Resistance training is widely recognized as an effective method for improving athletic performance due to documented adaptations in muscular hypertrophy, maximal strength, rate of force development, and power output (28). The specific adaptive response to resistance training has been shown to be directly influenced by the configuration of a number of acute training variables, including loading magnitude, number of sets and repetitions, rest duration, and exercise type (23). Although the optimal combination of these training variables remains an area of interest, it seems that relative load and training volume (sets × repetitions) are the 2 most critical factors in determining the type and extent of resulting neurophysiological adaptations (14,29).
Although differing methods for determining training load exist, the most common method, traditionally known as percentage-based training (PBT), prescribes relative submaximal loads from a previously established 1 repetition maximum (1RM). This method is prevalent within the literature and has been shown to be valid and reliable across a range of populations (24). However, as maximal strength has been shown to fluctuate daily due to fatigue, and significantly increase due to continuous training, the method of prescribing relative load on potentially obsolete 1RMs has been questioned (11,15). Other methods, collectively referred to as autoregulatory, rely on an athlete’s understanding of their rating of perceived exertion or “repetitions in reserve” (16). These methods offer real-time load adjustment, based on an athlete’s perceived readiness to train. Although considered valid and reliable with trained populations, autoregulatory methods adjust load based on subjective input from the athlete, creating potential inconsistencies between athletes and sessions based on understanding. Furthermore, although these methods facilitate load adaptation within training, they require a minimum number of repetitions to be completed before interpretation, potentially fatiguing participants before load modification (16). Therefore, an alternative method able to provide instantaneous repetition feedback, enabling objective load modification, could augment adaptations while concurrently limiting training-induced fatigue.
A potential alternative, made more accessible with recent advancements in commercially available kinematic measuring devices, exploits the relationship documented between relative load and mean concentric velocity (MCV) (15,18). Research has demonstrated that movement velocity, which is dependent on both the magnitude of the load, and the voluntary intent to move it (7) influence neuromuscular stimuli and, thus, the adaptations consequent to resistance training. This load-velocity relationship, commonly termed the load-velocity profile (LVP), has been explored across a range of compound movements including bench press, back squat, and prone bench pull (9,15,26). Providing maximal concentric effort is applied during movement, an inverse linear relationship is present between load and MCV. Furthermore, as repetitions continue during a consistent range of motion, MCV will decrease as muscular fatigue develops. This understanding has made it possible to determine the relative load during a given movement in relation to an athlete’s current daily maximum and their MCV, providing an LVP has been established (15). Such findings have opened up the possibility of real-time monitoring of relative load, enabling specific adaptations to be targeted, factoring in training fatigue and strength fluctuations, as repetitions, sets, and periodization progresses.
Importantly, although LVPs have been shown to be reliable across repeat visits with trained athletes (5), limited research has explored the use of integrating LVPs into periodized resistance training as a method of adjusting training load. Previous literature exploring velocity-based training (VBT) has used the LVP as a means to prescribe load at a given concentric velocity, with participants instructed to complete all repetitions maximally. This maximal concentric method has been compared with various training modalities, with results generally supporting its use as a means to elicit adaptations in strength and power performance (12,13,20,22). Despite these prospective improvements, methodological discrepancies between the research designs limit the confidence surrounding the proposed conclusions. Issues such as lack of training variable control, participants training experience, use of a Smith machine as opposed to free-weight movements, undisclosed maturation status of youth participants, or unreliable velocity collection methods are present throughout. Furthermore, to date, no research has explored the effect of VBT when compared with traditional PBT methods.
Despite the perceived and demonstrated importance of lifting velocity and its relationship with optimal load prescription, no research currently exists comparing the effects of manipulating load based on a pre-established LVP. Therefore, the aim of the present research was to investigate the effects VBT have on the strength and power adaptations within resistance-trained men when compared with a traditional PBT approach. This aim was achieved through the implementation of MCV monitoring into a periodized resistance training program over a 6-week mesocycle. Addressing this will provide further insight into researchers and practitioners in making informed decisions about the use of velocity as a performance variable within athletic program design and monitoring.
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