## 4 Discussion  
This study aimed to analyze within-group in the wMPA, wAcZ1, wAcZ2, wAcZ3, wDcZ1, wDcZ2, and wDcZ3 for starter and non-starter professional soccer players across pre-, early-, mid-, and end-season periods. Regarding wMPA, starters and non-starters revealed significant variations through the season. Specifically, starters showed higher values in early-season > pre-season > mid-season > end-season, while non-starters presented higher values in pre-season > early-season > mid-season > end-season. The presented results showed a different pattern to those found by [PERSON] et al. 's [PERSON] et al. (2018) study, where starters and non-starters showed significantly higher values in pre-season over early-season for MPA training monotony and strain indexes. Meanwhile, the same study observed a tendency to decrease MPA training monotony and strain indexes from the beginning to the end of the season, which is in line with the present study. Although the present study did not analyze training monotony and training strain, it seems there is a similar tendency of higher values in the pre-season and early-season, which means higher external workloads at the beginning of the season that are reduced until the end of the season. Despite that MPA was estimated by GPS used in this study, the theoretical basis of this calculation ([PERSON] et al., 2018; [PERSON] et al., 2018), its accuracy ([PERSON] et al., 2018), and reliability ([PERSON] et al., 2018) supported the use of this measure. Furthermore, MPA is also related with acceleration-based variables, and, as mentioned before, the GPS used in the present study has a high reliability for these variables. Even  
Figure 4: Pairwise comparisons between season periods in wAcZ3, The average weekly time spent on the acceleration threshold of zone 3 (<4 m\(\cdot\)s\({}^{2}\)) and wDcZ3, The average weekly time spent on the deceleration threshold of zone 3 (<\(-\)4 m\(\cdot\)s\({}^{2}\)). m\(\cdot\)s\({}^{-2}\), meters per second squared. Figure 3: Pairwise comparisons between season periods wAcZ2, the average weekly time spent on the acceleration threshold of zone 2 (2 to 4 m\(\cdot\)s\({}^{2}\)) and wDcZ2, the average weekly time spent on the deceleration threshold of zone 2 (\(-\)2 to \(-\)4 m\(\cdot\)s\({}^{2}\)); m\(\cdot\)s\({}^{-2}\), meters per second squared. so, researchers, coaches, and staff may use the values reported in this study as reference, considering this limitation. Regarding wAcZ1 and wDcZ1, it was observed that starters and non-starters presented higher values in pre- and early-season, and lower values in mid- and end-season, while wAcZ1 showed a decrease from the beginning of the season to the end of the season, and wDcZ1 showed a w-shape variation over the full season for starter players, with only a significant difference between early- vs. mid-season. In wAcZ2 and wDcZ2, starters presented the highest values in pre-season and early-season, and the lowest values in mid- and end-season, without significant variations. However, non-starters showed some variations for the same variables, where higher values were found in early-season. Finally, in wAcZ3, starters presented lower values in pre-season and higher values in early- and mid-season. Regarding wDcZ3, the pattern showed a w-shape variation without significant differences. However, in wAcZ3, non-starters showed some variations and higher values in early- to mid-season, but in wDcZ3, they showed higher values in pre-season and early-season, and the lower values were not found until the end of the season. Indeed, and according to the previous study, starters presented significantly higher values for all accelerometer-based variables than non-starters (all \(p\) < 0.05), except for wDcZ3 during pre-season, where no significant differences were found (\(p\) > 0.05) [21]. Overall, the higher values found in pre- and early-season were similar regarding the status of the players.