In our no sample, Asian and Oceania players had the lowest standing stature and body mass, respectively. Pearson correlations or multiple regressions are often used to identify which anthropometric characteristics or physical capabilities can predict athletic performance (Chaouachi et al., 2009). Strength, power, and throwing velocity are important factors in elite handball players (Gorostiaga et al., 2006) and it has been suggested that this can be affected by body mass and stature (Chaouachi et al., 2009). Position-adjusted partial correlations showed that there were negative associations between the ranks of the teams and age (r = ?0.150; p=0.002), standing stature (r = ?0.398; p=0.0001), and body mass (r = ?0.253; p=0.0001; Table 5). Chaouachi et al.

(2009) demonstrated that body height and body mass were not significantly related to standing throw velocity in Tunisian national handball players (Chaouachi et al., 2009). In conclusion, this study presented anthropometric data on more and less successful male handball teams that participated in the 2013 World Championships. Furthermore, this study confirms and expands on previous data about anthropometric differences among playing positions and continents in handball. The measurement of anthropometric characteristics provides an insight into the current status of handball players, allowing coaches to evaluate typical characteristics of elite performers. This information should serve as a reference for what the average standing stature, body mass, and BMI of handball players may be for positions at the professional level.

This date can be used to develop a model of elite handball performance which can be used to supplement talent identification programs, and also in the construction of effective player development programs.
Resistance training (RT) has been consistently used as an efficient training method for the development of muscular strength, power, and hypertrophy (ACSM, 2009a; Folland and Williams, 2007). A primary concern of the prescription of RT should take into account the individual��s goals to be achieved (ACSM, 2011). For this reason, the interaction of loading variables should be carefully considered during the prescription of RT programs such as the type of exercise, load, number of repetitions, number of sets, type of muscular contraction, speed, rest interval between sets and exercises, and also exercise order (Miranda et al.

, 2010; Sim?o et al., 2012). Several studies have been investigated one or more of the aforementioned variables in children and youth (Faigenbaum et al., 1999, 2008, 2009). However, to date, no study has been identified describing the effects of different exercise orders on the number of repetitions in children and/or youth. On the other hand, different authors have studied GSK-3 the effects of these variables among adults (Miranda et al., 2010; Sfrozo and Touey, 1996; Sim?o et al., 2005, 2012).