184 Chapter 8 swimmers’ (multidimensional) training programs, including physical and psychological load and recovery, the employed training methods, and indicators of the quality of training would be highly valuable. This is essential to not only further unravel but also ensure sustained progression towards elite level swimming performance. Last, it becomes essential to explore the efficacy of talent development environments in which swimmers participate, as environmental factors prove to be more controllable than innate talent in influencing swimmers’ development and potential success (Hall et al., 2019; Henriksen et al., 2010; Henriksen & Stambulova, 2023). The second direction involves gaining a more profound understanding into the relationship between changes in underlying performance characteristics and corresponding shifts in swim performances over time. An option worth exploring involves constructing agerelated multilevel models that predict performance using multiple underlying performance characteristics. By comparing estimates between these models over time, insights can be gained into the relative importance of each underlying characteristic in relation to swim performance at different stages of development. However, due to the dynamic nature of performance development, the significance of these characteristics may change not only with age but also with the swimmer's (future) performance level and specialization. Including these factors into modeling would be interesting. However, in this effort, it is crucial that the study sample remains largely intact over time, which is an extremely challenging aspect of talent development research conducted over several years. Moreover, to the best of our knowledge, statistical analysis that integrate all of these components while differentiating between small-sized groups have yet to be developed. Nevertheless, these analyses could provide a more direct and prospective understanding of the factors influencing and predicting swim performance towards the elite level, giving practical insights into which aspects when to improve and what changes to expect. The third direction entails a more detailed examination, delving into the complex interactions between underlying performance characteristics in relation to swim performance. For example, exploring the relation between lower body power and starts and turns (Jones et al., 2018), can provide valuable insights about the mechanisms and hierarchies underlying the development of swim performance. Moreover, our results show large standard deviations in most of the underlying factors, suggesting that performance levels are related to unique, individualistic combinations in which weaker points can be compensated with stronger points, known as the compensation phenomenon (Vaeyens et al. 2008). Take, for example, a junior female swimmer with lower scores on stroke index, but who excels at starts and turns. While her lower efficiency may not hinder her performance at late junior age, it could pose a challenge as she progresses to the senior level, where faster starts and turns alone may not suffice to overcome this limitation. Future studies could further explore on this, as it can be expected that even the relatively weaker points of a swimmers’ performance require a minimal level of proficiency.
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