross-sectional designs. Most of the studies (N = 39, 66.1%) reported concurrently two or more determinant factors (anthropometrics, biomechanics, energetics, and efficiency).

Conclusion: Youth swimming research relies on a multifactorial assessment. From the synthesis, it is possible to conclude that the performance of young swimmers is characterized by a multifactorial, holistic, and dynamic phenomenon. Better performance has always been related to better swimming technique and higher anthropometrics. This suggests that both anthropometrics (i.e., nature) and training (i.e., nurture) play key roles in the swimming performance of young swimmers.

Data Modeling for Inter- and Intra-Individual Stability of Young Swimmers' Performance: A Longitudinal Cluster Analysis

Purpose: The aims of this study were to classify, identify and follow-up young swimmers' performance and its biomechanical determinants during two competitive seasons (in seven different moments of assessment-M), and analyze the individual variations of each swimmer. Method: Thirty young swimmers (14 boys: 12.70 ± 0.63 years-old; 16 girls: 11.72 ± 0.71 years-old) were recruited. A set of anthropometric, kinematic, efficiency, hydrodynamic and mechanical power variables were assessed. Results: The cluster solution (i.e., number of ideal clusters for this sample) resulted in three clusters, which were named as: cluster 1 ("talented"), cluster 2 ("proficient"), and cluster 3 ("non-proficient"). The performance improved between moments of assessment in all clusters (cluster 1-M1: 68.07 ± 6.62s vs M7: 61.46 ± 3.43s; cluster 2-M1: 73.14 ± 4.87s vs M7: 65.33 ± 2.97s; cluster 3-M1: 82.60 ± 4.18s vs M7: 70.09 ± 3.48s). Anthropometric features also increased between moments of assessment, and remaining biomechanical variables (kinematic, efficiency, hydrodynamic and mechanical power) also increased between M1 and M7, in all clusters. Cluster 1 increased their swimmer's membership between M1 and M7 (4 to 11), cluster 2 decreased (12 to 5), and cluster 3 maintained (14). Conclusion: It can be concluded that the cluster formation depends on different determinant factors during two competitive seasons, and young swimmers are prone to change from one cluster to another over this period of time.

Discerning excellence from mediocrity in swimming: New insights using Bayesian quantile regression

AbstractPurpose: Previous research has captured point estimates for population means of somatic variables associated with swimming speed across strokes, but have not determined if predictors of swimming speed operate the same at the upper tails of the distribution (τ = 0.9) as they do at the median levels (τ = 0.5) and lower levels (τ = 0.1). Method: Three hundred sixty-three competitive-level swimmers (male [n = 202]; female [n = 161]) participated in the study. To identify key somatic variables associated with 100-m swimming across and between strokes controlling for age, we used a Bayesian allometric quantile regression model, refined using Bayes Factors and Leave-one-out cross validation. Results: High probabilities (>99%) were found for arm-span, seated-height and shoulder-breadth being the strongest somatic predictors across strokes. For individual strokes, Bayesian quantile regression demonstrated that the relative importance of predictors differs across quantiles. For swimmers in the 0.9 quartile, shoulder-breadth is a more important than height for front-crawl, wide shoulders are important for breaststroke swimmers but can be detrimental when combined with narrow hips, seated-height and hip-width are important for backstroke swimming speed, and calf girth for butterfly. Conclusion: These results highlight the importance of considering key somatic variables for talent identification in swimming and ensure young swimmers focus on strokes compatible with their somatic structure. The most important new insight is that predictors differ for the best swimmers compared to average or poorer swimmers. This has implications beyond swimming, pointing to the importance of considering the upper tails of distributions in performance and talent identification contexts.

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.

Quality versus Quantity Debate in Swimming: Perceptions and Training Practices of Expert Swimming Coaches

The debate over low-volume, high-intensity training versus high-volume, low-intensity training, commonly known as Quality versus Quantity, respectively, is a frequent topic of discussion among swimming coaches and academics. The aim of this study was to explore expert coaches’ perceptions of quality and quantity coaching philosophies in competitive swimming and to investigate their current training practices. A purposeful sample of 11 expert swimming coaches was recruited for this study. The study was a mixed methods design and involved each coach participating in 1 semi-structured interview and completing 1 closed-ended questionnaire. The main findings of this study were that coaches felt quality training programmes would lead to short term results for youth swimmers, but were in many cases more appropriate for senior swimmers. The coaches suggested that quantity training programmes built an aerobic base for youth swimmers, promoted technical development through a focus on slower swimming and helped to enhance recovery from training or competition. However, the coaches continuously suggested that quantity training programmes must be performed with good technique and they felt this was a misunderstood element. This study was a critical step towards gaining a richer and broader understanding on the debate over Quality versus Quantity training from an expert swimming coaches’ perspective which was not currently available in the research literature.