Sports medicine (Auckland, N.Z.) · 2026
35 Years of Joyner's Endurance Performance Model: Assessing the Contribution of Physiological Determinants of Performance Proxies in 888 Individuals from Recreational to World Class.
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Mougin Loïs, Bailey Stephen J, Jones Andrew M, Joyner Michael J, Mears Stephen A, Pearce Rhona, Zanini Michele
Аннотация
BACKGROUND: Endurance performance is predicted by maximal oxygen uptake, its fractional utilisation at lactate threshold (FULT) and exercise economy. These variables are used to estimate speed or power at lactate threshold (LT) and lactate turnpoint (LTP), which serve as performance proxies.
OBJECTIVE: This study examined the relationships between these variables in a large cohort of runners and cyclists and quantified their relative contributions to performance prediction.
METHODS: 495 runners (105 females) and 393 cyclists (42 females) completed incremental exercise tests to determine maximal oxygen uptake (running [R]: 56 mL/kg/min, 3.94 L/min; cycling [C]: 52 mL/kg/min, 3.99 L/min), economy (R: 220 mL/kg/km; C: 14.7 mL/min/W), FULT (R: 78%; C: 70%), FULTP (R: 88%; C: 84%), and speed or power at LT (R: 12.0 km/h; C: 190 W) and LTP (R: 13.9 km/h; C: 240 W). Single and multiple linear regression models were used to examine the relationship and relative contribution of physiological determinants to performance proxies.
RESULTS: Speed or power at LT and LTP correlated strongly and positively with maximal oxygen uptake (R2 = 0.65-0.77; P < 0.001), and inversely with economy (R2 = 0.24-0.26; P < 0.001). In contrast, trivial relationships were observed with FULT (R2 ≤ 0.04; P = 0.01-0.05) or FULTP (R2 ≤ 0.01; P = 0.01-0.09). Regression models estimating LT and LTP from physiological determinants showed very strong agreement with measured performance proxies (R2 = 0.94-0.99; P < 0.001), indicating consistency in their relative contribution to performance proxies. Maximal oxygen uptake contributed most to performance proxies (65-76%) followed by running economy (20-24%), with marginal contributions from FULT or FULTP (4-11%).
CONCLUSIONS: These results indicate that maximal oxygen uptake and economy collectively predict ~ 95% of speed or power at LT and LTP, and by extension performance, whilst the contribution of FULT or FULTP is limited in populations with heterogeneous characteristics.
OBJECTIVE: This study examined the relationships between these variables in a large cohort of runners and cyclists and quantified their relative contributions to performance prediction.
METHODS: 495 runners (105 females) and 393 cyclists (42 females) completed incremental exercise tests to determine maximal oxygen uptake (running [R]: 56 mL/kg/min, 3.94 L/min; cycling [C]: 52 mL/kg/min, 3.99 L/min), economy (R: 220 mL/kg/km; C: 14.7 mL/min/W), FULT (R: 78%; C: 70%), FULTP (R: 88%; C: 84%), and speed or power at LT (R: 12.0 km/h; C: 190 W) and LTP (R: 13.9 km/h; C: 240 W). Single and multiple linear regression models were used to examine the relationship and relative contribution of physiological determinants to performance proxies.
RESULTS: Speed or power at LT and LTP correlated strongly and positively with maximal oxygen uptake (R2 = 0.65-0.77; P < 0.001), and inversely with economy (R2 = 0.24-0.26; P < 0.001). In contrast, trivial relationships were observed with FULT (R2 ≤ 0.04; P = 0.01-0.05) or FULTP (R2 ≤ 0.01; P = 0.01-0.09). Regression models estimating LT and LTP from physiological determinants showed very strong agreement with measured performance proxies (R2 = 0.94-0.99; P < 0.001), indicating consistency in their relative contribution to performance proxies. Maximal oxygen uptake contributed most to performance proxies (65-76%) followed by running economy (20-24%), with marginal contributions from FULT or FULTP (4-11%).
CONCLUSIONS: These results indicate that maximal oxygen uptake and economy collectively predict ~ 95% of speed or power at LT and LTP, and by extension performance, whilst the contribution of FULT or FULTP is limited in populations with heterogeneous characteristics.