To apply a new method to identify, classify, and follow up young swimmers based on their performance and its determinant factors over a season and analyze the swimmers' stability over a competitive season with that method. Fifteen boys and 18 girls (11.8±0.7 y) part of a national talent-identification scheme were evaluated at 3 different moments of a competitive season. Performance (ie, official 100-m freestyle race time), arm span, chest perimeter, stroke length, swimming velocity, speed fluctuation, coefficient of active drag, propelling efficiency, and stroke index were selected as variables. Hierarchical and k-means cluster analysis were computed. Data suggested a 3-cluster solution, splitting the swimmers according to their performance in all 3 moments. Cluster 1 was related to better performances (talented swimmers), cluster 2 to poor performances (nonproficient swimmers), and cluster 3 to average performance (proficient swimmers) in all moments. Stepwise discriminant analysis revealed that 100%, 94%, and 85% of original groups were correctly classified for the 1st, 2nd, and 3rd evaluation moments, respectively (0.11≤Λ≤0.80; 5.64≤χ2≤63.40; 0.001<P≤.68). Membership of clusters was moderately stable over the season (stability range 46.1-75% for the 2 clusters with most subjects). Cluster stability is a feasible, comprehensive, and informative method to gain insight into changes in performance and its determinant factors in young swimmers. Talented swimmers were characterized by anthropometrics and kinematic features.

The purpose of this study was to analyze the effect of gender and energetics on biomechanics and performance of masters swimmers over 1 season. Twenty-five masters swimmers (14 male and 11 female) were assessed 3 times (TP1, TP2, and TP3) during a season (male personal record in 200-m freestyle event: 173.00 ± 31.41 seconds: female personal record in 200-m freestyle event: 200.73 ± 25.02 seconds). An incremental 5 × 200-m step test was selected to evaluate velocity at 4 mmol·l⁻¹ of blood lactate concentration (v4), maximal blood lactate concentration after exercise (La(peak)), maximal oxygen uptake (V̇O2max), stroke frequency, stroke length (SL), stroke index (SI), and propelling efficiency of the arm stroke (η(p)). The 200-m freestyle performance and average swimming velocity (v200) were also monitored. Significant differences were observed between males and females for the 200-m freestyle performance, SL, SI, and La(peak). Performance (205.18 ± 24.47 seconds; 197.45 ± 20.97 seconds; 193.45 ± 18.12 seconds), SL (1.69 ± 0.17 m; 1.79 ± 0.13 m; 1.78 ± 0.15 m), SI (1.68 ± 0.31 m²·c⁻¹·s⁻¹; 1.83 ± 0.27 m²·c⁻¹·s⁻¹; 1.85 ± 0.27 m²·c⁻¹·s⁻¹), η(p) (0.32 ± 0.04; 0.33 ± 0.03; 0.33 ± 0.04), and V̇O2max (38.71 ± 3.44 ml·kg⁻¹·min⁻¹; 43.43 ± 3.71 ml·kg⁻¹·min⁻¹; 43.95 ± 7.02 ml·kg⁻¹·min⁻¹) have changed significantly throughout the season (TP1, TP2, and TP3, respectively) in female swimmers. In male, significant changes were found in η(p) (0.33 ± 0.07; 0.36 ± 0.05; 0.36 ± 0.06) and V̇O2max (41.65 ± 7.30 ml·kg⁻¹·min⁻¹; 45.19 ± 6.55 ml·kg⁻¹·min⁻¹; 50.19 ± 9.65 ml·kg⁻¹·min⁻¹) over the season (TP1, TP2, and TP3, respectively). Gender presented a significant effect on SL (TP2: η(p)² = 0.29; TP3: η(p)² = 0.37), SI (TP2: η(p)² = 0.25), and La(peak) (TP3: η(p)² = 0.42). v4 (TP1: η(p)² = 0.23), SL (TP1: η(p)² = 0.46), SI (TP1: η(p)² = 0.78; TP2: η(p)² = 0.37; TP3: η(p)² = 0.32), and η(p) (TP1: η(p)² = 0.28) had a significant effect on performance. Male masters swimmers have better performance, SL, SI, and La(peak) than female counterparts. Female masters swimmers enhanced significantly the 200-m freestyle performance over the season due to the improvement in swimming technique (SL, SI, and η(p)) and energetic factors (v4 and V̇O2max). Nonsignificant improvements were observed for the males' performance. Gender has a significant effect on SL, SI, and La(peak). Therefore, performance is more dependent on technical factors than energetics.

The aim was to develop a path-flow analysis model for young swimmers' performance based on biomechanical and energetic parameters, using structural equation modeling. Thirty-eight male young swimmers served as subjects. Performance was assessed by the 200-m freestyle event. For biomechanical assessment the stroke length, the stroke frequency and the swimming velocity were analyzed. Energetics assessment included the critical velocity, the stroke index and the propulsive efficiency. The confirmatory model explained 79% of swimming performance after deleting the stroke index-performance path, which was nonsignificant (SRMR = 0.06). As a conclusion, the model is appropriate to explain performance in young swimmers.

