AUTHOR=Yang Woo-Hwi , Park So-Young , Kim Taenam , Jeon Hyung-Jin , Heine Oliver , Gehlert Sebastian TITLE=A modified formula using energy system contributions to calculate pure maximal rate of lactate accumulation during a maximal sprint cycling test JOURNAL=Frontiers in Physiology VOLUME=Volume 14 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2023.1147321 DOI=10.3389/fphys.2023.1147321 ISSN=1664-042X ABSTRACT=Purpose: This study aimed to compare previous calculating formulas of maximal lactate accumulated rate (vLa.max) and a modified formula of pure vLa.max (PvLa.max) during a 15-s all-out sprint cycling test (ASCT) and to analyze their relationships. Methods: Thirty male national-level track cyclists participated in this study (n =30). They performed a 15-s ASCT. Anaerobic power output (Wpeak and Wmean), oxygen uptake, and blood lactate concentrations (La−) were measured. These parameters were used for different calculations of vLa.max and three energy contributions (phosphagen; WPCr, glycolytic; WGly, and oxidative; WOxi). PvLa.max calculation considered delta La−, time until Wpeak (tPCr−peak), and contributed time of the oxidative system (tOxi). Other vLa.max levels without tOxi were calculated using decreased time by 3.5% from Wpeak (tPCr −3.5%) and tPCr−peak. Results: Absolute and relative WPCr showed higher values compared to WGly and WOxi. Absolute and relative WGly were significantly higher than WOxi (p < 0.0001, respectively). vLa.max (tPCr −3.5%) was significantly higher than PvLa.max and vLa.max (tPCr−peak) while vLa.max (tPCr−peak) was lower than PvLa.max (p < 0.0001, respectively). A very strong correlation between PvLa.max and vLa.max (tPCr−peak) was found (r = 0.99, R2 = 0.98). It was higher than the relationship between PvLa.max and vLa.max (tPCr −3.5%) (r = 0.87, R2 = 0.77). vLa.max (tPCr−peak), PvLa.max, and vLa.max (tPCr −3.5%) correlated with absolute Wmean and WGly. Conclusions: PvLa.max as a modified calculation of vLa.max provides more detailed insights into inter-individual differences in energy and glycolytic metabolism than vLa.max (tPCr−peak) and vLa.max (tPCr −3.5%). Because WOxi and WPCr can differ remarkably between athletes, implementing those values in PvLa.max can establish more optimized individual profiling for elite track cyclists.