Factors affecting sports involvement in a school-based youth cohort: Implications for long-term athletic development.

The aim of the present study was to determine the factors affecting sports involvement in a school-based adolescent population. The cross-sectional cohort study assessed anthropometry, physical capacities and motor competence in 501 boys (aged 10-16 y), from junior (10-12 y) and senior (13-16 y) cohorts. Sports participation data was collected from junior participants. Multivariate analysis of covariance revealed moderate maturity, anthropometry, physical capacity and motor competence differences between sports in the senior cohort (F = 2.616, p < 0.001, η2 = .08), but not in the junior cohort. Furthermore, differences in physical fitness were revealed between playing levels (F = 2.616, p < 0.001, η2 = .08), with a discriminant analysis correctly classifying 73% of participants using aerobic fitness and vertical jump measures. Representative level participants engaged in more structured training and commenced organised competition at a later age (F = 4.332, p < 0.001, η2 = .21). This study's findings are twofold: 1) physical and motor competence profiles differ more between sports with increasing age, and 2) participants at a higher level of competition report delayed engagement in their main sport. As a result, schools may be the ideal environment in which to provide children and adolescents with the opportunity to sample different sports.

Factors affecting perception of effort (session rating of perceived exertion) during rugby league training.

PURPOSE: The purpose of this study was to examine the validity of session rating of perceived exertion (sRPE) for monitoring training intensity in rugby league. METHODS: Thirty-two professional rugby league players participated in this study. Training-load (TL) data were collected during an entire season and assessed via microtechnology (heart-rate [HR] monitors, global positioning systems [GPS], and accelerometers) and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and various other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during rugby league training. RESULTS: There were significant within-individual correlations between sRPE and various other internal and external measures of intensity and load. The stepwise multiple-regression analysis also revealed that 62.4% of the adjusted variance in sRPE-TL could be explained by TL measures of distance, impacts, body load, and training impulse (y = 37.21 + 0.93 distance - 0.39 impacts + 0.18 body load + 0.03 training impulse). Furthermore, 35.2% of the adjusted variance in sRPE could be explained by exercise-intensity measures of percentage of peak HR (%HRpeak), impacts/min, m/min, and body load/min (y = -0.01 + 0.37%HRpeak + 0.10 impacts/min + 0.17 m/min + 0.09 body load/min). CONCLUSION: A combination of internal and external TL factors predicts sRPE in rugby league training better than any individual measures alone. These findings provide new evidence to support the use of sRPE as a global measure of exercise intensity in rugby league training.