## 4 Discussion
### Relationship Between Maturation and Training Adaptations
The 30-15 IFT, while a valid measure of intermittent endurance [28], relies heavily on maximal running speed, particularly in its later stages. For pre-PHV players, a limiting factor in test performance could be their inability to sustain the required velocity due to lower baseline sprint capacity, rather than central fatigue or aerobic limitations. As for that, improvements in 30-15 IFT in pre-PHV players may come due to both improved sprint mechanics and a reduced percentage of maximum sprint speed required at each stage. Notably, the RM ANOVA revealed no significant \"time \(\times\) maturity group\" interaction effect, and both pre- and post-PHV groups exhibited similar ES in physical performance changes. This suggests that, although only the pre-PHV group showed significant pre-post intervention improvements in the 30 m sprint and vIFT, the overall training adaptations did not differ significantly between the pre- and post-PHV groups when considering the statistical interaction. This lack of interaction may be attributed to the study's limited sample size (\(n=19\) in the EG). A post hoc power analysis using G*Power (version 3.1.9.7) (effect size f = 0.25, \(\alpha=0.05\), total \(n=19\)) indicated a statistical power of 0.55 to detect a time \(\times\) maturity interaction. Although this value is moderate, it falls below the commonly accepted threshold of 0.80, suggesting a potential risk of Type II error. As such, non-significant interaction effects should be interpreted with caution, and future studies with larger sample sizes are recommended to confirm these findings. As previously mentioned, there is ongoing debate regarding the existence of a specific window of opportunity for enhanced trainability and greater adaptations in speed and endurance [53]. As previously shown, findings of [PERSON] et al. [53] reported similar sprint improvements across pre-, mid-, and post-PHV groups following pyometric training interventions. Regarding endurance, discrepancies persist in the literature about whether a specific period of heightened trainability exists. [PERSON] et al. [18] observed similar peak VO\({}_{2}\) improvements across maturational groups following intermittent endurance training [18], suggesting a relatively uniform adaptability throughout childhood and adolescence. Growth-related changes such as increased predominance of glycolytic metabolism, enhanced activation of mitochondrial biogenesis pathways, and gains in lean body mass undoubtedly influence endurance development [56; 57; 58; 59], yet these adaptations may contribute linearly to performance gains across maturation rather than being confined to a critical window [60]. To further elucidate these findings, future research should explore the biological mechanisms underpinning these adaptations, such as changes in muscle fibre type, neuromuscular efficiency, or anaerobic power, which remain underexplored in youth footballers [18]. Larger sample sizes and longitudinal designs could also enhance the detection of maturational interactions, addressing the limitations of the current study. Future studies should consider stratified randomisation to minimise potential bias from maturity differences. Moreover, incorporating direct measures of cardiorespiratory fitness (e.g., VO\({}_{2}\) max) alongside the 30-15 IFT could clarify whether the observed improvements stem from speed enhancements or broader metabolic adaptations, offering a more comprehensive understanding of maturity-related training responses in young football players. Coaches should consider monitoring IL more closely in pre-PHV players, as their higher physiological responses may require a particular load adjustment.