# Quantifying Sub-Elite Youth Football Weekly Training Load and Recovery Variation
## 1 Introduction  
Monitoring training load in football is an important strategy to improve athletic performance and effective training periodization [1, 2]. Determining individual adaptations allows the assessment of physical and physiological responses, gathering insights about fatigue-recovery status [3, 4]. In addition, there is evidence that an optimal load management can minimize the risk for overtraining and injuries [5]. The training load has been defined as an input variable for training outcomes [6]. It is possible to slip it into external and internal loads [7]. The external load describes the performed work, whereas the internal load refers to biological requirements (physiological and psychological) imposed on athletes [8]. The external load can be monitored by global positioning system (GPS) devices and micro-electromechanical systems (MEMS) [9]. These tracking systems can accurately measure distances, speeds, accelerations/decelerations and accelerometer variables (e.g., player load, body impact or dynamic stress load) [5; 10; 11]. The internal load is assessed using objective and subjective measures [12]. The rating of perceived exertion (RPE) is the most common scale used to assess individual internal load [13]. Validity and reliability of RPE are well established in several sports and physical activities at different ages and expertise levels [14]. The session rating of perceived exertion (sRPE) has been reported as a better training load indicator to explain the training session intensity in comparison to RPE [15]. An adequate balance between stress and recovery has been described as essential to optimize athletic performance [6; 7; 8]. [PERSON] and [PERSON] [16] proposed \"total quality recovery\" (TQR) to predict individual and subjective recovery [17]. The TQR scale describes the fatigue-recovery using physical and psychosocial components [17; 18]. Studies have verified that the TQR did not contribute to predict young football performance. Nevertheless, the hypothesis was partly confirmed when only the weekly training load was analyzed [18]. The training load quantification has been widely studied in professional football for training conditions [19; 20; 21; 22; 23; 24]. The training load presented a high load variation within a weekly microcycle [21; 23; 25]. In contrast, the cumulative training load presented limited variation along mesocycles [20; 22; 26]. A large variation in training load has been also documented concerning training modes [19; 22]. The positional role should be considered an important variable to quantify the training load, given the interposition differences [20; 23; 24]. Generally, central midfielders covered more distance and wide-midfielders covered more distances in high-intensity zones [20; 23; 24]. The central defenders and wide-defenders covered more distance in low-intensity zones. In addition, forwards seemed to sprint significantly less frequently than central defenders [23]. In youth football, the influence of age and positional role on the activity profile has been analyzed in the match behavior [27; 28] and constrained training tasks [29; 30]. Typical weekly training load has been also analyzed in elite young football players; there was an age-related influence on the total weekly training load, which seems to be increasing with age [31; 32; 33]. For instance, [PERSON] et al. [32] reported higher total distances covered in under-17 (U17), followed by under-19 (U19) and under-15 (U15) players. In the same study, the total body impacts and relative impacts were lower in U15 players. [PERSON] et al. [31] reported a higher total distance covered (<13 km h\({}^{-1}\)), body impacts and time spent above high-intensity zones in U19 post-match training sessions. Building upon that, the elite typical weekly training load presented significant differences within weekly microcyles and among training modes [31; 32; 33].