Using load-velocity relationships to quantify training-induced fatigue
School of Medical and Health Sciences/ Centre for Exercise and Sports Science Research
Hughes, LJ, Banyard, HG, Dempsey, AR, Peiffer, JJ, and Scott, BR. Using load-velocity relationships to quantify training-induced fatigue. J Strength Cond Res 33(3): 762-773, 2019-The purpose of this study was to investigate using load-velocity relationships to quantify fluctuations in maximal strength (1 repetition maximum [1RM]), which occur as a result of training-induced fatigue. The 19 well-trained men (age: 24.3 ± 2.9 years, height: 180.1 ± 5.9 cm, body mass: 84.2 ± 10.5 kg, and squat 1RM: 151.1 ± 25.7 kg) who were recruited for this study attended 5 sessions. After baseline strength testing, individual load-velocity relationships were established using mean concentric velocity during visits 2, 4, and 5, with visit 3 consisting of a bout of fatiguing exercise (5 sets of squats performed to muscular failure with 70% 1RM). Predicted 1RM values were calculated using the minimal velocity threshold (1RMMVT), load at zero velocity (1RMLD0), and force-velocity (1RMFV) methods. Measured 1RM, maximal voluntary contractions, and perceived muscle soreness were used to examine the effects of fatigue in relation to the predicted 1RM scores. The 1RMMVT and 1RMLD0 demonstrated very strong and strong correlations with measured 1RM during each of the sessions (r = 0.90-0.96 and r = 0.77-0.84, respectively), while no strong significant correlations were observed for the 1RMFV. Further analysis using Bland-Altman plots demonstrated substantial interindividual variation associated with each method. These results suggest that load-velocity-based 1RM predictions are not accurate enough to be used for daily training load prescription, as has been previously suggested. Nevertheless, these predictions are practical to implement during an individual's warm-up and may be useful to indicate general fluctuations in performance potential, particularly if used in conjunction with other common monitoring methods.