## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Physical Activity** & **G1 (n = 36)** & **G2 (n = 62)** & **G3 (n = 57)** & **F(2, 154)** & \(p\) \\ \hline NPA (min) & 31.30 \(\pm\) 8.91 & 41.81 \(\pm\) 15.34 & 37.27 \(\pm\) 13.26 & 7.139 & 0.001 \\ LPA (min) & 13.05 \(\pm\) 2.33 & 20.83 \(\pm\) 6.57 & 16.54 \(\pm\) 5.38 \({}^{+,\#}\) & 24.800 & 0.000 \\ MPA (min) & 16.21 \(\pm\) 4.51 & 18.51 \(\pm\) 7.22 & 13.45 \(\pm\) 5.66 \({}^{\#}\) & 10.137 & 0.000 \\ VPA (min) & 11.25 \(\pm\) 4.10 & 9.48 \(\pm\) 3.76 \({}^{*}\) & 6.12 \(\pm\) 2.93 \({}^{+,\#}\) & 25.550 & 0.000 \\ MVPA (min) & 27.46 \(\pm\) 7.97 & 27.99 \(\pm\) 10.18 & 19.58 \(\pm\) 8.12 \({}^{+,\#}\) & 15.134 & 0.000 \\ \hline \end{tabular}  
Data are presented as means \(\pm\) SD. \({}^{*}\) Significant difference between G1 and G2, + Significant difference between G1 and G3, and # Significant difference between G2 and G3.  
\end{table} 
Table 4: Physical activity among age groups. walking, suggesting that low-intensity movements remain consistent across age groups. This pattern may imply that older players conserve energy by limiting high-speed efforts to avoid fast transitions or fast breaks rather than reducing overall movement during play [44]. Significant differences in ML and JL between age groups were observed, suggesting pronounced age-related adaptations in movement patterns. Unlike commonly used metrics, ML and JL offer a more differentiated approach for quantifying how athletes distribute physical effort across horizontal and vertical planes. To the authors' knowledge, this is one of the first implementations of these metrics in this context. G1's ML was 23.4% higher than G2 and 38.5% higher than G3, while G2's ML exceeded G3 by 19.2%. Similarly, G1's JL was 32.2% higher than G2 and 46.7% higher than G3, with G2's JL being 21.4% higher than G3. These findings underscore the sharper decline in vertical efforts with age and highlight the value of ML and JL as novel methods for assessing age-related movement pattern adaptations. Studies have shown that type II (\"fast twitch\") muscle fibers, which are essential for power movements like jumping and sprinting, are predominantly affected [71]. This decrease in fast-twitch muscle fibers aligns with the lower jump frequencies and the lower distance covered in the running speed zones observed in older athletes, strengthening the perspective that they may adapt their game to compensate for reduced power output by limiting vertical actions, such as jumping for rebounds or performing high jump layups or shots [44]. Instead, they may rely more on tactical positioning, short runs, and defensive coverage. This change may also be influenced by the elevated injury risk associated with high-impact vertical actions, which place a substantial load on knees, ankles, and other musculoskeletal structures, increasing the likelihood of strains and grained joints. A linear decline in athletic performance in various sports, particularly in jumping and running events, supports these adaptations [72]. In basketball, these adaptations may expand to shooting patterns, with older athletes potentially preferring mid-distance shots over three-point attempts, given the reduced lower-body power required for shorter distances [44]. Indeed, these adaptations agree with previous research in older adults, where during a friendly basketball match, players performed a limited number of high-intensity actions, emphasizing on defensive rebounding and mid-range shooting [44]. Although there were no significant differences in subjective ratings of perceived exertion among age groups, the values were significantly higher than those reported in other studies that consider master basketball matches as a light to moderate activity, indicating that despite the age-related decline in EL, IL remains relatively unaffected [43]. A study by [PERSON] et al. [43] reported an average sRPE load of 148.9 \(\pm\) 69.7 AU during a 4 \(\times\) 10 min game format, which was lower than the values recorded in all groups.