## 3 Results
### Correlations  
Significant associations were found between FL and ACSA when all athletes were examined together (\(r=0.625\), \(p<0.001\)). Furthermore, significant correlations were found \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **Group 1 (n = 13)** & **Group 2 (n = 14)** & **Group 3 (n = 26)** & **Group 4 (n = 22)** & **Group 5 (n = 14)** \\  & **8–10 y** & **10–12 y** & **12–14 y** & **14–16 y** & **16–18 y** \\ \hline
**FL (cm)** & **3.66 \(\pm\) 0.40** & **3.88 \(\pm\) 0.55** & **4.31 \(\pm\) 0.60** & **4.54 \(\pm\) 0.61** & **4.55 \(\pm\) 0.42** & \(p<0.001\) \\ \hline
**Group 1** & \multirow{2}{*}{\(p=0.827\) (\(d\equiv 0.47\))} & \multirow{2}{*}{\(11\%\)} & \multirow{2}{*}{\(17\%\)} & \multirow{2}{*}{\(17\%\)} \\ \cline{2-2} \cline{6-6}
**Group 2** & & & & & \\ \cline{2-2} \cline{6-6}
**Group 3** & & & & & \\ \cline{2-2} \cline{6-6}
**Group 4** & & & & & \\ \cline{2-2} \cline{6-6}
**Group 5** & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison matrix of FL among the five age groups of female volleyball players (means \(\pm\) standard deviations). Gray area shows [PERSON]’s \(d\) and \(p\) values for the compared groups. White area shows the percent differences between the compared groups. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **Group 1 (n = 13)** & **Group 2 (n = 14)** & **Group 3 (n = 26)** & **Group 4 (n = 22)** & **Group 5 (n = 14)** \\  & **8–10 y** & **10–12 y** & **12–14 y** & **14–16 y** & **16–18 y** \\ \hline
**ACSA** & \multirow{2}{*}{\(9.98\pm 2.07\)} & \multirow{2}{*}{\(12.59\pm 3.49\)} & \multirow{2}{*}{\(13.08\pm 3.01\)} & \multirow{2}{*}{\(13.86\pm 2.65\)} & \multirow{2}{*}{\(14.86\pm 3.01\)} & \multirow{2}{*}{\(p<0.001\)} \\ \cline{2-2}
**(cm^{2})** & & & & & \\ \hline
**Group 1** & \multirow{2}{*}{\(p=0.140\) (\(d=0.94\))} & \multirow{2}{*}{-} & \multirow{2}{*}{\(4\%\)} & \multirow{2}{*}{\(10\%\)} & \multirow{2}{*}{\(18\%\)} \\ \cline{2-2}
**Group 2** & & & & & \\ \cline{2-2} \cline{6-6}
**Group 3** & & & & & \\ \hline
**Group 4** & \multirow{2}{*}{\(p=0.002\) (\(d=1.63\))} & \multirow{2}{*}{\(p=0.703\) (\(d=0.44\)  
(0%), while non-significant small increases are observed in ACSA by 6 and 7% for age groups 14-16 and 16-18 years (\(d\) = 0.28 and 0.37, respectively). The twofold greater increase in ACSA (49%) compared with FL (24%) from the age of 8 until the age of 18 years may indicate a primarily transverse rather than longitudinal growth of gastrocnemius medialis muscle fascicles. Significant correlations were found between participants' anthropometric characteristics (especially weight and height), as well as age, and gastrocnemius medialis FL and ACSA underpinning the role of growth and body dimensions as a mechanical stimulus for muscle growth. Gastrocinemius medialis muscle architecture is an important functional characteristic, as this muscle plays a key role in ankle joint movement [26; 37]. The functional properties of gastrocnemius medialis may be altered by muscle architecture changes that occur during growth, potentially impacting force-length and force-velocity relationships [38; 39]. The results of this study indicated large increases in gastrocnemius medialis FL from the age of 8-10 y until the age of 12-14 y by 18% (\(d\) = 1.23), followed by a small but not significant increase in the age of 14-16 years (\(d\) = 0.38) while no further increase was observed in the age 16-18 years (\(d\) = 0.02). In line with these results, [PERSON] et al. [23] also observed different FL adaptations between two groups of males, during the period of PHV (\(\sim\)10% increase) and post the period of PHV (\(\sim\)9%), with the first showing greater increases in gastrocnemius medialis FL. [PERSON] [1] also found relatively large FL increases by 5% per year, in children aged 5-12 years. In contrast, a previous study, examining gastrocnemius medialis FL in children and adolescents aged 10-19 years did not find differences between different ages [16].