29 Performance development of top-elite swimmers 2 development programs and the level of competition. Individual differences in underlying performance characteristics, environmental characteristics, timing and tempo of the growth spurt and the number and quality of training hours may harness possible explanations for differences in swim performance between performance groups and sexes and for the wide variation in developmental patterns between top-elite swimmers. Therefore, future, longitudinal studies following youth swimmers throughout their sports career, measuring underlying performance characteristics, mapping environmental characteristics and tracking their maturation, learning, training and level of swim performance, could potentially provide further insight into successful 100m freestyle performance development of top-elite swimmers (Elferink-Gemser et al., 2011; Kannekens et al., 2011). In here, the effect of age of selection on the performance development of those reaching top-elite level should be addressed as well. The present study is the first that investigated 100m freestyle performance development at such large scale. Following the method developed by Stoter et al. (2019), the present study defined swim performance as a relative measure instead of an absolute measure. The major strength of using a relative measure of swim performance (rSBT) is that it allows a more “fair” comparison of swim performance between and within swimmers. Therefore we were able to include swim performance over multiple generations which resulted in a big data set with multigenerational and longitudinal data. Consequently, we extended group sizes of populations characterized with smaller sample sizes (e.g. top-elite swimmers). This provided us the unique opportunity to investigate 100m freestyle performance development of top-elite, elite, sub-elite and high-competitive swimmers over more than 20 years. In a similar way, other sports with absolute performance measures (i.e. time-trial sports such as cycling or running) can be studied. However, when applying this method it is important to realize that a different classification of performance groups may lead to different outcomes (Swann et al., 2015). Hence, the present study carefully considered the definitions of topelite, elite, sub-elite and high-competitive swimmers and defined performance groups based on task- and sex-specific limits, meaningful for the sport for competitive swimming. With particular interest, the present study researched the performance development of topelite swimmers. In here, the sport science perspective of striving to find regularities and patterns that can be applied to a whole population (Leezenberg & de Vries, 2001) was mixed with the investigation of individual pathways, a highly relevant and valuable combination for research in elite sports since experts in sports are individuals who do not comply with regularities. The frequency analysis on the first entry age of top-elite swimmers at the four performance levels showed an innovative method to describe the individual pathways towards acquisition of top-elite performance level. By analyzing these individual pathways, we gathered insight into the mean age and general age ranges at which top-elite swimmers for the first time started to perform at high-competitive, sub-elite, elite and top-elite level.
RkJQdWJsaXNoZXIy MTk4NDMw