## 1 Introduction  
Soccer involves both aerobic and anaerobic activities, with players frequently engaging in high-intensity efforts throughout a match [1]. Advances in technology, such as miniaturized tracking devices, have enhanced our understanding of the sport's physical demands. These devices measure total distance and distance covered at various speeds, including walking, jogging, and sprinting. On average, elite players cover between 9 and 11 km per game [1, 2, 3, 4, 5]. Notably, more distance, especially at high intensities (>18 km/h for men and >15 km/h for women), is covered in the first half compared to the second [6, 7, 8, 9, 10, 11]. Additionally, players at higher competition levels tend to cover greater distances at high intensities than those at lower levels [4, 5]. While a decline in physical performance is observed in the second half at all levels [5, 9, 10, 12, 13], the exact cause remains unclear [5, 14]. Fatigue is often suggested as a contributing factor, though it has not been directly measured [5, 12, 14, 15]. For example, one study found that high-intensity running and repeated sprints can reduce sprint performance by up to 9% post-match, with fatigue lasting up to 72 h [15]. However, the relationships between on-field, in-game performance metrics and fatigue are not yet fully understood [5; 14; 15]. Previous research suggests that body composition significantly affects soccer players' performance in physical tests. Players with higher fat mass tend to score lower on aerobic capacity, sprint, and vertical jump tests compared to those with lower fat mass [16; 17]. Seasonal variations in body composition are common, with the lowest body fat observed at the end of the season and the highest at the start of the pre-season [18; 19]. These fluctuations are associated with slower sprint times as body fat increases [18; 19]. While fat mass clearly influences physical test results, its direct impact on on-field, in-game performance remains unproven. Although it is widely assumed that more lean mass enhances performance, studies show that athletes with greater lean mass do not always perform better in sprint or jump tests [17; 20]. This underscores the need for further research to examine how body composition affects both physical test outcomes and on-field, in-game performance in soccer players [17; 20; 21]. A major challenge in comparing data between studies is the inconsistent methods used to measure body composition and its impact on performance. Many studies rely on skilloid equations or bioelectrical impedance analysis (BIA) [19; 21; 22], which, although practical and inexpensive, can have high variability when used to analyze athletes [23; 24]. In contrast, dual-energy x-ray absorptiometry (DXA), which is considered the gold standard for body composition analysis, provides precise estimates of both regional and whole-body composition using a three-compartment model (bone mass, lean tissue mass, and fat mass). DXA is a valid and reliable method for athletes [25; 26; 27], especially when evaluating specific regions such as the lower extremities in soccer players [28; 29; 30]. Another challenge in using physical tests to assess soccer performance is their inability to differentiate high-level players from lower-level ones [1; 17; 31; 32]. Similar sprint test results have been observed between National Collegiate Association (NCAA) and professional European players, as well as between starters and substitutes on professional teams [7; 30]. One study even found that the top male NCAA soccer player had lower aerobic capacity than his teammates [32], suggesting that tests like VO2 max or sprints don't always correlate with higher performance [17; 32; 33]. Players who excel in these tests may not necessarily perform better during games [13; 17; 32; 33; 34]. Physical tests assess isolated skills and fail to capture the complexities of competitive play [21]. While body composition may influence test results, its impact on on-field, in-game performance remains largely unstudied [17].