The capacity to recover from intense training, competition and matches is considered an important determinant in soccer performance. At present, there is no consensus on the effect of post-training recovery interventions on subsequent training session. The aim of this study was to determine the effectiveness of active (12 min submaximal running and 8 min of static stretching) and passive recovery (20 min sitting on a bench) interventions performed immediately after a training session on anaerobic performances (CMJ, 20 m sprint and Balsom agility test) and lower limb flexibility 24 h after the training. During two experimental sessions, 31 professional soccer players participated in a randomized fully controlled trial design. The first session was designed to evaluate the player's anaerobic performances and lower limb flexibility (pretest). After baseline measurements, participants performed a standardized soccer training during which heart rate and RPE were recorded to evaluate the training load. At the end of the training unit all players were randomly assigned to the active recovery group and the passive recovery group. A second experimental session was organized to obtain the posttest values. Players performed the same test, administered in the same order than in the first trial. No significant differences between groups were observed in heart rate and RPE. No significant effect due to recovery interventions was found on lower limb flexibility and anaerobic performances except CMJ that posttest value was significantly greater in the active recovery group than in the passive group (p < 0.05).
The aim of the present study was to identify performance indicators that discriminate winning teams from drawing and losing teams in the UEFA Champions League. All 288 matches played at the group stage in the 2007-2008, 2008-2009, and 2009-2010 seasons were analyzed. The game-related statistics gathered were: total shots, shots on goal, effectiveness, passes, successful passes, crosses, offsides committed and received, corners, ball possession, crosses against, fouls committed and received, corners against, yellow and red cards, venue, and quality of opposition. Data were analyzed performing a one-way ANOVA and a discriminant analysis. The results showed that winning teams had significantly higher average values that were for the following game statistics: total shots (p<0.01), shots on goal (p<0.01), effectiveness (p<0.01), passes (p<0.05), successful passes (p<0.05), and ball possession (p<0.05). Losing teams had significantly higher values in the variable yellow cards (p<0.01), and red cards (p<0.01). Discriminant analysis allowed to conclude the following: the variables that discriminate between winning, drawing and losing teams were the shots on goal, crosses, ball possession, venue and quality of opposition. Coaches and players should be aware of these different profiles in order to increase knowledge about game cognitive and motor solicitation and, therefore, to design and evaluate practices and competitions for soccer peak performance teams in a collective way.
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