Despite widespread encouragement for children to participate in sport, the efficacy of early sporting pathways remains underexplored. We compared a rotational junior-sport model combining skills from rugby, cricket, and netball with a modified games model. Motion analysis was used to quantify movement. Results revealed no differences between sporting models in relative percent time spent stationary (p = .32), walking (p = .89), jogging (p = .45), and fast running (p =.06). The rotational model had a greater number of skill-development opportunities per minute (median = 3.4) compared with the modified games model (median = 1.1, p = .001). Promising results from varied and rotational skill exposure warrant further elucidation.
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A Movement-Analysis Comparison in Two Models of Junior Sport
Timothy B. Hartwig and Geraldine Naughton
Defining the Volume and Intensity of Sport Participation in Adolescent Rugby Union Players
Timothy B. Hartwig, Geraldine Naughton, and John Searl
Purpose:
Investigating adolescent training loads might help us understand optimal training adaptations. GPS tracking devices and training diaries were used to quantify weekly sport and other physical activity demands placed on adolescent rugby union players and profile typical rugby training sessions.
Methods:
Participants were 75 males age 14 to 18 y who were recruited from rugby teams representing 3 levels of participation: schoolboy, national representative, and a selective sports school talent squad.
Results:
Schoolboy players covered a distance of (mean ± SD) 3511 ± 836 m, representative-squad players 3576 ± 956 m, and talent-squad players 2208 ± 637 m per rugby training session. The representative squad recorded the highest weekly duration of sport and physical activity (515 ± 222 min/wk), followed by the talent squad (421 ± 211 min/week) and schoolboy group (370 ± 135 min/wk). Profiles of individual players identified as group outliers showed participation in up to 3 games and up to 11 training sessions per week, with twice the weekly load of the team averages.
Conclusion:
Optimal participation and performance of adolescent rugby union players might be compromised by many high-load, high-impact training sessions and games and commitments to other sports and physical activities. An improved understanding of monitoring and quantifying load in adolescent athletes is needed to facilitate best-practice advice for player management and training prescription.
Validating the Use of Continuous Glucose Monitors With Nondiabetic Recreational Runners
Lesley J. Mason, Timothy Hartwig, and David Greene
Purpose: Continuous glucose monitors (CGMs) are becoming increasingly popular among endurance athletes despite unconfirmed accuracy. We assessed the concurrent validity of the FreeStyle Libre 2 worn on 2 different sites at rest, during steady-state running, and postprandial. Methods: Thirteen nondiabetic, well-trained recreational runners (age = 40 [8] y, maximal aerobic oxygen consumption = 46.1 [6.4] mL·kg–1·min–1) wore a CGM on the upper arm and chest while treadmill running for 30, 60, and 90 minutes at intensities corresponding to 50%, 60%, and 70% of maximal aerobic oxygen consumption, respectively. Glucose was measured by manually scanning CGMs and obtaining a finger-prick capillary blood glucose sample. Mean absolute relative difference, time in range, and continuous glucose Clarke error grid analysis were used to compare paired CGM and blood glucose readings. Results: Across all intensities of steady-state running, we found a mean absolute relative difference of 13.8 (10.9) for the arm and 11.4 (9.0) for the chest. The coefficient of variation exceeded 70%. Approximately 47% of arm and 50% of chest paired glucose measurements had an absolute difference ≤10%. Continuous glucose Clarke error grid analysis indicated 99.8% (arm) and 99.6% (chest) CGM data fell in clinically acceptable zones A and B. Time-in-range analysis showed reduced accuracy at lower glucose levels. However, CGMs accurately detected trends in mean glucose readings over time. Conclusions: CGMs are not valid for point glucose monitoring but appear to be valid for monitoring glucose trends during steady-state exercise. Accuracy is similar for arm and chest. Further research is needed to determine whether CGMs can detect important events such as hypoglycemia during exercise.
