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Kyle Davis, Stephen Rossi, Jody Langdon and Jim McMillan

The purpose of the present investigation was to examine the relationship between jumping and sprinting among members of a regionally competitive club-level ultimate team. Twenty-two subjects (mean ± SD; 21.1±2.26 year) volunteered to participate in two testing sessions the week before the team’s regional tournament. Testing sessions included body-composition measurement, a 40-yard sprint (with a 10-yard split time recorded), a standing long jump (LJ) and a vertical jump (VJ). Pearson product-moment correlations revealed a significant negative correlation between LJ and 40-yard sprint time. Significant positive relationships were observed between VJ height and 10-yard power, VJ power and 10-yard power, VJ power and relative 10-yard power, relative VJ power and relative 10-yard power, BJ distance and 10-yard power, VJ height and 40-yard power, VJ power and 40-yard power, and relative VJ power and relative 40-yard power. BJ distance related significantly to 40-yard velocity, 40-yard power and 40-yard relative power. There appears to be a relationship between jumping ability and sprinting in this population, but more studies with this population are needed to confirm these results.

Open access

Jennifer Sygo, Alicia Kendig Glass, Sophie C. Killer and Trent Stellingwerff

these events. The need to jump as high or as far as possible also demands that athletes maintain an optimal body mass (BM) and body composition that maximize their power–weight (power-to-weight) ratio. Throwing events, which include shot put (SP), discus throw, javelin throw (JT), and hammer throw (HT

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Trent Stellingwerff, Ingvill Måkestad Bovim and Jamie Whitfield

will focus on novel approaches. Regarding the appropriate macroperiodization of calories, a research field that has received much recent attention has been the relative energy deficiency in sport (RED-S) and the impact that chronic energy availability (EA) can have on health, body composition, and

Open access

Louise M. Burke, Linda M. Castell, Douglas J. Casa, Graeme L. Close, Ricardo J. S. Costa, Ben Desbrow, Shona L. Halson, Dana M. Lis, Anna K. Melin, Peter Peeling, Philo U. Saunders, Gary J. Slater, Jennifer Sygo, Oliver C. Witard, Stéphane Bermon and Trent Stellingwerff

, during, and after exercise to assist in optimizing training capacity, recovery, and body composition • Some evidence to support the use of a small number of supplements (e.g., caffeine and creatine, plus beta-alanine and bicarbonate for longer sprints) to assist in the training and/or competition

Open access

Trent Stellingwerff, James P. Morton and Louise M. Burke

adequate EI for optimal EA. If required, assess RED-S status indicators as outlined by Mountjoy et al. ( 2018) .  In relation to the training phase/block, what are the current and long-term body composition goals? Are changes even necessary? Strategic team discussions around risk and reward to optimize

Open access

Roberta Gaspar, Natalia Padula, Tatiana B. Freitas, João P.J. de Oliveira and Camila Torriani-Pasin

—that is, muscular atrophy, osteopenia/osteoporosis, hypertonia, and restrictions of joint mobility—body composition changes, and metabolic and cardiorespiratory disorders, which increase the risk of comorbidity secondary to injury. 7 – 9 Decline in muscle strength, endurance, and functional capacity are

Open access

International Olympic Committee Expert Group on Dietary Supplements in Athletes

evaluation, body composition analysis, biochemical testing, nutrition-focused clinical examination, and patient health and performance history. Assessment should take account of maturation status, sex, ethnicity and culture. The limitations and uncertainties in all of the methods employed must be recognised

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Jenny H. Conviser, Amanda Schlitzer Tierney and Riley Nickols

tests, gowned weights, body composition, bone health analysis, sitting/standing blood pressure, resting heart rate, electrocardiogram, and growth chart documentation for children and adolescents. Figure 2 —Signs and symptoms of eating disorders ( Academy of Eating Disorders, 2016 ). Figure 3 —Basic

Open access

Neil Armstrong and Jo Welsman

these criteria on each test occasion, totaling 1057 determinations of peak V ˙ O 2 . Data Analyses Data were analyzed using SPSS v24 software (IBM Corp, Armonk, NY). To explore age, body mass, and body composition relationships with peak V ˙ O 2 across the data set, Pearson correlation coefficients

Open access

Ben Desbrow, Nicholas A. Burd, Mark Tarnopolsky, Daniel R. Moore and Kirsty J. Elliott-Sale

outcome variables for consideration will be improvements in performance in endurance-specific sport or changes in body composition/metabolism that would influence performance. Given the well-known loss of muscle mass with human aging, it is particularly important for masters athletes to pay attention to