significantly between each group (Figure 1 ), whereby HIGH > MOD > LOW at every time point (weeks 1–6; P < .05 for all). Training volume did not significantly change over the 6-week intervention for LOW but did increase weekly from week 3 onward for MOD and HIGH only ( P < .05), with the exception of week 6
Samuel R. Heaselgrave, Joe Blacker, Benoit Smeuninx, James McKendry and Leigh Breen
Mathieu Lacome, Simon Avrillon, Yannick Cholley, Ben M. Simpson, Gael Guilhem and Martin Buchheit
-to-likely small increase in BFlh and SM fascicle length; (2) the effects of this low-volume program were similar to those observed following a program including 4 times more repetitions; and (3) after 6 weeks, the increase in training volume in the low-volume group did not result in further strength gain or
Joanne E. Richards, Timothy R. Ackland and Bruce C. Elliott
Thirty-seven females, aged initially between 10 and 13.5 years, completed a mixed longitudinal study over 3.3 years to investigate the effect of training volume and growth upon gymnastic performance. Gymnasts undergoing high volume training (mean = 30 hrs/week: Group 1) and moderate volume training (mean = 15 hrs/week: Group 2) were tested at 4-month intervals on growth measures including height, mass, skinfolds, and segment lengths, as well as the strength of lower limb, upper limb, and trunk musculature. Functional gymnastic development was observed through the assessment of generic, whole body rotation tasks, a vertical jump, and a v-sit action. The high training volume gymnasts were significantly smaller but markedly stronger than those gymnasts in Group 2 despite the size disadvantage. Consequently, Group 1 gymnasts were able to produce higher velocities for front and backward rotations and a faster v-sit action. These training group differences remained significant after initial size differences were taken into account via an analysis of covariance.
Laurent Schmitt, Stéphane Bouthiaux and Grégoire P. Millet
For many years, the French Nordic-ski national teams periodized their training loads with the “polarized” principle. 1 This method emphasizes the major influence of high training volume performed at low intensity. 2 – 5 The “polarized” principle, 1 with a “75-5-20” training intensity
This study examined clinical and subclinical eating disorders (EDs) in young Norwegian modern rhythmic gymnasts. Subjects were 12 members of the national team, age 13-20 years, and individually matched nonathletic controls. All subjects participated in a structured clinical interview for EDs, medical examination, and dietary analysis. Two of the gymnasts met the DSM-III-R criteria for anorexia nervosa, and 2 met the criteria for anorexia athletica (a subclinical ED). AH the gymnasts were dieting in spite of the fact that they were all extremely lean. The avoidance of maturity, menstrual irregularities, energy deficit, high training volume, and high frequency of injuries were common features among the gymnasts. There is a need to learn more about risk factors and the etiology of EDs in different sports. Coaches, parents, and athletes need more information about principles of proper nutrition and methods to achieve ideal body composition for optimal health and athletic performance.
Dean Ritchie, Will G. Hopkins, Martin Buchheit, Justin Cordy and Jonathan D. Bartlett
Training volume, intensity, and distribution are important factors during periods of return to play.
To quantify the effect of injury on training load (TL) before and after return to play (RTP) in professional Australian Rules football.
Perceived training load (RPE-TL) for 44 players was obtained for all indoor and outdoor training sessions, while field-based training was monitored via GPS (total distance, high-speed running, mean speed). When a player sustained a competition time-loss injury, weekly TL was quantified for 3 wk before and after RTP. General linear mixed models, with inference about magnitudes standardized by between-players SDs, were used to quantify effects of lower- and upper-body injury on TL compared with the team.
While total RPE-TL was similar to the team 2 wk before RTP, training distribution was different, whereby skills RPE-TL was likely and most likely lower for upper- and lower-body injury, respectively, and most likely replaced with small to very large increases in running and other conditioning load. Weekly total distance and high-speed running were most likely moderately to largely reduced for lower- and upper-body injury until after RTP, at which point total RPE-TL, training distribution, total distance, and high-speed running were similar to the team. Mean speed of field-based training was similar before and after RTP compared with the team.
Despite injured athletes’ obtaining comparable TLs to uninjured players, training distribution is different until after RTP, indicating the importance of monitoring all types of training that athletes complete.
Heather K. Larson, Bradley W. Young, Tara-Leigh F. McHugh and Wendy M. Rodgers
training volume, from ages 6 to 12 years. Athlete Burnout Questionnaire The Athlete Burnout Questionnaire ( Raedeke & Smith, 2001 ) measures three dimensions (emotional/physical exhaustion, reduced sense of accomplishment, and sport devaluation) with five items each. Swimmers were presented with statements
Harry G. Banyard, James J. Tufano, Jose Delgado, Steve W. Thompson and Kazunori Nosaka
research has individualized training volume prescription (number of repetitions per set), 9 – 11 but, notably, no research has used velocity to individualize training load prescription (load–velocity relationship). Additionally, participants within these studies have used a Smith machine and not a large
Miguel Sánchez-Moreno, David Rodríguez-Rosell, Fernando Pareja-Blanco, Ricardo Mora-Custodio and Juan José González-Badillo
) evaluate an athlete’s strength without the need to perform 1RM or XRM tests; (2) determine the %1RM that is being used as soon as the first repetition with a given load is performed with maximal voluntary velocity. 5 Training volume is another important variable for configuring the training load in RT
Alex S. Ribeiro, Matheus A. Nascimento, Brad J. Schoenfeld, João Pedro Nunes, Andreo F. Aguiar, Edilaine F. Cavalcante, Analiza M. Silva, Luís B. Sardinha, Steven J. Fleck and Edilson S. Cyrino
the proper manipulation of variables that make up the RT prescription, such as intensity, volume, exercise order and selection, and other training variables ( Borde, Hortobágyi, & Granacher, 2015 ; Ratamess et al., 2009 ; Schoenfeld, 2010 ). Training volume is affected by training frequency, defined