## 4 Discussion  
This study was designed to describe the AS profile of elite soccer players during competition and to analyse their seasonal changes and inter-player differences over seasons. The main findings of the study showed an average team season value of 6.20 \(\pm\) 0.51 m/s\({}^{2}\) and 9.18 \(\pm\) 0.58 m/s for A\({}_{0}\) and S\({}_{0}\), respectively. Second, although average team season values seem to be stable, substantial seasonal changes and different trends were observed in A\({}_{0}\) and S\({}_{0}\) when players were analysed individually. The inter-player differences were higher during the pre-season (Pre 1) and the middle of season (In 2) for A\({}_{0}\) while for S\({}_{0}\) were stable during all periods. Monitoring game-specific performance brings a deep insight into the real competitive peculiarities [3,6]. Thus, the present study analysed the AS profile values during an elite soccer season matches. Our current results showed lower season A\({}_{0}\) averages values (Table 1) compared to [PERSON] et al. (2022) [21] (8.41 \(\pm\) 0.57 m/s\({}^{2}\)) and [PERSON] et al. (2021) [16] (7.20 \(\pm\) 0.40 m/s\({}^{2}\)), both gathered during the first part of season. Although caution is needed when comparing values from different teams and contexts, the lack of agreement between A\({}_{0}\) values is notable. Greater A\({}_{0}\) values from training sessions [16] could be explained by the potential use of some frequently used tasks in soccer (i.e., small side games) that might predispose players to show higher A\({}_{0}\) values during training than match [27, 28, 29]. Differences in playing style, tactical behaviour, or player level, which affect accelerations variables outcomes during matches [7,30,31], could explain the differences in A\({}_{0}\) values obtained by [PERSON] et al. (2022) [21]. Regarding to the S\({}_{0}\), our results showed similar values (Table 2) compared to previous studies: 9.34 \(\pm\) 0.49 m/s [21] and 9.47 \(\pm\) 0.52 m/s [16]. In addition, our S\({}_{0}\) values concur with the V\({}_{0}\) values obtained from the F-V profile in soccer players: 9.25 \(\pm\) 0.61 m/s [9] and 9.20 \(\pm\) 0.40 m/s [15]. Considering the novelty of the AS profile, caution is still recommended to sports scientists and fitness coaches when using out of context data as reference values, especially for A\({}_{0}\). Neuromuscular performance is sensitive to change during season [9], which helps coaches detect potential injury risks and guide training programs [10]. The present study analysed, for the first time, the team and individual seasonal changes in the AS profile. Although no significant differences were found when studying A\({}_{0}\) and S\({}_{0}\) at team level, substantial variations were found at individual level during season for most players (see SD in Tables 1 and 2). According to [PERSON] et al. (2009) [26], the smallest meaningful change to optimally evaluate player seasonal performance in team sports can be assessed using sports-specific standardized differences. In that vein, a 0.2 intra-player SD in team sports is generally enough to detect small changes in performance [26]. Considering that winning margins in elite soccer can be a fraction of a second, small changes in sprint acceleration could be decisive during the game [19,26,32]. [PERSON] and [PERSON] (2015) [19] showed how variations of 0.03-0.04 s in a 20 m sprint meant a difference of \(\sim\)30 cm, which is decisive in one-on-one duels in soccer. Thus, it is recommended to prioritize individual player data to improve long-term monitoring of sprint performance. Players are differently exposed to maximal accelerations and maximal velocities actions during competition [6]. In a macroscopic to microscopic approach, our current results showed substantial inter-player variability throughout each analysed period (Figure 3).