The main aim of this study was to investigate the effect of finger spread on the propulsive force production in swimming using computational fluid dynamics. Computer tomography scans of an Olympic swimmer hand were conducted. This procedure involved three models of the hand with differing finger spreads: fingers closed together (no spread), fingers with a small (0.32 cm) spread, and fingers with large (0.64 cm) spread. Steady-state computational fluid dynamics analyses were performed using the Fluent code. The measured forces on the hand models were decomposed into drag and lift coefficients. For hand models, angles of attack of 0 degrees, 15 degrees, 30 degrees, 45 degrees, 60 degrees, 75 degrees, and 90 degrees, with a sweep back angle of 0 degrees, were used for the calculations. The results showed that the model with a small spread between fingers presented higher values of drag coefficient than did the models with fingers closed and fingers with a large spread. One can note that the drag coefficient presented the highest values for an attack angle of 90 degrees in the three hand models. The lift coefficient resembled a sinusoidal curve across the attack angle. The values for the lift coefficient presented few differences among the three models, for a given attack angle. These results suggested that fingers slightly spread could allow the hand to create more propulsive force during swimming.

Countermovement jump (CMJ) has been extensively used in training; yet, limited and contradictory kinematic data are available for trained subjects. To our best knowledge, no other studies have evaluated the associations between force-time curve characteristics and CMJ in a large sample of trained athletes using a linear transducer. Thus, the aim of this study was to determine the association between force-time measures and CMJ performance collected with a linear transducer. Thirty-five trained athletes were asked to perform 3 maximal weighted CMJ using a linear transducer attached to a barbell (17 kg). The data indicated that the maximal rate of force development (RFD(max)) was strongly related to CMJ displacement (r = 0.809/0.807, p < 0.001) and also to the percentage of peak force (r = -0.823/-0.809, p < 0.001) at RFD(max). Velocity and displacement at RFD(max) were not correlated to CMJ height. It was therefore concluded that the percentage of PF applied at RFD(max) and RFD(max) were the best predictive variables for CMJ performance in this study.

This study aimed to analyse the effect of growth during a summer break on biomechanical profile of talented swimmers. Twenty-five young swimmers (12 boys and 13 girls) undertook several anthropometric and biomechanical tests at the end of the 2011-2012 season (pre-test) and 10 weeks later at the beginning of the 2012-2013 season (post-test). Height, arm span, hand surface area, and foot surface area were collected as anthropometric parameters, while stroke frequency, stroke length, stroke index, propelling efficiency, active drag, and active drag coefficient were considered as biomechanical variables. The mean swimming velocity during an all-out 25 m front crawl effort was used as the performance outcome. After the 10-week break, the swimmers were taller with an increased arm span, hand, and foot areas. Increases in stroke length, stroke index, propelling efficiency, and performance were also observed. Conversely, the stroke frequency, active drag, and drag coefficient remained unchanged. When controlling the effect of growth, no significant variation was determined on the biomechanical variables. The performance presented high associations with biomechanical and anthropometric parameters at pre-test and post-test, respectively. The results show that young talented swimmers still present biomechanical improvements after a 10-week break, which are mainly explained by their normal growth.

The aim of this study was to track and compare the changes of performance and energetic profile of male and female masters swimmers during a season. Eleven female (age: 34.7±7.3-y) and fourteen male (age: 35.6±7.4-y) with 4.2±3.7-y and 3.9±1.6-y of experience in masters, respectively, performed an all-out 200 m freestyle to evaluate total energy expenditure (Etot), aerobic (Aer), anaerobic lactic (AnL) and alactic (AnAl) contributions. The oxygen uptake (VO2) was measured immediately after the 200 m trial and the VO2 reached during the trial was estimated through the backward extrapolation of the O2 recovery curve. Fingertip capillary blood samples were collected before the 200 m trial and 3, 5, and 7 minutes after its end. Significant differences were observed between male (TP1:177.50±30.96s; TP2:174.79±29.08s; TP3:171.21±22.38s) and female (TP1:205.18±24.47s; TP2: 197.45±20.97s; TP3: 193.45±18.12s) for 200 m freestyle performance at the three time periods (TPs). Male presented higher Etot in all TPs (TP1:230.40±48.40kJ; TP2:242.49±37.91kJ; TP3:257.94±46.32kJ) compared with that found for female swimmers (TP1:188.51±35.13kJ; TP2:193.18±20.98kJ; TP3:199.77±25.94kJ). Male presented higher AnL (TP1:33.42±6.82kJ; TP2:30.97±8.73kJ; TP3:30.66±8.27kJ) and AnAl (TP1:30.61±3.48kJ; TP2:30.61±3.48kJ; TP3:30.60±3.48kJ) than female (TP1:18.83±8.45kJ; TP2:14.98±4.17kJ; TP3:18.33±8.66kJ) and (TP1:24.32±2.22kJ; TP2:24.31±2.23kJ; TP3: 24.31±2.23kJ). Aerobic metabolism is the major contributor for Etot both in male (TP1:71.63±4.99%; TP2:74.05±5.03%; TP3:76.14±4.46%) and female swimmers (TP1:76.87±3.86%; TP2:79.40±3.63%; TP3:78.40±5.54%). The better performance obtained by male compared to female swimmers may be due to the different contributions of the energetic pathways. Aerobic metabolism was the major contributor to Etot in a 200 m race, in both genders. Partial aerobic contribution was higher in female, while partial anaerobic contribution was greater in male.

