Key result
Training performance variables, particularly heart rate, successfully classified youth rugby players into two distinct clusters (57.1% and 42.9%), offering an alternative to age-based grouping.
Observational (n=28)
Heart rate during training can be used to classify youth rugby players into groups based on physiological demands rather than age.
May support physiological grouping by heart rate in youth rugby; hypothesis-generating and should not yet change practice.
In order to be successful in rugby union, coaches need to adapt their training program to meet the demands of the modern game. The purpose of this study was classify youth rugby union players by training performances and know if these criteria can be used to group players instead the age group-criteria. Twenty-eight players participated in the study (under-16, n=13; under-18, n=15) during a two-week period for eight randomly selected training sessions. A two-step cluster analysis was performed to classify the players into different groups according their performance variables during the training sessions, and, the analysis resulted in 2 different groups: Cluster 1 (n=16, 57.1%) and Cluster 2 (n=12, 42.9%). The heart rate (HR) results were the best predictors of group classification. There were also significant differences across the two cluster groups for the heart rate zones, where all players spent most of the time below 75% of maximum heart rate (HRmax). Coaches and trainers can use this information to assist with grouping players based on the physiological demands of training, instead of using the age group-criteria. This classification analysis can be used to improve the accuracy of talent identification programs and to help improve the task representativeness in training sessions by optimizing the conflict effects.
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Vaz et al. (2015) conducted an observational in Youth rugby union players (n=28). Training performance variables was evaluated on Player classification by two-step cluster analysis. Training performance variables, particularly heart rate, successfully classified youth rugby players into two distinct clusters (57.1% and 42.9%), offering an alternative to age-based grouping.
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