This study aimed to examine young swimmers’ behavioral flexibility when facing different task constraints, such as swimming speed and stroke frequency. Eighteen (five boys and 13 girls) 13- to 15-year-old swimmers performed a 15 × 50-m front crawl with five trials, at 100%, 90%, and 70% each of their 50 m maximal swimming speed and randomly at 90%, 95%, 100%, 105%, and 110% of their preferred stroke frequency. Seven aerial and six underwater cameras were used to assess kinematics (one cycle), with upper-limb coordination computed through a continuous relative phase and index of coordination. A cluster analysis identified six patterns of coordination used by swimmers when facing various speed and stroke frequency constraints. The patterns’ nature and the way the swimmers shifted between them are more important than getting the highest number of patterns (range of repertoire), that is, a change in the motor pattern in order to adapt correctly is more important than being able to execute a great number of patterns.
Ana F. Silva, Pedro Figueiredo, Sara Morais, João P. Vilas-Boas, Ricardo J. Fernandes and Ludovic Seifert
Ana F. Silva, Pedro Figueiredo, João Ribeiro, Francisco Alves, João Paulo Vilas-Boas, Ludovic Seifert and Ricardo J. Fernandes
To analyze young swimmers’ performance regarding sex and skill level, 23 boys and 26 girls (15.7 ± 0.8 and 14.5 ± 0.8 years old, respectively) were assessed for anthropometry, flexibility, strength, drag, coordination, and biomechanical variables. During a 50-m maximal front-crawl bout, seven aerial and six underwater Qualisys cameras assessed kinematics, and a load cell was used to measure drag (Tedea, United Kingdom) and tethered swimming force. A multivariate analysis of variance test (p < .05) enabled us to observe differences between skill levels in speed, stroke frequency, stroke index, and intracyclic velocity variations, but most relevant differences were noticed when comparing sexes, particularly for anthropometrics, shoulder flexibility, speed, stroke frequency, stroke length, drag, mechanical power, power per stroke, and maximal and mean force. Considering the included variables, only male swimmers’ performance could be predicted through multiple linear regression, with stroke index, left shoulder flexion, and intracycle velocity variations showing great importance in achieving better results.