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  • Author: Ferran A. Rodríguez x
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José M. Saavedra, Yolanda Escalante and Ferran A. Rodríguez

This study develops multivariate models to predict swimming performance based on multidimensional assessment. 66 male (age 13.6 ± 0.6 y) and 67 female (11.5 ± 0.6 y) swimmers undertook a test battery including a sports background and training questionnaire, anthropometry, general and specific fitness tests, and technique. Competitive performance (LEN scores in three best events) was the predicted variable. A multiple linear regression model explained 82.4% of performance variability in males (based on age, sitting height, 30-min test, 6 × 50 m at 1:30, and swimming index) and 84.5% in females (age, 30-min test, 6 × 50 m at 1:30, and velocity at 50 m). Discriminant analysis using a four-group split-sample approach correctly classified 94.1% of the best male swimmers (based on age, 30-min test, 6 × 50 m at 1:30, shoulder extension, arm span, and height), and 71.0% of the best females swimmers (30-min test, horizontal floating, velocity at 50 m, and age). Chronological age was the main predictor of performance in this age category. Main predictive variables pertained to the anthropometric (particularly in males), specific fitness (aerobic speed and endurance), and technical domains (particularly in females). In these ages competitions should be organized according to year of birth and not by age categories.

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Diego Chaverri, Thorsten Schuller, Xavier Iglesias, Uwe Hoffmann and Ferran A. Rodríguez

Purpose:

Assessing cardiopulmonary function during swimming is a complex and cumbersome procedure. Backward extrapolation is often used to predict peak oxygen uptake (V̇O2peak) during unimpeded swimming, but error can derive from a delay at the onset of V̇O2 recovery. The authors assessed the validity of a mathematical model based on heart rate (HR) and postexercise V̇O2 kinetics for the estimation of V̇O2peak during exercise.

Methods:

34 elite swimmers performed a maximal front-crawl 200-m swim. V̇O2 was measured breath by breath and HR from beat-to-beat intervals. Data were time-aligned and 1-s-interpolated. Exercise V̇O2peak was the average of the last 20 s of exercise. Postexercise V̇O2 was the first 20-s average during the immediate recovery. Predicted V̇O2 values (pV̇O2) were computed using the equation: pV̇O2(t) = V̇O2(t) HRend-exercise/HR(t). Average values were calculated for different time intervals and compared with measured exercise V̇O2peak.

Results:

Postexercise V̇O2 (0–20 s) underestimated V̇O2peak by 3.3% (95% CI = 9.8% underestimation to 3.2% overestimation, mean difference = –116 mL/min, SEE = 4.2%, P = .001). The best V̇O2peak estimates were offered by pV̇O2peak from 0 to 20 s (r 2 = .96, mean difference = 17 mL/min, SEE = 3.8%).

Conclusions:

The high correlation (r 2 = .86–.96) and agreement between exercise and predicted V̇O2 support the validity of the model, which provides accurate V̇O2peak estimations after a single maximal swim while avoiding the error of backward extrapolation and allowing the subject to swim completely unimpeded.

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Philippe Hellard, Robin Pla, Ferran A. Rodríguez, David Simbana and David B. Pyne

Purpose: To compare the dynamics of maximal oxygen uptake (V˙O2), blood lactate ([La]b), total energy expenditure (E tot), and contributions of the aerobic (E aer), alactic anaerobic (E an,al), and lactic anaerobic (E an,lac) metabolic energy pathways over 4 consecutive 25-m laps (L0–25, L25–50, etc) of a 100-m maximal freestyle swim. Methods: Elite swimmers comprising 26 juniors (age = 16 [1] y) and 23 seniors (age = 24 [5] y) performed 100 m at maximal speed and then 3 trials (25, 50, and 75 m) at the same pace as that of the 100 m. [La]b was collected, and V˙O2 was measured 20 s postexercise. Results: The estimated energetic contributions for the 100-m trial are presented as mean (SD): E aer, 51% (8%); E an,al, 18% (2%); E an,lac, 31% (9%). V˙O2 increased from L0–25 to L25–50 (mean = 3.5 L·min−1; 90% confidence interval [CI], 3.4–3.7 L·min−1 to mean = 4.2 L·min−1; 90% CI, 4.0–4.3 L·min−1) and then stabilized in the 2nd 50 m (mean = 4.1 L·min−1; 90% CI, 3.9–4.3 L·min−1 to mean = 4.2 L·min−1; 90% CI, 4.0–4.4 L·min−1). E tot (juniors, 138 [18] kJ; seniors, 168 [26] kJ), E an,al (juniors, 27 [3] kJ; seniors, 30 [3] kJ), and E an,lac (juniors, 38 [12] kJ; seniors, 62 [24] kJ) were 11–58% higher in seniors. Faster swimmers (n = 26) had higher V˙O2(4.6L·min1, 90% CI 4.4–4.8 L·min−1 vs 3.9 L·min−1, 90% CI 3.6–4.2 L·min−1), and E aer power was associated with fast performances (P < .001). Conclusion: Faster swimmers were characterized by higher V˙O2 and less time to reach the highest V˙O2 at ∼50 m of the 100-m swim. Anaerobic qualities become more important with age.

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Rafael Martín Acero, Miguel Fernández-del Olmo, José Andrés Sánchez, Xosé Luis Otero, Xavier Aguado and Ferrán A. Rodríguez

The aim of this study was to determine the reliability of the squat jump test (SJ) and countermovement jump test (CMJ), in fifty-six children (30 girls and 26 boys) with ages ranging from 6 to 8 years. Each subject performed two evaluation sessions (T1, T2) with seven days between tests. The results show that the CMJ test has a high intratrial reproducibility in T1 and T2 measured through intraclass correlation coefficient (ICC ≥ 0.95). The ICC for the SJ test had a high value (0.99) only in T1. The variability for both tests among children under 9 years of age is higher than those reported for adult subjects in other studies. The intersession reliability was questionable with a high methodical error (ME= 9.86–15.1%, for the SJ and CMJ, respectively) and a significant worsening of the results of CMJ in T2 (p < .05).