## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Qualitative Inferences for**} & \\  & & **Pre** & **Post** &
\begin{tabular}{c} **Effect Magnitude** \\ **(Mean Difference, \(\pm\)90\% CL)** \\ \end{tabular} & **rANOVA** \\ \hline \multirow{3}{*}{Total Time [s]} & SG & 2.96 \(\pm\) 0.14 & 2.89 \(\pm\) 0.02 a & *** (\(-\)0.07, \(\pm\)0.03) & \\  & HG & 2.97 \(\pm\) 0.13 & 2.89 \(\pm\) 0.15 a & *** (\(-\)0.08, \(\pm\)0.03) & \\  & CG & 3.06 \(\pm\) 0.05 & 3.09 \(\pm\) 0.13 & (0.03, \(\pm\)0.03) & \\ \hline \multirow{3}{*}{Avg Vel 1a [m/s]} & SG & 3.00 \(\pm\) 0.23 & 3.10 \(\pm\) 0.17 & *** (0.10, \(\pm\)0.06) & \\  & HG & 2.95 \(\pm\) 0.16 & 3.08 \(\pm\) 0.15 a & *** (0.13, \(\pm\)0.01) & \\  & CG & 2.96 \(\pm\) 0.14 & 2.88 \(\pm\) 0.20 & *** (\(-\)0.08, \(\pm\)0.07) & \\ \hline \multirow{3}{*}{Avg Vel 1b [m/s]} & SG & 3.53 \(\pm\) 0.12 & 3.68 \(\pm\) 0.10 a,b & *** (0.15, \(\pm\)0.06) & \\  & HG & 3.54 \(\pm\) 0.17 & 3.56 \(\pm\) 0.11 & (0.02, \(\pm\)0.07) & \\  & CG & 3.52 \(\pm\) 0.12 & 3.53 \(\pm\) 0.10 & (0.01, \(\pm\)0.08) & \\ \hline \multirow{3}{*}{Dec Dist [m]} & SG & 2.31 \(\pm\) 0.38 & 2.38 \(\pm\) 0.25 & *** (0.07, \(\pm\)0.02) & \\  & HG & 2.10 \(\pm\) 0.43 & 1.74 \(\pm\) 0.52 & *** (\(-\)0.36, \(\pm\)0.20) & \\ \cline{1-1}  & CG & 2.35 \(\pm\) 0.32 & 2.20 \(\pm\) 0.30 & *** (\(-\)0.15, \(\pm\)0.26) & \\ \hline \hline \end{tabular} Values are given as mean \(\pm\) SD, a = sig. dig. to pre, b = sig. dig. SG-CC; chances that the true magnitude of the effects is beneficial, * = possibly (25–75%), ** = likely (75–95%), ** = very likely (95–99.5%); CL = confidence limits, Avg Vel 1a = average velocity from start to change of direction, Avg Vel 1b = average velocity after change of direction, Dec Dist = distance from the first drop in velocity to the change of direction.  
\end{table} 
Table 4: Comparison of CoD speed performance in the modified 5-0-5 test between SG (\(n\) = 9), HG (\(n\) = 9), and CG (\(n\) = 7) pre- and post-intervention. inferred that the LA value during training was not sufficiently elevated to hinder or restrict performance. Because this study was conducted with high-level basketball players, LA habituation may have influenced the results, and it should be considered that outcomes could differ among less-trained subjects. In line with previous studies, the current findings provide evidence supporting the effectiveness of sand training in improving both jumping and sprint performance on a hard surface [27; 44; 48; 49; 50]. This indicates the potential transfer of training effects from sand to hard surfaces, which seems surprising initially, as training to enhance these athletic capabilities typically prioritizes the favorable attributes of firm surfaces that enable the generation of high stretch loads, effective storage of elastic energy, and activation of the stretch reflex. These biomechanical factors play a critical role in facilitating the SSC and the resulting concentric muscle contractions, leading to the refinement of athletic capabilities in terms of jumping and sprinting [51; 52]. Conversely, sand training results in a significant dissipation of elastic energy, leading to extended ground contact times and decreased movement efficiency. This causes a greater demand for concentric muscle actions, increases energy costs and the level of muscle activation [23], and challenges the ankle to generate vertical force. Therefore, jumping on sand necessitates a more vigorous concentric push-off phase, which has been demonstrated as an important predictor of jumping performance [53]. Furthermore, all byometrics performed on sand rely on the long SSC due to extended ground contact times, whereas some performed on hard surfaces rely more on the short SSC. Correspondingly, enhancements in vertical jump performance, in particular, have been observed in exercises involving a longer SSC (CMJ, PSJT), where concentric force development makes a greater contribution.