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Scott McLean, Hugo A. Kerhervé, Nicholas Stevens, and Paul M. Salmon

In recent years, scrutiny on sport-science research has intensified from both internal and external sources. 1 , 2 Several debates have arisen concerning methodological and theoretical issues, such as magnitude-based inferences (MBI) 3 and the acute chronic workload ratio (ACWR). 4 For example

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Israel Halperin, Andrew D. Vigotsky, Carl Foster, and David B. Pyne

Over the passing years, exercise and sport sciences have developed into a large field of study consisting of several disciplines including physiology, biomechanics, psychology, nutrition, performance analysis, motor learning and control, strength and conditioning, and sports medicine. Much like

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Iñigo Mujika and Ritva S. Taipale

performed on female athletes: 2 studies were conducted on synchronized swimmers (now called artistic swimmers), 1 on handball players, and 1 on soccer players. By contrast, one of us (R.S.T.) has made a career in sport science by mainly studying women and sex differences in responses and adaptations to

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Shona L. Halson and David T. Martin

“gold-medal-winning factory.” In an attempt to increase international competitiveness, many countries built their own centralized elite sport centers. 2 East Germany learned from the Soviet Union, and with heavy state funding, exceptional facilities, committed coaching, and sport science support, the

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Iñigo Mujika and David B. Pyne

, or dwindling motivation are all factors we recognize in sport. Many of these also apply in occupational, employment, and professional settings, including sport-science practice and research. When the drum of moving on starts to beat louder and longer it’s time for self-reflection and decision making

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Patrick Ward, Johann Windt, and Thomas Kempton

Sport science, the application of scientific principles to inform practice, 1 has become increasingly common as professional sporting organizations seek to gain a performance advantage. These organizations increasingly employ sport scientists from varying backgrounds including physiology, strength

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Tim Newans, Phillip Bellinger, Christopher Drovandi, Simon Buxton, and Clare Minahan

pre-average data before running analyses. 18 Therefore, it is reasonable to suggest that mixed models are the most appropriate statistical methodology to analyze longitudinal data sets often acquired by sports scientists. This aligns with previous guidance by Hopkins et al 19 in encouraging sport-science

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Alan D. Ruddock, Craig Boyd, Edward M. Winter, and Mayur Ranchordas

from the goal of becoming an Olympic champion or an Olympian might be 8 hours away. • Why do they seek scientific support? • What are their expectations of support? • What support have they had previously? To identify what the athlete thinks of sport sciences and to understand their expectations of

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Iñigo Mujika

nature of sport science both in the field with coaches and athletes and in academic circles. These metrics are easily generated, but the challenge is to identify and articulate the impact of sport science. For instance, these numbers were achieved while simultaneously helping individual athletes and

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Carl Foster

Sport science can mean a lot of different things. At one level, it can be the collation and transmission of scientific findings to coaches and athletes. At another, it can be the evaluation of athletes in the laboratory, intended to give the coach a venue free view of the current status and