Computational fluid dynamics (CFD) plays an important role to quantify, understand and "observe" the water movements around the human body and its effects on drag (D). We aimed to investigate the flow effects around the swimmer and to compare the drag and drag coefficient (CD) values obtained from experiments (using cable velocimetry in a swimming pool) with those of CFD simulations for the two ventral gliding positions assumed during the breaststroke underwater cycle (with shoulders flexed and upper limbs extended above the head-GP1; with shoulders in neutral position and upper limbs extended along the trunk-GP2). Six well-trained breaststroke male swimmers (with reasonable homogeneity of body characteristics) participated in the experimental tests; afterwards a 3D swimmer model was created to fit within the limits of the sample body size profile. The standard k-ε turbulent model was used to simulate the fluid flow around the swimmer model. Velocity ranged from 1.30 to 1.70 m/s for GP1 and 1.10 to 1.50 m/s for GP2. Values found for GP1 and GP2 were lower for CFD than experimental ones. Nevertheless, both CFD and experimental drag/drag coefficient values displayed a tendency to jointly increase/decrease with velocity, except for GP2 CD where CFD and experimental values display opposite tendencies. Results suggest that CFD values obtained by single model approaches should be considered with caution due to small body shape and dimension differences to real swimmers. For better accuracy of CFD studies, realistic individual 3D models of swimmers are required, and specific kinematics respected.

This study aimed to summarize evidence on masters' swimmers energetics, biomechanics, and performance gathered in selected studies. An expanded search was conducted on 6 databases, conference proceedings, and department files. Fifteen studies were selected for further analysis. A qualitative evaluation of the studies based on the Quality Index (QI) was performed by 2 independent reviewers. The studies were thereafter classified into 3 domains according to the reported data: performance (10 studies), energetics (4 studies), and biomechanics (6 studies). The selected 15 articles included in this review presented low QI scores (mean score, 10.47 points). The biomechanics domain obtained higher QI (11.5 points), followed by energetics and performance (10.6 and 9.9 points, respectively). Stroke frequency (SF) and stroke length (SL) were both influenced by aging, although SF is more affected than SL. Propelling efficiency (ηp) decreased with age. Swimming performance declined with age. The performance declines with age having male swimmers deliver better performances than female counterparts, although this difference tends to be narrow in long-distance events. One single longitudinal study is found in the literature reporting the changes in performance over time. The remaining studies are cross-sectional designs focusing on the energetics and biomechanics. Overall, biomechanics parameters, such as SF, SL, and ηp, tend to decrease with age. This review shows the lack of a solid body of knowledge (reflected in the amount and quality of the articles published) on the changes in biomechanics, energetics, and performance of master swimmers over time. The training programs for this age-group should aim to preserve the energetics as much as possible and, concurrently, improve the technique. Training sessions should feature a higher percentage of technical drills with the goal of enhancing the swim technique. Another goal should be the association of technique enhancement with aerobic and anaerobic sets, enabling the swimmer to improve the swimming efficiency.

The aim of this study was to compare the speed fluctuation and the drag force in young swimmers between genders. Twenty-three young pubertal swimmers (12 boys and 11 girls) volunteered as subjects. Speed fluctuation was measured using a kinematical mechanical method (i.e., speedo-meter) during a maximal 25-m front crawl bout. Active drag, active drag coefficient and power needed to overcome drag were measured with the velocity perturbation method for another two maximal 25m front crawl bouts with and without the perturbation device. Passive drag and the passive drag coefficient were estimated using the gliding decay velocity method after a maximal push-off from the wall while being fully immersed. The technique drag index was also assessed as a ratio between active and passive drag. Boys presented meaningfully higher speed fluctuation, active drag, power needed to overcome drag and technique drag index than the girls. There were no significant gender differences for active drag coefficient, passive drag and passive drag coefficient. There were positive and moderate-strong associations between active drag and speed fluctuation when controlling the effects of swim velocity. So, increasing speed fluctuation leads to higher drag force values and those are even higher for boys than for girls.