## 4 Discussion
On the other hand, no significant differences were observed in the sprint test, even though it may also depend on factors related to strength and power production to some extent [44; 45]. This coincides with the results found in previous studies, which observed that players who had already passed the maximum growth peak had better results in the sprint test [49] and that early maturers had better results in strength and speed tests [44]. It has been observed that other factors that could affect sprint performance are reaction time at onset, technique or sprint mechanics, among others, which could be the reason that no differences were observed in the present study [50]. The T-Half test measuring agility and the Yo-Yo test measuring endurance also showed no significant differences between the biological maturation groups. Moreover, [PERSON] et al. [43] also found no differences in the agility test they performed. The absence of differences could be because, in this test, performance is also influenced by other factors, such as neural control of movements or years of practice in the sport [51]. On the other hand, in the meta-analysis by [PERSON] et al. [13], they also found no differences in the Yo-Yo test, which seeks to evaluate VO\({}^{2}\) max as the main variable of aerobic endurance [52]. One explanation for the absence of differences between the biological maturation groups could be that an athlete's endurance would be more influenced by the effects of training than by other variables [53; 54; 55]. In fact, it has been seen that the age at which endurance athletes have their maximum performance is far from adolescence [56]. Therefore, the hormonal development that occurs during biological maturation seems to influence physical tests where strength and power predominate, so it should be considered for future research where physical performance is also evaluated in groups of biological maturation. Even research to observe whether having teams in higher leagues influences the physical tests that evaluate the performance of an athlete. However, these differences between the results of the present study and previous literature could be due to the sample selected for each of them since [PERSON] et al. [49] evaluated young players from the first division and [PERSON] et al. [43] evaluated players that also belong to the first division and the national team. In contrast, in the present investigation, the population belonged to a regional level, competing in both provincial and autonomic leagues. These differences in the competitive level of the athletes could affect their body composition and, therefore, their performance in the physical tests [7,8]. Another aim of this research was to analyze the differences between the biological maturation groups after including the covariates age, maturity offset and diet in the model. In this line, significant differences were observed in the same kinanthropometric characteristics and in the same physical test results. With the inclusion of the covariate age in the model, significant differences were also found for the percentage of fat mass and in all the other results of the physical tests. The effect of age on these variables has also been analyzed by other authors in other sports [26,57], observing how the values improved with increasing age, with players of early biological maturation having higher values. This similarity in the results could be due to the physiological and hormonal changes involved in the maturation process as they advance in age [11,14] since, both in our research and in the others, the sample had an age close to the APHV, causing the biological maturation in early maturers to be more advanced. With the inclusion of the maturity offset covariate in the model, the same significant differences were found for the kinanthropometric characteristics as for the age covariate. As for the results of the physical tests, with the inclusion of the maturity offset, the same significant differences were found as age, except for the T-Half Test.