Introduction. The aim of the present study was to find the relation of exercise-induced biomarkers (antioxidant, muscle dam-age, and inflammatory markers) with endurance capacity and anaerobic power. The study also aimed to develop predicting regression models for maximal oxygen uptake (VO2max) and relative anaerobic power (Wpeak) to specify the essential performance limiting elements. Material and Methods. Eighty-six endurance male players (i.e., football (n = 39) and field hockey (n = 47)) were selected as test subjects for the present study. Muscle damage indices (creatine kinase (CK), lactate dehydrogenase (LDH), cortisol), inflammatory markers (interleukin-6 (IL-6), tumor necrosis factor-a (TNF-a)), antioxidant variables (malondialde-hyde (MDA), superoxide dismutase (SOD), glutathione (GSH), glutathione peroxidase (GPx)) and performance variables (indi-cated as VO2max and Wpeak) were assessed using standard protocols. Results. The most significant (sig p < 0.001) prediction of VO2max = (0.763) MDA+ (5.644) SOD+ (0.039) GSH- (0.154) GPx+ (0.002) LDH- (0.011) CK+ (0.038) cortisol+ (1.232) IL+ (1.135) TNF+ 20.018. The strongest correlations were found between VO2max vs MDA (R2 = 0.852), VO2max vs IL-6 (R2 = 0.589), VO2max vs TNF-a (R2 = 0.385). Conclusions. Artificial neural network perceptron model depicted stronger prediction of VO2max (R2 = 0.872) in comparison to Wpeak (R2 = 0.271), with MDA and CK as the major predictors for VO2max and Wpeak, respectively. Among all biomarkers, MDA, IL-6, and TNF-a were identified as the most valuable indicators to predict endurance capacity significant-ly. While MDA, SOD, GPx, IL-6, and TNF-a were strongly correlated with VO2max and LDH, cortisol was strongly correlated with Wpeak. Contrarily, exercise-induced biomarkers failed to predict anaerobic power.
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