## 1 Introduction
Whereas for most high-speed or high-intensity parameters, it is not possible to accumulate a high load during the week (related to the game demands), conversely, for TD, ACCs, and DECs, the related game/load ratio can be high, but this is recommended for application only in long-duration microcycles [18; 27]. This high accumulation of mechanical load (ACCs, DECs) is achieved through various training modules and small- and large-sided games (SSGs, LSGs) that coaches integrate in the middle of the training week [28]. The average Hooper score is correlated with FTG and SRN. These parameters have a high effect on EXLD during training sessions (TD, HSR, ACm, player load) and games (ACCs, DECs) [7; 29; 30; 31]. Stress has a correlation with TD, HSR, and player load, but practitioners should be aware that external factors (e.g., family and social obligations) may affect the players' responses to this parameter [32]. In young players, [PERSON] et al. [5] did not find any correlation between FTG, SLP and TD, HMLD, ACCs, and DECs. A study on Australian football players using microcycles of different durations revealed that the players' wellness responses were influenced by the length of the microcycle [33]. On the contrary, in another study, there were no correlations found for football players, and this was justified by the small amount of short microcycles' that was included in the analysis [15]. Furthermore, they noticed that many other factors could possibly contribute (team level, training methodology, etc.) [15]. All these findings provide a new vision regarding the correlation between EXLD parameters and perceivedwellness scores and suggest the application of these tools as part of a multidimensional athlete monitoring approach [7]. RPE and RPE\({}_{\text{dur}}\) are correlated with internal and EXLD variables [34; 35; 36], although many factors could possibly affect perceived exertion [37; 38]. Specifically, there is a correlation between RPE and ACh, SPm, distance > 14.4 km/h (DIS > 4), distance 19.8-25.5 km/h (SPh), and when the EXLD is calculated with individualized thresholds, there is also a correlation with SPvh [37; 39]. Similar findings have been found in young football players for TD, HSR, and AChm [36]. Similarly, RPE\({}_{\text{dur}}\) has correlations with TD, HMLD, HSR, DIS > 4, distance > 18 km/h, ACC, and training duration (DUR) [29; 37; 40; 41]. The same is the case for young players with DUR, TD, HSR, and semiprofessional players with TD [42]. For both methods (RPE, RPE\({}_{\text{dur}}\)), using individualized thresholds (depending on the players' abilities) to calculate EXLD variables results in higher correlations compared to the arbitrary threshold method [39]. Furthermore, higher correlations exist when using RPE\({}_{\text{dur}}\) than RPE, presumably because there is a devaluation of DIS > 4 with the second method [41]. There are no data available regarding the evaluation of internal load using the RPE\({}_{\text{dur}}\) in microcyles of different durations in professional football. Nonetheless, in rugby, there was lower RPE\({}_{\text{dur}}\) on the short microcyles in comparison to the medium and large ones [43]. Prior research examined the load accumulation in games, where the RPE\({}_{\text{dur}}\) was higher in a single game compared to two game microcyles [44], and this could be explained by the fact that, in congestive game weeks, the training sessions are focused on recovering from the games (low intensity--volume), resulting in lower perceived responses [17]. Regarding wellness responses, SRN and FTG had higher values in two-game microcyles, but for stress responses, they were higher in single-game microcyles [44]. In a study [45] that investigated the relationship between training load and variables related to wellness in U16 football players, correlations were observed between the load and the indicators of fatigue, stress, and the Hooper index.