## 4 Discussion
### Correlates of Power Abilities and Agility  
Although some authors have reported poor relationships between power qualities and agility performance, the majority of previous research found positive correlations [26; 27; 28]. In studies conducted on both young and adult athletes, researchers stress that agility, speed time, and jumping ability belong to the same physical attribute [29; 30; 31; 32]. From all measured power indices in our study, only the squat jump test proved to be significant predictor of reactive agility in the boys' sample. Results like this are consistent with the literature review. For example, [PERSON] et al. (2015) found a strong correlation (r = \(-\)0.71) between SJ and the zigzag agility test performed without the ball in young soccer players [33]. The authors explained this through the similarity of muscle actions and short duration in both tests; namely, to perform a jump or to change the direction of movement, one needs to use a lot of muscle power in a short period of time [1]. According to the results of our study, we may say that more powerful preadolescent boys perform better on a generic reactive agility test. In previous research, authors found positive effects of jumping training on agility performance. Obviously, plyometric training enhances muscle neural adaptations and the enhancement of motor unit recruitment [34; 35]. Both features are very important for fast and effective change of direction movements. We assume that those features, along  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & \(\beta\) & **SE (\(\beta\))** & **b** & **SE (b)** & **t-Value** & \(p\)**-Value** \\ \hline Intercept & & & 1.42 & 0.71 & 1.99 & 0.07 \\ TCODS & 0.65 & 0.20 & 0.78 & 0.24 & 3.22 & 0.01 \({}^{*}\) \\ R & 0.65 & & & & & \\ R\({}^{2}\) & 0.43 & & & & & \\ \(p\) & 0.006 & & & & & \\ \hline \hline \end{tabular} Legend: TCODs—triangle test change of direction speed, \(\beta\)—regression coefficient, SE (\(\beta\))—standard error of the regression coefficient, \({}^{*}\) indicates the statistical significance of \(p\) < 0.05.  
\end{table}
Table 4: Forward stepwise linear regression of TRAG calculated for validation sample separately for girls.  
with those mentioned before, make a difference between a good and bad agility performer of this particular age and gender.  
Linear regression calculation did not find any significant power predictor for reaction agility in the girls' sample. Apparently, the girls' results in the TRAG test are possible to predict only with the CODS test. Therefore, it is expected that girls rely less on power and more on some other motor qualities to execute this specific reactive agility task. Actually, several authors have proposed that different agility manifestations in pubescent girls should be observed as relatively independent qualities since the percentage of the common variance between the observed agility tests rarely exceeded 50% [18; 36].  
The absence of running speed influence on reactive agility performance in both genders should be contextualised with TRAG test movement characteristics. During the TRAG test, subjects move short distances (4.5 m between the polygons' cones) and are not able to develop any significant linear speed such as during sprinting tests. Also, the number of steps in the TRAG test ranges from 3 to 5, and those steps are pretty short due to the speed decrement and accelerations during stop-and-go movements. Contrarily, during sprint tests, subject move larger distances (10 to 20 m) which they cover with 10 to 15 steps. One of the studies that corroborates our assumption was conducted by [PERSON] et al. (2016). The authors found that sprinting ability can enhance CODS and RAG in young football players only if trained in a multidirectional manner and over distances similar to those in agility tests [37].