The purpose of this study was to determine a resting interval between countermovement jumps (i.e., volleyball spikes) that allows the maintenance of maximal jumping performance. Ten male volleyball players (1.85 +/- 0.05 m, 77.2 +/- 10.6 kg, 21.6 +/- 5.3 years) performed 6 experimental jumping sessions. In the first and sixth sessions, maximal countermovement jump height was measured, followed by submaximal countermovement jumps to the point of volitional fatigue. The number of countermovement jumps was used as a reference to test the effect of rest period between volleyball spikes. From the second to fifth experimental sessions, 30 maximal volleyball spikes were performed with different resting periods (i.e., 8, 14, 17, and 20 seconds) followed by countermovement jumps. Between the 15th and 30th spikes, the blood lactate concentration and heart rate were measured. Because the performance on the first and sixth sessions was the same, no training effects were noticed. During the 8-second resting interval set, the lactate concentration increased significantly between the 15th and 30th spikes (i.e., from 3.37 +/- 1.16 mmol to 4.94 +/- 1.49 mmol); the number of countermovement jumps decreased significantly after spikes compared to those performed without a previous effort (i.e., from 23 +/- 7 jumps to 17 +/- 9 jumps); and these variables were significantly correlated (r = -0.7). On the other hand, the lactate concentration and number of countermovement jumps were stable across the other resting intervals, without a heart rate steady state. The results indicate that an adequate resting period between spikes allowed participants to achieve a lactate steady state in which the performance was maintained during the exercise. These findings show that resting intervals between 14 and 17 seconds, typical during volleyball matches, are indicated to use in volleyball spike drills due to their capacity to maintain maximal jumping performance.

No abstract

Evaluation of anaerobic capacity in soccer players using a maximal shuttle run testResumo -O objetivo do presente estudo foi verificar se o teste de Vai-e-Vem300m pode ser utilizado para predizer a capacidade anaeróbia, correlacionando com a potência média do teste de Wingate, em um grupo de jogadores de futebol profissional. Participaram do estudo 21 jogadores (21 ± 2 anos; 76,8 ± 7,0 kg; 179,8 ± 6,7 cm) de uma equipe da primeira divisão da Federação Paulista de Futebol. No primeiro dia, os participantes realizaram o teste de Wingate e foram determinados o pico de potência relativo, a potência média relativa e o índice de fadiga. No segundo dia, os participantes realizaram o teste de Vai-e-Vem300m, que consistia em corridas de vai-e-vem de 20m, na maior velocidade possível, até totalizar a distância de 300 m. Os parâmetros obtidos desse teste foram a duração do Vai-e-Vem300m e a velocidade média de 20 m (V20m). Antes e após a realização do Vai-e-Vem300m, foram obtidas amostras sangüíneas para determinação da concentração de lactato ([LAC]). Ao realizar a correlação de Pearson entre os parâmetros obtidos no Wingate e no Vai-e-Vem300m, apenas a potência média relativa correlacionou significativamente (p<0,05) com a duração do Vai-e-Vem300m (r = -0,75) e com a V20m (r = 0,72). A [LAC] aumentou significativamente (p<0,05) quando comparados os valores antes (2,1 ± 1,0 mM) e após (14,3 ± 2,4 mM) o Vai-e-Vem300m. Portanto, os resultados do presente estudo demonstraram que o teste de Vai-e-Vem300m pode ser utilizado para predizer a capacidade anaeróbia em jogadores de futebol profissional. Palavras-chave: Wingate; Lactato sanguíneo; Campo e pista. Abstract -The aim of this study was to investigate whether a 300-m shuttle run test predicts anaerobic capacity, expressed as mean power output in the

Usually, the players' or teams' efficiency to perform passes is measured in terms of accuracy.The degree of difficulty of this action has been overlooked in the literature. The present study aimed to classify the degree of passing difficulty in soccer matches and to identify and to discuss the variables that most explain the passing difficulty using spatiotemporal data. The data used corresponds to 2,856 passes and 32 independent variables. The Fisher Discriminant Analysis presented 72.0% of the original grouped cases classified correctly. The passes analyzed were classified as low (56.5%), medium (22.6%), and high difficulty (20.9%), and we identified 16 variables that best explain the degree of passing difficulty related to the passing receiver, ball trajectory, pitch position and passing player. The merit and ability of the player to perform passes with high difficulty should be valued and can be used to rank the best players and teams. In addition, the highlighted variables should be looked carefully by coaches when analyzing profiles, strengths and weaknesses of players and teams, and talent identification context. The values found for each variable can be used as a reference for planning training, such as small side games, and in future research.

(9,8 mmol/l, 9,4 mmol/l e 6,6 mmol/l) nos tempos 0', 5' e 20' minutos