Effect of a congested match schedule on immune-endocrine responses,technical performance and session-RPE in elite youth soccer players

ABSTRACT

This study investigated the effects of a congested match schedule (7 matches played in 7 days) on steroid hormone concentrations, mucosal immunity, session rating of perceived exertion (S-RPE) and technical performance in 16 elite youth soccer players (14.8 ± 0.4 years; 170.6 ± 9.4 cm; 64.9 ± 7 kg). No change was observed for salivary cortisol concentration across match time points (P = 0.33; effect size [ES] = 0.13–0.48). In contrast, there was a decrease in salivary testosterone and salivary IgA (SIgA) concentrations from the 1st compared with the last time point (P = 0.01 and 0.001, ES = 0.42 and 0.67, respectively). The SIgA concentration varied across time points (P < 0.001) with the highest value observed at the 3rd time point (rest day) (3rd vs all time point; ES = 0.47–0.73). No changes were observed for S-RPE across time points (P > 0.05). A higher number of tackles and interceptions were observed during the 4th match vs 1st and 7th matches (P < 0.001; ES = 2.25 and 1.90, respectively). The present data demonstrate that accumulated fatigue related to participation in a congested match schedule might induce a decrease in testosterone concentration in youth players and negatively affect their mucosal immunity and capacity to perform certain technical actions.     

College students’ categorical perceptions of grades: it’s simply ‘good’ vs. ‘bad’

College students’ categorical perceptions of numeric and alphabetic grades were examined by assigning participants to one of four conditions: numeric grades alphabetic grades, numeric non-grades and alphabetic non-grades. They were then asked to give ratings for each possible grade or non-grade, using a 10-point scale. Factor analysis revealed that college students view both numeric and alphabetic grades as occurring in dichotomous categories, presumably either ‘good’ or ‘bad’. There were no neutral categories for course grades. Replications consistently yielded similar results, although specific boundaries between ‘good’ and ‘bad’ grades varied slightly.     

Adolescent Sleep Duration,Variability, and Peak Levels of Achievement and Mental Health

To inform public health recommendations for adolescent sleep, the amounts of sleep associated with the highest levels of academic achievement and mental health were examined. The degree to which daily variability in sleep duration represents an underappreciated but functionally significant sleep behavior also was tested. A total of 421 adolescents (M_age = 15.03 years) with Mexican‐American backgrounds reported nightly sleep times for 2 weeks; approximately 80% repeated the same protocol 1 year later. Multilevel modeling indicated that the amount of sleep associated with the lowest levels of internalizing and externalizing symptoms was more than 1 hr greater than the amount associated with the highest levels of academic performance. Greater daily variability in sleep duration predicted greater symptomatology and mixed academic outcomes.     

Analysis of football game-related statistics using multivariate techniques

Abstract

The purpose of this study was to explore football game-related statistics during a competition, using principal component and cluster analyses to determine if it is possible to distinguish the winning teams from the drawing and losing ones. We collected the game-related statistics of the group phase matches of the 2006 World Cup and organised them into a matrix. The principal components of the covariance matrix were calculated. The scores of the first and second components were used to represent the new data, and cluster analysis was applied to separate the elements in two groups (G1 and G2). To analyse the degree of separation between the groups, we calculated the Silhouette Coefficient for each group. Finally, we checked if the winning teams were classified into the same group. The Silhouette Coefficients found for G1 and G2 were 0.54 and 0.55, respectively. Results showed that 70.3% of the winning teams were classified into the same group (G1). Similarly, 67.8% of the drawing and losing teams were classified in G2. This study presented a different way to analyse game-related statistics that allowed the multivariate differences to be shown between successful and unsuccessful teams.