From the 2024 NSCA’s Coaches Conference, Kelly Jones helps coaches with practical nutrition strategies to maximize physical and mental performance, as well as optimal recovery methods.

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Deloading is a period of reduced training stress where training demand is intentionally reduced to mitigate physiological and psychological fatigue and promote recovery. A deload is commonly implemented to enhance readiness for subsequent training and occurs between or during training phases. During a deload, training is typically modified by reducing the intensity of effort, training volume, duration, or frequency. Adjustments in exercise selection are based on recovery goals and the specific demands of the athlete’s training. Deloads are commonly preplanned and implemented into the training program every 4–8 weeks based on the structure of the training cycle and recovery needs. Alternatively, deloads are sometimes applied reactively using an autoregulatory approach to accommodate unexpected fatigue or performance decrements. While deloading shares conceptual similarities with tapering and training cessation, it should be differentiated based on its objective, structure, and positionality with the overall training program. The purpose of this article is to describe the current research landscape, propose areas for future research, and to provide broad practical recommendations for implementing deloading within the strength and physique sports training program.

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An individual’s training status is a key factor used to determine the volume, the intensity, and the selection of exercises for resistance training prescription. Interestingly, there are no objective parameters to assess training status, so there is ambiguity in determining the appropriate volume and other resistance training variables in this regard. Thus, the objective of this study was to propose a strategy for classification and determination of resistance training status. The following five parameters were identified and used: (a) current uninterrupted training time, (b) time of detraining, (c) previous training experience, (d) exercise technique, and (e) strength level. Moreover, 4 classification levels are proposed: beginner, intermediate, advanced, and highly advanced, which are determined by the mean score of the parameters used. The proposed model represents an important advancement in training status classification and can be used as a valid tool for training prescription and for researchers to better characterize a sample and reproduce results under the same conditions in future studies.

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