## 4 Discussion
There was a relatively large difference (up to 22.4%) for the first half's distance, spent in Z3 (\(>\)14.4 km.h\({}^{-1}\)), while for the second half (T5; 45-90 min), only the distance in the Z2 (0.7-7.2 km.h\({}^{-1}\)) was increased by 5.21%. Youth, especially elite youth, were chosen because of the limited research in the area of comparative profiles of the match demands in adolescent team sports [32; 33]. Other studies [3; 34; 12; 35] evaluated comparable factors of movement using the GPS system; however, the study subjects in the study were adult elite soccer players. Additionally, soccer analysis using the GPS also deviates from the elite sphere; covered distance in semi-pro players varies at 113.0 \(\pm\) 8.9 m.min\({}^{-1}\)[36]. In a study conducted by [PERSON] et al. [12], significant correlation between TDC (r = 0.62, \(p\) < 0.001, \(\text{Cl}_{95\%}\) = 0.36-0.79), HIR (r = 0.51, \(p\) < 0.05, CI = 0.21-0.72), and VHIR (r = 0.65, \(p\) < 0.001, \(\text{Cl}_{95\%}\) = 0.40-0.81) was established. In top-level European and Australian leagues, [PERSON] et al. [34] reported TDC from 10,063 to 11,230 m. [PERSON] et al. [35] reported 104 \(\pm\) 10 m.min\({}^{-1}\) for the Australian soccer players. We must emphasize that there is a significant difference in soccer formation such as 4-3-3, 4-4-2, and 4-5-1 gameplay, which might have influenced the player load [11]. [PERSON] et al. [37] revealed that in addition to age, maturation and body dimension were position-dependent variables that influenced in-match running performance. [PERSON] [38] reported greater TDC in the U16 category than in the U18 category. TDC was significantly greater in the U16 team for both half times (1 st half: 5.2 \(\pm\) 0.6 km; 2 nd half: 4.9 \(\pm\) 0.4 km) than in the U18 (1 st half: 4.8 \(\pm\) 0.6 km, ES = 0.70, \(\text{Cl}_{95\%}\) = 0.01-0.83; 2 nd half: 4.5 \(\pm\) 0.5 km, ES = 0.74, \(\text{Cl}_{95\%}\) = 0.04-0.7, \(p\) < 0.001) and U21 teams (1 st half: 4.7 \(\pm\) 0.6 km, \(p\) < 0.001, ES = 0.74, \(\text{Cl}_{95\%}\) = 0.05-0.91; 2 nd half: 4.5 \(\pm\) 0.7 km, \(p\) < 0.004, ES = 0.55, \(\text{Cl}_{95\%}\) = -0.08-0.76). In relation to the match demand profile, [PERSON] et al. [14] examined U18 players, using parameters such as \(\text{TDC}_{\text{rel}}\) 98.3 \(\pm\) 21.94 m.min\({}^{-1}\) at an average speed of 5.95 \(\pm\) 0.94 km.h\({}^{-1}\) and with 9.74 \(\pm\) 4.21% HIR. The range of the \(\text{TDC}_{\text{rel}}\) was 93.5 to 108.8 m.min\({}^{-1}\). [PERSON] et al. [39] used GPS units to monitor distances covered by players (U18) in ACC and DCC zones. From a time point of view, the study monitored the decline in ACC/DCC (\(-\)4.0 to 4.0 m. s\({}^{-2}\)) between the first and second halves. In our study, we also found a significant decline in ACC/DCC numbers of entries between the two halves; for ACC\({}_{Z2}\) (2.4-3.6 m.s\({}^{-2}\)) by 14.3%; ACC\({}_{Z3}\) (\(>\)3.6 m.s\({}^{-2}\)) by 60.0%; and \(\text{DCC}_{Z1}\) (\(<\)\(-\)2.4 m.s\({}^{-2}\)) by 11.0% in between T3 and T4 (0-70 vs. 70-90 min). We must emphasize that it is difficult to compare the ACC data of our study with those of other studies as there is little consensus regarding the use of ACC thresholds in team sports [40]. Our study and the study by [PERSON] et al. [39] suggest that high speed movements in the first half reach a volume when enough neuromuscular fatigue accumulates, influencing performance in the latter half of the match (45-90 min or even 70-90 min). The negative impact of neuromuscular fatigue and strength imbalances on specific soccer skills has been also reported [41]. [PERSON] [38] revealed significantly greater \(\text{TDC}_{\text{rel}}\) for the U16 group (108.68 \(\pm\) 9.79 m.min\({}^{-1}\)) than for the U18 (99.97 \(\pm\) 11.18 m.min\({}^{-1}\)) and U21 (98.72 \(\pm\) 14.04 m.min\({}^{-1}\)) groups. In our research, we established \(\text{TDC}_{\text{rel}}\) to be 117 \(\pm\) 9.02 m.min\({}^{-1}\) for the total match duration (0-90 min).