Effects of Different Training-Intensity Distribution Models on Maximal Oxygen Uptake and Time-Trial Performance in Endurance Athletes: A Bayesian Network Meta-Analysis

ABSTRACT: Li, H, Yang, Q, and Wang, B. Effects of different training-intensity distribution models on maximal oxygen uptake and time-trial performance in endurance athletes: A Bayesian network meta-analysis. J Strength Cond Res XX(X): 000-000, 2026-Training intensity distribution (TID) describes how an athlete's total training time is allocated across low-, moderate-, and high-intensity zones. Training intensity distribution models are central to endurance training, but their relative effectiveness across key performance outcomes remains unclear. We conducted a Bayesian network meta-analysis to compare the effects of common TID models on maximal oxygen uptake (V̇o2max) and time-trial (TT) performance. Randomized controlled trials were retrieved from PubMed, Web of Science, EBSCO, the Cochrane Library, and Scopus, with risk of bias assessed using the Cochrane tool. Compared with polarized training, no other TID model showed a definite advantage for improving V̇o2max or TT performance, because all 95% credible intervals crossed zero. However, Bayesian posterior ranking indicated that lactate-threshold training (THR) was most likely to be the optimal model for V̇o2max (rank-1 probability = 65.4%, SUCRA = 84.8%), whereas high-intensity interval training (HIT) was most likely to optimize TT performance (rank-1 probability = 53.9%, SUCRA = 81.5%). Age, training status, intensity-quantification method, intervention duration, and sex were identified as potential moderators. Cluster analysis showed both shared and sport-specific TID patterns. Overall, coaches should tailor TID strategies to athlete characteristics and sport demands, with THR and HIT emerging as the most promising options for targeting V̇o2max and TT performance, respectively.