Reproducibility of estimated optimal peak output using a force-velocity test on a cycle ergometer

Modelling anaerobic peak power assessed by the force-velocity test among late adolescents

OBJECTIVES

The aim of this study was to examine the concurrent contributions of body size, estimates of whole-body composition, and appendicular volume in addition to participation in competitive basketball to explain inter-individual variance in anaerobic peak power output during late adolescence. The study also tested non-participation versus participation in basketball as an independent predictor of peak power output.

METHODS

The sample of this cross-sectional study was composed of 63 male participants (basketball: n=32, 17.0±0.9 years; school: n=31, 17.4±1.0 years). Anthropometry included stature, body mass, circumferences, lengths, and skinfolds. Fat-free mass was estimated from skinfolds and lower limbs volume predicted from circumferences and lengths. Participants completed the force-velocity test using a cycle ergometer to determine peak power output.

RESULTS

For the total sample, optimal peak power was correlated to body size (body mass: r=0.634; fat-free mass: r=0.719, lower limbs volume: r=0.577). The best model was given by fat-free mass and explained 51% of the inter-individual variance in force-velocity test. The preceding was independent of participating in sports (i.e., the dummy variable basketball vs. school did not add significant explained variance).

CONCLUSION

Adolescent basketball players were taller and heavier than school boys. The groups also differed in fat-free mass (school: 53.8±4.8 kg; basketball: 60.4±6.7 kg), which was the most prominent predictor of inter-individual variance in peak power output. Briefly, compared to school boys, participation in basketball was not associated with optimal differential braking force. Higher values in peak power output for basketball players were explained by a larger amount of fat-free mass.

Allometric Scaling of Force-velocity Test Output Among Pre-pubertal Basketball Players

Basketball is characterized by high-intensity episodes predominantly reliant on anaerobic metabolism. The force-velocity test enables individual determination of an optimal braking force and emerged as appropriate to estimate optimal peak power. It has rarely been used in youth basketball. This study aimed to examine the contribution of body size, composition, and biological maturation to interindividual variation in force-velocity test output among pre-pubertal basketball players. The sample consisted of 64 male participants (8.4-12.3 years). Stature, sitting height, body mass and two skinfolds were measured, and leg length estimated. Fat-free mass and lower limb volume were estimated from anthropometry. Age at peak height velocity was predicted from maturity offset. Optimal peak power was correlated with all body size descriptors (correlation: 0.541-0.700). Simple allometric models explained 30-47% of inter-individual variance, with fat-free mass being the best predictor of performance. Whole-body fat-free mass (as a surrogate for active muscle mass) plus the indicator of maturation emerged as the best proportional allometric model (53% explained variance). Even at pre-pubertal ages, the interpretation of the force-velocity test requires assessing the metabolically active component of body mass.

Allometric Modeling of Wingate Test among Adult Male Athletes from Combat Sports

Background and objectives: Athletes from combat sports are grouped into a series of weight categories that are intended to promote fair competition. Differences in performance are partly attributable to differences in body size. Consequently, ratio standards in which a performance variable is simply divided by an anthropometric characteristic such as body mass are often used, although this application is not recommended. This study aimed to obtain allometric models to interpret Wingate Anaerobic Test (WAnT) outputs among male adult athletes from combat sports. Materials and Methods: The sample was composed of 64 participants aged 18–39 years (24.2 ± 4.6 years). Stature and body mass (BM) were measured and air displacement plethysmography used to estimate fat mass and fat-free mass (FFM). Lower-limb lean soft tissue (LL-LST) was derived from dual energy X-ray absorptiometry. WAnT outputs were peak power (WAnT-PP) and mean power (WAnT-MP). Allometric models were obtained from simple and multiple linear regressions using log-transformed variables. Results: Models derived from a single three-dimension descriptor explained a large portion of variance: WAnT-PP (BM: 31.1%; FFM: 54%; LL-LST: 47.2%) and WAnT-MP (BM: 50.1%; FFM: 57.4%; LL-LST: 62.7%). Finally, the best proportional allometric models emerged from the combination of LL-LST and FFM (WAnT-PP: 55%; WAnT-MP: 65%). Conclusions: The relationship between weight categories and performance did not seem to be explained by the basic principles of geometric similarity.