## 3 Results
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Indicator** & **Strike** & **Mean \(\pm\) SD** & **Median** & **Lower** & **Upper** & **Range** & **Z** & \(p\) & **CV\%** & **CI 95\%** & **CI 95\%** \\  & & & & **Quantile** & **Quantile** & & & & & **Lower** & **Upper** \\ \hline Pressure & RC & 1709.3 \(\pm\) 486.6 & 1594.9 & 1339.8 & 2099.8 & 2866.8 \(\div\) 1082.5 & \multirow{2}{*}{\(-6.062\)\({}^{*}\)} & \multirow{2}{*}{\(<\)0.0018 \({}^{*}\)} & \multirow{2}{*}{32.3} & \multirow{2}{*}{25.5} & \multirow{2}{*}{39} \\ force & LJ & 1176.6 \(\pm\) 248.7 & 1163.8 & 1010.8 & 13645 & 1748.2 \(\div\) 670 & & & & \\ \hline \multirow{2}{*}{\(\begin{array}{c}\text{Fist}\\ \text{acceleration}\end{array}\)} & RC & 94.3 \(\pm\) 18.5 & 95.3 & 78.9 & 103.4 & 174.2 \(\div\) 68.3 & \multirow{2}{*}{\(-6.379\)\({}^{*}\)} & \multirow{2}{*}{\(<\)0.001 \({}^{*}\)} & \multirow{2}{*}{29.8} & \multirow{2}{*}{23.6} & \multirow{2}{*}{36} \\ acceleration & LJ & 66. \(\pm\) 19.5 & 61.4 & 47.7 & 78.1 & 114.7 \(\div\) 36.3 & & & & \\ \hline \multirow{2}{*}{\(\begin{array}{c}\text{Forearm}\\ \text{acceleration}\end{array}\)} & RC & 67.1 \(\pm\) 25.3 & 65.8 & 47.2 & 81.4 & 146.7 \(\div\) 34.3 & & & & \\ \cline{2-10}  & LJ & 41.6 \(\pm\) 11 & 39.2 & 34.6 & 49 & 65.3 \(\div\) 22.5 & & & & \\ \hline \multirow{2}{*}{\(\begin{array}{c}\text{Arm}\\ \text{acceleration}\end{array}\)} & RC & 88.4 \(\pm\) 19.2 & 90.2 & 78.1 & 102.4 & 123.5 \(\div\) 47.7 & & & & & \\ \cline{2-10}  & LJ & 81.4 \(\pm\) 28.8 & 79.1 & 64.8 & 96.1 & 206.5 \(\div\) 28.6 & & & & \\ \hline \hline \end{tabular} RC–Right-hand, LJ–lead-jab, SD—standard deviation, Z—Z score, \(p\)—The \(p\)-value in hypothesis testing, CV—Coefficient of Variation, CL—Confidence Interval, \({}^{*}\)—\(p<\) 0.05.  
\end{table} 
Table 1: Descriptive statistics of registered variables. Total_GRF, with a peak value of approximately 2866.76 N. Conversely, the \"1-0-1\" pattern, denoting high acceleration in the distal and proximal segments but low acceleration in the middle segment (forearm), resulted in the lowest observed Total_GRF, with a value of approximately 1643.56 N (Figure 6). Figure 5: Proximal-to-Distal Acceleration Patterns in Upper Limb Segments with Polynomial Trend Analysis. Figure 6: Max Total Ground Reaction Force Across Combined Acceleration Categories of Upper Limb Segments. In examining the effects of various predictors on total ground reaction force (Total_GRF), identified as a key measure of force in boxing dynamics, a multiple regression analysis was conducted. The analysis, detailed in the accompanying dataset, reveals a robust model fit, evidenced by an R-value of 0.801 and an R\({}^{2}\) of 0.642. This indicates that approximately 64.2% of the variance in Total_GRF can be attributed to the predictors included in the model. The adjusted R\({}^{2}\), refined to 0.610 to account for the number of predictors, further underscores the model's capacity to elucidate the determinants of Total_GRF. The model's overall significance is confirmed by a high F-statistic value of 19.928 (df = 9, 100, \(p\) < 0.00001), validating the predictive power of the regression model. The regression coefficients, as outlined in the results, provide insight into the individual contributions of each predictor. Notably, fist acceleration (afist) emerges as a statistically significant predictor, with a coefficient of 13.290 (\(p\) < 0.001), underscoring a pronounced positive relationship with Total_GRF. Body mass is also identified as a significant factor, with a coefficient of 10.491 (\(p\) < 0.001), indicating its influential role in force generation. Furthermore, training tenure, with a coefficient of 15.662 (\(p\) = 0.035), is highlighted as a key contributor to Total_GRF, suggesting the impact of experience and conditioning on force output.