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The linear regression model provides the force-velocity relationship parameters with the highest reliability.

Alejandro Pérez CastillaPierre SamozinoIvan JukicEliseo Iglesias-SolerAmador García Ramos
Published in: Sports biomechanics (2022)
An a-posteriori multicentre reliability study was conducted to compare the between-session reliability of the force-velocity relationship parameters (force-intercept [ F 0 ], velocity-intercept [ v 0 ], and maximum power [P max ]) between different regression models during the bench press (BP) and bench press throw (BPT) exercises. Data from four and three studies were considered for the BP (n = 102) and BPT (n = 81) exercises, respectively. The force-velocity relationships were determined using five regression models: linear multiple-point, linear two-point, quadratic polynomial, hyperbolic, and exponential. All regression models provided F 0 and P max with acceptable reliability (cut-off CV ≤ 9.45%; cut-off ICC ≥ 0.79) with the exceptions of F 0 for the quadratic polynomial and hyperbolic models (BPT) and P max for the exponential model (BP and BPT). Only the linear multiple- and linear two-point models provided v 0 with acceptable absolute reliability (cut-off CV ≤ 7.72%). Regardless of the exercise, the reliability of the three parameters was generally higher for the linear multiple- and two-point models compared to the other models (CV ratio ≥ 1.22), and no significant differences were observed between multiple- and linear two-point models (CV ratio ≤ 1.11). Linear regression models are recommended to maximise the reliability of the force-velocity relationship parameters during the BP and BPT exercises.
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