## 1 Introduction  
In the past decades, almost all the professional football teams were using electronic performance tracking systems to monitor the players' load. This information is very important for sports scientists and conditioning coaches to better understand the volume and intensity during the training sessions and the official matches [1, 2]. Training load monitoring is fundamental for training planning and periodization for several reasons: (a) to avoid undertraining or overtraining, (b) to reduce the risk of injury and (c) to have the optimal physical condition to compete [3]. In this regard, the aim of strength and conditioning coaches is to find the right balance of the player training load [4]. The training load can be divided into \"internal\" and \"external\". Heart rate training impulse (TRIPM) and session rate of perceived exertion (s-RPE) are the common methods to describe the internal load [5]. On the other hand, the external load consists of parameters related to the players' movement on the field (distance covered in different speed zones, accelerations, decelerations, sprint actions, etc.) and can be captured through GPS or video-based technologies [6]. Monitoring the wellness status of athletes allows us to know the details of fatigue, stress and delayed onset muscle soreness (DOMS) [7]. The Hooper index [8] assesses these variables (plus \"sleep quality\"), which are associated with biochemical (physical and physiological) and biomechanical stress responses [7]. The s-RPE is proven to be valid, reliable and has correlation with the heart training zones [9], but it is not sensitive to the subjective perceptions of fatigue, DOMS or stress [10] that can be assesses with the Hooper index [8]. Past research has found no association between the Hooper index and RPE [10]. Interestingly, [PERSON] et al. (2017) [11] found that during the weeks with two matches, the correlation was small-to-moderate (negative), but there was no correlation during the weeks with only one match. In another study, it was reported that on the first day after match (MD + 1), s-RPE showed a lower value in comparison with all the other match days, but the Hooper index had a higher value because of the fatigue from the preceding game [12]. From the above findings, we suggest using the Hooper and s-RPE methods and reading their results independently according to the week format or the days of the week. During the training days of the week, the workload varies in professional soccer players. After the recovery days, the training load increased progressively until three days before the next match (MD \(-\) 3) and later decreased down to MD \(-\) 1 [4; 12; 13; 14]. Specifically, it was found that on MD \(-\) 4 and MD \(-\) 3, the workload was greater than on MD \(-\) 2 and MD \(-\) 1 [4; 14; 15], and these days are the most suitable to load the players through repeated high-intensity actions, drills undertaken on larger pitch sizes and small-sided games [4; 14; 16]. [PERSON] at el. (2015) [17] found that the total load remained similar during training days, except for MD \(-\) 1, and [PERSON] et al. (2017) [18] reported that training load variables including s-RPE were elevated on MD \(-\) 3 compared with MD \(-\) 4, \(-\) 2 and \(-\)1. Similarly, in another study, significantly lower values for all the training load variables (total distance, average speed and high-speed running distance) appeared on MD\(-\)1 [12]. The loading strategy is different for the players who do not participate (or play less than 45 min in the last game), for them, an additional demanding day is MD + 1 [13]. All the above confirms the tapering strategy which is adopted by strength and conditioning coaches to decrease the stress of training and maximize performance on the match day [19]. The weekly workload should be adjusted to achieve the desired results.