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Darren J. Burgess

Research describing load-monitoring techniques for team sport is plentiful. Much of this research is conducted retrospectively and typically involves recreational or semielite teams. Load-monitoring research conducted on professional team sports is largely observational. Challenges exist for the practitioner in implementing peer-reviewed research into the applied setting. These challenges include match scheduling, player adherence, manager/coach buy-in, sport traditions, and staff availability. External-load monitoring often attracts questions surrounding technology reliability and validity, while internal-load monitoring makes some assumptions about player adherence, as well as having some uncertainty around the impact these measures have on player performance This commentary outlines examples of load-monitoring research, discusses the issues associated with the application of this research in an elite team-sport setting, and suggests practical adjustments to the existing research where necessary.

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Gordon G. Sleivert

Wireless microtechnologies are rapidly emerging as useful tools for sport scientists to move their work out of the laboratory and into the field. The purpose of this report is to describe some of the practical aspects of using ingestible radiotelemetric temperature sensors in sport physiology. Information is also presented to demonstrate the utility of this technology in understanding individual differences in coping with environmental stress, optimizing heat adaptation, and fine-tuning competition strategy (pacing). Wireless core-temperature technology has already revolutionized field monitoring of elite athletes training and competing in extreme environments. These technologies are valuable tools for sport scientists to better understand the interaction between the physiology of exercise and the environment.

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Benoit Capostagno, Michael I. Lambert, and Robert P. Lamberts

Finding the optimal balance between high training loads and recovery is a constant challenge for cyclists and their coaches. Monitoring improvements in performance and levels of fatigue is recommended to correctly adjust training to ensure optimal adaptation. However, many performance tests require a maximal or exhaustive effort, which reduces their real-world application. The purpose of this review was to investigate the development and use of submaximal cycling tests that can be used to predict and monitor cycling performance and training status. Twelve studies met the inclusion criteria, and 3 separate submaximal cycling tests were identified from within those 12. Submaximal variables including gross mechanical efficiency, oxygen uptake (VO2), heart rate, lactate, predicted time to exhaustion (pTE), rating of perceived exertion (RPE), power output, and heart-rate recovery (HRR) were the components of the 3 tests. pTE, submaximal power output, RPE, and HRR appear to have the most value for monitoring improvements in performance and indicate a state of fatigue. This literature review shows that several submaximal cycle tests have been developed over the last decade with the aim to predict, monitor, and optimize cycling performance. To be able to conduct a submaximal test on a regular basis, the test needs to be short in duration and as noninvasive as possible. In addition, a test should capture multiple variables and use multivariate analyses to interpret the submaximal outcomes correctly and alter training prescription if needed.

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Jordan L. Fox, Aaron T. Scanlan, Robert Stanton, Cody J. O’Grady, and Charli Sargent

basketball players, given differences in sleep patterns between young people and adults, 8 and differences in approaches used to monitor player workloads during soccer and basketball. Young people typically have different sleep patterns in adults 9 and are subject to different scheduling considerations

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Darren J. Paul, Gustavo Tomazoli, and George P. Nassis

Recovery monitoring is a staple feature in the daily routine of most professional football clubs. The objective is to measure changes in fatigue/stress and recovery and, when appropriate, take action to avoid overtraining or exposure to high loads. 1 Several different tools are used either alone

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John F. Fitzpatrick, Kirsty M. Hicks, and Philip R. Hayes

, with training load monitored throughout the period. Before inclusion in this study, players were examined by the club medical staff and were deemed to be free from illness and injury. This study was granted institutional ethics approval from Northumbria University prior to commencement and conformed to

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Joel M. Garrett, Stuart R. Graham, Roger G. Eston, Darren J. Burgess, Lachlan J. Garrett, John Jakeman, and Kevin Norton

after games and training. 1 , 5 For the monitoring of neuromuscular fatigue (NMF) within high-performance team sports environments, the countermovement jump (CMJ) test is recognized as the reference standard test. 6 , 7 It has been shown to possess both robust reliability and validity 1 , 6 , 8 , 9

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Alberto Franceschi, Daniele Conte, Marco Airale, and Jaime Sampaio

imposed, the athlete’s readiness, and the risk associated with changes in load, with the ultimate goal of assisting the coaches in their decision-making process. 5 Despite the growing interest on athlete monitoring systems, there is a paucity of real examples of the preparation of elite athletes in

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Michael J. Rose, Michael P. LaValley, S. Reza Jafarzadeh, Kerry E. Costello, Nirali Shah, Soyoung Lee, Belinda Borrelli, Stephen P. Messier, Tuhina Neogi, and Deepak Kumar

were active in the study at different times. The intervention period was followed by a 6-month observation period. During the 6-month intervention period, participants in both groups continuously wore a wrist-worn activity monitor on their nondominant wrist (Charge 3, Fitbit) and completed weekly

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Joseph O.C. Coyne, Sophia Nimphius, Robert U. Newton, and G. Gregory Haff

Monitoring training and competition workload (TL) has become increasingly popular in sport research focusing on decreasing the risk of injury. 1 , 2 One variable that has received increasing interest is the acute to chronic workload ratio (ACWR). The ACWR was originally calculated as the 7-day