Modelling the 200 m Front-Crawl Performance Predictors at the Winter Season Peak

Development and Interplay of Metabolic and Mechanical Performance Determinants Over an Annual Training Period in Adolescent National-Level Squad Swimmers

PURPOSE

The study examined the longitudinal interplay of anthropometric, metabolic, and neuromuscular development related to performance in adolescent national-level swimmers over 12 months.

METHODS

Seven male and 12 female swimmers (14.8 [1.3] y, FINA [International Swimming Federation] points 716 [51]) were tested before (T0) and after the preparation period (T1), at the season's peak (T2), and before the next season (T3). Anthropometric (eg, fat percentage) and neuromuscular parameters (squat and bench-press load-velocity profile) were assessed on dry land. Metabolic (cost of swimming [C], maximal oxygen uptake [V˙O2peak], and peak blood lactate [bLapeak]) and performance (sprinting speed [vsprint] and lactate thresholds [LT1 and 2]) factors were determined using a 500-m submaximal, 200-m all-out, 20-second sprint, and incremental test (+0.03 m·s-1, 3 min), respectively, in front-crawl swimming.

RESULTS

vsprint (+0.6%) and LT1 and 2 (+1.9-2.4%) increased trivially and slightly, respectively, from T0 to T2 following small to moderate strength increases (≥+10.2%) from T0 to T1 and V˙O2peak (+6.0%) from T1 to T2. Bench-press maximal strength and peak power correlated with vsprint from T0 to T2 (r ≥ .54, P < .05) and LT2 at T1 (r ≥ .47, P < .05). Changes in fat percentage and V˙O2peak (T2-T1 and T3-T2, r ≤ -.67, P < .01) and C and LT2 (T2-T0, r = -.52, P = .047) were also correlated.

CONCLUSIONS

Increases in strength and V˙O2peak from preparation to the competition period resulted in improved sprint and endurance performance. Across the season, upper-body strength was associated with vsprint and LT2, although their changes were unrelated.

Which of the Physiological vs. Critical Speed Is a Determinant of Modern Pentathlon 200 m Front Crawl Swimming Performance: The Influence of Protocol and Ergometer vs. Swimming Pool Conditions

BACKGROUND

Modern pentathlon includes horse riding, fencing, swimming, shooting and cross-country running. Events can last many hours during which the athletes face almost maximal energy and physiological demands, and fatigue. Early recognition and prevention of injuries and overuse syndromes can be achieved by refining the individual training loads. The purpose of the study was to determine which parameter could be the most accurate predictor of swimming working capacity determinants in pentathletes.

METHODS

Fourteen male pentathletes performed a continuous maximal incremental test in the swimming flume ergometer to measure peak oxygen uptake (VO₂peak), and five swimming tests in a 50 m swimming pool to detect critical velocity (CV); velocity at 2 and 4 mM·L^-1 of blood lactate (v2, v4) and energy cost (EC).

RESULTS

The 200 m swimming time was 2:18-2:32 m:s (340 FINA points). CV was 1.21 ± 0.04 m·s^-1, v2 was 1.14 ± 0.09 and v4 1.23 ± 0.08 m·s^-1. VO₂peak was 3540.1 ± 306.2 mL·min^-1 or 48.8 ± 4.6 mL·kg^-1·min^-1. EC at 1.24 m·s^-1 was 45.7 ± 2.4 mL·kg^-1·min^-1. Our main finding was the large correlation of CV with 200 m swimming performance; Conclusions: Among all the protocols analysed, CV is the most predictive and discriminative of individual swimming performance in this group of pentathletes. It appears as the most suitable test to constantly refine their swimming training loads for both performance enhancement and health promotion.

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.

Exploration of Internal and External Factors of Swimmers' Performance Based on Biofluid Mechanics and Computer Simulation

The purpose of this study is to explore the influence of different swimming strokes on the performance of swimmers and the resistance of each part from the perspective of hydrodynamics. In this paper, the influence of internal and external factors on the swimming speed is analyzed comprehensively and meticulously from the macro and micro perspectives. In the macroscopic part, the swimming speed representation model is established, and the validity of the model is further verified by the analysis of experimental data and hydrodynamic equations. In the microscopic part, we carefully analyzed details such as the opening angle of the palm, the timing of the arm and leg and the angular velocity of each link of the human body. Combined with computer simulation, stereo modeling and numerical analysis are carried out, and the best scheme FOR how to cooperate with each part of the body in swimming is given.