# Does Higher Maturation Make Age-Grouped Swimmers Faster? A Study on Pubertal Female Swimmers
## 4 Discussion
[29] among young boys. High \(SR\) itself does not lead to better performance; it is known that older swimmers note lower \(SR\) values than their younger counterparts at submaximal speeds [30]. It is the proper relationship between \(SR\) and \(SL\) which guarantees a higher swimming speedand younger swimmers are often not able to maintain _SL_ throughout a race [6]. In the present study, _SR_ was close to significant when measuring the linear correlation with the swimming speed (r = 0.30; \(p\) = 0.06), while the correlation with _SL_ was not significant. The kinematic indices of technique (_SR_, _SL_, _SI_) are strongly connected to sprint performance in adolescents. Including those indices into a multiple linear regression model could explain 99% (\(R^{2}\) = 0.99) of the swimming performance of young swimmers [31]. [PERSON] et al. [1] noted a strong correlation between _SI_ and 100 m front crawl performance of adolescent girls (age: 12.31 \(\pm\) 1.09 years). _SI_ was not included in the regression model in the current study because _SI_ is a product of _SL_ and \(v\), which in the authors' opinion could cause bias in the results when \(v\) is considered as the performance level. The _SL_ was also excluded from the model (replaced by _AS_) to avoid multicollinearity. The cluster analysis did not indicate significant differences in _SR_ and _SL_ between the groups; however, the result for _SL_ was close to significant (\(p\) = 0.07). [PERSON] et al. [32] examined 53 boys and girls (age: 12.40 \(\pm\) 0.74 years), creating three tiers on the basis of the swimming speed. They found no significant differences in _SR_ or _SL_, or in groups with significantly larger _BH_. More somatically developed (with advanced biological maturation) swimmers due to greater _AS_ and _BH_ are generally faster (at short distances 50-100 m) and perform fewer upper limb cycles over the same distances [33]. It is supposed that the lack of significant differences in performance among standard and early maturers in our study could be due to the well-trained swimming technique of less physically developed swimmers, who are also members of regional competition teams. [PERSON] et al. [13] investigated the influence of maturation on anaerobic energy production and concluded that this pathway of energy production was higher among adults than in children. Our study confirms [PERSON] findings, faster maturation process (higher _BA_) results in higher energy production (60_Fave_, \(v_{100}\)); correlation was also found between _BA_ and \(v_{100}\) (r = 0.40; \(p\) = 0.01). Also, [PERSON] et al. [11] reported moderate-to-strong significant correlations between \(\dot{V}\)O\({}_{2}\)max, _Fave_, and _BA_ but did not identify a mediation effect of _BA_ with regard to the correlation between \(v_{100}\) and _SL_ or _SR_. The cluster and ANOVA analyses performed in the present study indicated significant differences between the distinguished cluster groups in terms of the individuals' _BA_ (F = 44.03, \(p\) < 0.00001). It is interesting that only late-maturing girls (cluster 3, _BA_: 11.94 \(\pm\) 0.95 years) were significantly slower than the biologically older ones (cluster 1: 14.07 \(\pm\) 0.96, cluster 2: 17.05 \(\pm\) 1.53), and the differences in \(v_{100}\) between clusters 1 and 2 turned out not significant (1.39 \(\pm\) 0.08 vs. 1.41 \(\pm\) 0.05 m\(\cdot\)s\({}^{-1}\)). Conducting cluster analysis is still not performed very often in research regarding swimming. To the best of our knowledge, this is the first study where _BA_ and _VO2 peak_ are included in cluster analysis. [PERSON] et al. [34], performing cluster analysis in groups of age-grouped swimmers (14 boys: 12.70 \(\pm\) 0.63; 16 girls: 11.72 \(\pm\) 0.71 years old), came to a conclusion that coaches should design the training and developing programs of swimmers while being aware of the subgroups which exist in the training group. They also presented three clusters based on performance (100 m freestyle time). Similar to our study, the slowest swimmers from the study of [PERSON] et al.