19 resultados para maximal ontological completeness
Resumo:
[ES] Durante pruebas cíclicas de larga duración ha sido probada que las estrategias para gestionar la fatiga pueden ser un factor determinante. A pesar de ello, este mismo fenómeno no está del todo probado que pueda darse en esfuerzos máximos de corta duración. Es por eso, que el objetivo de este trabajo ha sido analizar si variando el grado de conocimiento de los atletas durante este tipo de pruebas puede darse alguna alteración en su rendimiento. METODO: Siete deportistas varones completaron durante tres diferentes días un mismo protocolo (8 repeticiones máximas de 30 metros con un minuto de recuperación) en el que se varió la información que se les deba. Así, el primer día se les señaló que realizarían 4 repeticiones, pero cuando finalizaron se les indicó que realizarían 4 más (Prueba decepción). El segundo día, no se les informó del número de repeticiones a realizar (Prueba Suspense) y se les mandó parar al realizar la octava. Y por último, el tercer día se les señaló que realizarían 8 repeticiones (Prueba Control). RESULTADOS: Diferencias significativas (p>0.05) se encontraron en los tiempos de las cuatro primeras repeticiones entre la Prueba Suspense y Prueba Decepción. CONCLUSIÓN: Los resultados muestran como en pruebas máximas de corta duración las estrategias de gestión de la fatiga se pueden dar de manera anticipatoria al número de repeticiones a realizar.
Resumo:
The purpose of this study was to compare the effects of Small-Sided Games (SSG) vs. Interval Training (IT) in soccer training on aerobic fitness and physical enjoyment in youth elite soccer players during the last 8 weeks of the season. Seventeen U-16 male soccer players (age = 15.5 +/- 0.6 years, and 8.5 years of experience) of a Spanish First Division club academy were randomized to 2 different groups for 6 weeks: SSG group (n = 9) and IT group (n = 8). In addition to the usual technical and tactical sessions and competitive games, the SSG group performed 11 sessions with different SSGs, whereas the IT group performed the same number of sessions of IT. Players were tested before and after the 6-week training intervention with a continuous maximal multistage running field test and the counter movement jump test (CMJ). At the end of the study, players answered the physical activity enjoyment scale (PACES). During the study, heart rate (HR) and session perceived effort (sRPE) were assessed. SSGs were as effective as IT in maintaining the aerobic fitness in elite young soccer players during the last weeks of the season. Players in the SSG group declared a greater physical enjoyment than IT (P = 0.006; ES = 1.86 +/- 1.07). Coaches could use SSG training during the last weeks of the season as an option without fear of losing aerobic fitness while promoting high physical enjoyment.
Resumo:
Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams.
Resumo:
The aim of the present study is to analyse the influence of different large-sided games (LSGs) on the physical and physiological variables in under-12s (U12) and -13s (U13) soccer players. The effects of the combination of different number of players per team, 7, 9, and 11 (P7, P9, and P11, respectively) with three relative pitch areas, 100, 200, and 300 m(2) (A100, A200, and A300, respectively), were analysed in this study. The variables analysed were: 1) global indicator such as total distance (TD); work:rest ratio (W:R); player-load (PL) and maximal speed (V-max); 2) heart rate (HR) mean and time spent in different intensity zones of HR (<75%, 75-84%, 84-90% and >90%), and; 3) five absolute (<8, 8-13, 13-16 and >16 Km h(-1)) and three relative speed categories (<40%, 40-60% and >60% V-max). The results support the theory that a change in format (player number and pitch dimensions) affects no similarly in the two players categories. Although it can seem that U13 players are more demanded in this kind of LSG, when the work load is assessed from a relative point of view, great pitch dimensions and/or high number of player per team are involved in the training task to the U12 players. The results of this study could alert to the coaches to avoid some types of LSGs for the U12 players such as:P11 played in A100, A200 or A300, P9 played in A200 or A300 and P7 played in A300 due to that U13>U12 in several physical and physiological variables (W:R, time spent in 84-90% HRmax, distance in 8-13 and 13-16 Km h(-1) and time spent in 40-60% V-max). These results may help youth soccer coaches to plan the progressive introduction of LSGs so that task demands are adapted to the physiological and physical development of participants.