Tapering and Peaking Maximal Strength for Powerlifting Performance: A Review

Travis, S. Kyle; Mujika, Iñigo; Gentles, Jeremy A.; Stone, Michael H.; Bazyler, Caleb D.

doi:10.3390/sports8090125

Cited by 30 publications

(65 citation statements)

References 64 publications

(129 reference statements)

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“…Lastly, our results support the theoretical basis of a competitive taper. Previous research [ 60 ] has indicated that the purpose of a competitive taper is to lower fatigue while increasing readiness. This can be accomplished by reducing training volume, intensity, and possibly training cessation.…”

Section: Discussionmentioning

confidence: 99%

Strength, Endocrine, and Body Composition Alterations across Four Blocks of Training in an Elite 400 m Sprinter

Batra

Wetmore

Hornsby

et al. 2021

JFMK

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The ability to produce force rapidly has the potential to directly influence sprinting performance through changes in stride length and stride frequency. This ability is commonly referred to as the rate of force development (RFD). For this reason, many elite sprinters follow a combined program consisting of resistance training and sprint training. The purpose of this study was to investigate the strength, endocrine and body composition adaptations that occur during distinct phases of a block periodized training cycle in a 400 m Olympic level sprinter. The athlete is an elite level 400 m male sprinter (age 31 years, body mass: 74 kg, years of training: 15 and Personal Best (PB): 45.65 s). This athlete completed four distinct training phases of a block periodized training program (16 weeks) with five testing sessions consisting of testosterone:cortisol (T/C) profiles, body composition, vertical jump, and maximum strength testing. Large fluctuations in T/C were found following high volume training and the taper. Minor changes in body mass were observed with an abrupt decrease following the taper which coincided with a small increase in fat mass percentage. Jump height (5.7%), concentric impulse (9.4%), eccentric impulse (3.4%) and power ratio (18.7%) all increased substantially from T1 to T5. Relative strength increased 6.04% from T1 to T5. Lastly, our results demonstrate the effectiveness of a competitive taper in increasing physiological markers for performance as well as dynamic performance variables. Block periodization training was effective in raising the physical capabilities of an Olympic level 400 m runner which have been shown to directly transfer to sprinting performance.

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Section: Discussionmentioning

confidence: 99%

Strength, Endocrine, and Body Composition Alterations across Four Blocks of Training in an Elite 400 m Sprinter

Batra

Wetmore

Hornsby

et al. 2021

JFMK

Self Cite

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“…Thus, performing a 1RM is considered a maximal dynamic effort. Once this value is known, programming of RT is done prescribing relative loads to the individual’s 1RM [ 14 , 15 ]. However, this methodology comes with certain disadvantages.…”

Section: The Challenges and Drawbacks Of The 1-repetition Maximum Paradigmmentioning

confidence: 99%

The Implementation of Velocity-Based Training Paradigm for Team Sports: Framework, Technologies, Practical Recommendations and Challenges

Balsalobre-Fernández

Torres-Ronda

2021

Sports

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While velocity-based training is currently a very popular paradigm to designing and monitoring resistance training programs, its implementation remains a challenge in team sports, where there are still some confusion and misinterpretations of its applications. In addition, in contexts with large squads, it is paramount to understand how to best use movement velocity in different exercises in a useful and time-efficient way. This manuscript aims to provide clarifications on the velocity-based training paradigm, movement velocity tracking technologies, assessment procedures and practical recommendations for its application during resistance training sessions, with the purpose of increasing performance, managing fatigue and preventing injuries. Guidelines to combine velocity metrics with subjective scales to prescribe training loads are presented, as well as methods to estimate 1-Repetition Maximum (1RM) on a daily basis using individual load–velocity profiles. Additionally, monitoring strategies to detect and evaluate changes in performance over time are discussed. Finally, limitations regarding the use of velocity of execution tracking devices and metrics such as “muscle power” are commented upon.

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“…Reggiani et al [664] showed that the increase in muscle mass did not necessarily lead to increase in strength and vice versa [664], and in worst case, the increase in muscle mass was shown to decrease strength production [664,718]. There also seems to exist multiple types of muscle hypertrophy [664,820], with the concept of task-specic hypertrophy [820] becoming relevant when trying to transfer the gains from strength training program to improvements in the particular sport of the athlete [906]. For instance sports as dierent as combat sports [485,765] and ballet [16,180,818], can be beneted for similar plyometric/ballistic training for explosive force production [906] mixed with some maximum strength training.…”

Section: Precision Strength Trainingmentioning

confidence: 99%

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Teikari¹,

Pietrusz²

2021

Preprint

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In strength training, personalised strength training (autoregulation) approaches have been used to individualise exercise programs with monitoring an for dynamic adjustment based on their responses to training. While this transition from tradition-based training to evidence-based training framework has been an improvement in training practices, we argue that the future of strength training will also incorporate deep learning models powered by data. We refer to this data-driven framework as precision strength training inspired by the similar modeling frameworks used in precision medicine. In contrast to current personalised training in which the acquired athlete data is often subject to human expert decision-making, we are anticipating the rise of human-in-the-loop systems with an augmented coach who will be doing decisions collaboratively with the machine. Similar to other precision frameworks, such as precision health, we envision such a future to take decades to be realised and we focus here on practical short-term targets on a way to long-term realisation. In this chapter, we will review the measurement technology needed for continuous data acquisition from an individual during training/physical activity, how to acquire these datasets for the development of such systems and, how a proof-of-concept system could be developed for powerlifting training with applicability to general strength and conditioning (S&C) and physical rehabilitation purposes. Additionally, we will evaluate how the user experience (UX) of the system feedback and visualisation could be designed.

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Tapering and Peaking Maximal Strength for Powerlifting Performance: A Review

Cited by 30 publications

References 64 publications

Strength, Endocrine, and Body Composition Alterations across Four Blocks of Training in an Elite 400 m Sprinter

Strength, Endocrine, and Body Composition Alterations across Four Blocks of Training in an Elite 400 m Sprinter

The Implementation of Velocity-Based Training Paradigm for Team Sports: Framework, Technologies, Practical Recommendations and Challenges

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

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