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Irineu Loturco, Lucas A. Pereira, Ciro Winckler, Weverton L. Santos, Ronaldo Kobal and Michael McGuigan

The load–velocity relationship is widely recognized for its ability to accurately predict the 1-repetition maximum (1RM) in both lower-body and upper-body exercises. 1 – 3 With the data generated by linear-regression models, practitioners can frequently monitor and adjust the resistance

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Francisco Luis Pestaña-Melero, G. Gregory Haff, Francisco Javier Rojas, Alejandro Pérez-Castilla and Amador García-Ramos

be compromised in free-weight exercises. 7 , 14 The load–velocity relationship has been used to predict 1RM with both linear 6 , 7 , 13 and polynomial regression models. 10 , 15 However, to the authors knowledge, no study has determined which of these 2 regression models provides the most reliable

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Alejandro Pérez-Castilla, Antonio Piepoli, Gabriel Garrido-Blanca, Gabriel Delgado-García, Carlos Balsalobre-Fernández and Amador García-Ramos

velocity. 5 – 7 A practical question that remains virtually unexplored is whether wearable wireless devices could predict a 1RM with an accuracy comparable with the most commonly used linear position and velocity transducers. Recent studies have recommended the individual load–velocity relationship for

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Alejandro Pérez-Castilla, Daniel Jerez-Mayorga, Dario Martínez-García, Ángela Rodríguez-Perea, Luis J. Chirosa-Ríos and Amador García-Ramos

). Figure 1 —Load–velocity relationships obtained for the bench-press exercise performed on a Smith machine using a narrow grip width (upper left), a medium grip width (upper right), a wide grip width (lower left), and a self-selected grip width (lower right). 1RM indicates 1-repetition maximum; N, number

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Amador García-Ramos, Guy Gregory Haff, Francisco Luis Pestaña-Melero, Alejandro Pérez-Castilla, Francisco Javier Rojas, Carlos Balsalobre-Fernández and Slobodan Jaric

proposed to predict the 1RM. 6 , 9 – 11 The indirect method that has received the most attention in recent years is to predict the 1RM based on the load–velocity relationship. 6 , 9 , 12 , 13 Several studies have reported a strong linear relationship between movement velocity and relative load (%1RM) in a

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Samuel T. Orange, James W. Metcalfe, Ashley Robinson, Mark J. Applegarth and Andreas Liefeith

may indicate enhanced muscle strength. 11 Therefore, VBT can be used to manipulate training load according to the athlete’s current physiological state. Although several VBT approaches exist, recent research has encouraged the use of individualized load–velocity relationships. 12 – 14 This method

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Harry G. Banyard, James J. Tufano, Jose Delgado, Steve W. Thompson and Kazunori Nosaka

research has individualized training volume prescription (number of repetitions per set), 9 – 11 but, notably, no research has used velocity to individualize training load prescription (load–velocity relationship). Additionally, participants within these studies have used a Smith machine and not a large

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Harry G. Banyard, James J. Tufano, Jonathon J.S. Weakley, Sam Wu, Ivan Jukic and Kazunori Nosaka

velocity can accurately determine a %1RM value throughout the entire load–velocity relationship ( r  = .97–.99). 9 , 13 This infers that relative strength levels (%1RM) can be determined on any particular day, according to the repetition velocity. Moreover, coaches can prescribe sessional target

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Amador García-Ramos, Francisco Luis Pestaña-Melero, Alejandro Pérez-Castilla, Francisco Javier Rojas and Guy Gregory Haff

recorded by linear position transducers. It should be noted that all the studies that have determined the load–velocity relationship in the concentric-only BP have reported very similar velocities for a given %1RM. 9 , 10 , 15 Collectively, these results offer support for the use of general equations to

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Jorge Carlos-Vivas, Elena Marín-Cascales, Tomás T. Freitas, Jorge Perez-Gomez and Pedro E. Alcaraz

to describe the load–velocity relationship in sprinting using WV in semiprofessional soccer players and to investigate the effects of increasing loads on spatiotemporal and derived kinetics variables. Furthermore, we aimed to determine which load maximized power output. We hypothesized: (1) an