Ce with this, the purposes of this study were (a) to examine the morphologic-, fitness-, handball-specific skills and psychological and “biosocial” differences between top elite and nontop elite team-handball players and (b) to investigate the extent to which they may be used to identify top elite team-handball players. One hundred sixty-seven adult male team-handball players were studied and divided in 2 groups: top elite (n = 41) and nontop elite (n = 126). Twenty-eight morphologic-, 9 fitness-, 1 handball-specific skills and 2 psychological-based and 2 “biosocial”-based attributes were used. Top elite and nontop elite groups were compared for each variable of interest using Student's t-test, and 5 logistic regression analyses were performed with the athlete's performance group (top elite or nontop elite) as the dependent variable and the variables of each category as predictors. The results showed that (a) body mass, waist girth, radiale-dactylion length, midstylion-dactylion length, and absolute muscle mass (morphologic model); (b) 30-m sprint time, countermovement jump height and average power, abdominal strength and the class of performance in the Yo-Yo Intermittent Endurance Test (fitness model); (c) offensive power (specific-skills model); (d) ego-based motivational orientation (psychological model); (e) socioeconomic status and the energy spent (for week) in handball activity (biosocial model); significantly (p < 0.05) contributed to predict the probability of an athlete to be a top elite team-handball player. Moreover, the fitness model exhibited higher percentages of correct classification (i.e., 91.5%) than all the other models did. This study provided (a) the rational to reduce the battery of tests for evaluation purposes, and (b) the initial step to work on building a multidisciplinary model to predict the probability of a handball athlete to be a top elite player....

Background: Physical activity (PA) is beneficial, enhancing healthy development. However, one-third of school-age children practicing sports regularly suffer from an injury. These injuries are associated with sex, chronological age, and PA level. Purpose: To identify the importance of age, PA level, and maturity as predictors of injury in Portuguese youth. Study Design: Descriptive epidemiological study. Level of Evidence: Level 3. Methods: Information about injury and PA level was assessed via 2 questionnaires (LESADO RAPIL II) from 647 subjects aged 10 to 17 years. Maturity offset according to Mirwald (time before or after peak height velocity) and Tanner-Whitehouse III bone age estimates were used to evaluate maturation. Binary logistic regression and gamma regression were used to determine significant predictors of injury and injury rate. Results: Injury occurrence was higher for both sexes in recreational, school, and federated athletes (athletes engaged in sports that are regulated by their respective federations, with formal competition). These injuries also increased with age in boys and in the higher maturity offset group in girls. Injury rate was higher for both sexes in the no sports participation group. Early-maturing girls, with higher bone age and lower maturity offset, showed higher injury rate. Conclusion: Injuries in Portuguese youth were related to PA level, age, and biological maturation. Recreational, school, and federated athletes had more injury ocurrences while subjects with no sports participation had higher injury risk. Older subjects had more injuries. Early-maturing girls that had just passed peak height velocity may be particularly vulnerable to risk of sports injury because of the growing process. Clinical Relevance: Increased knowledge about injury with specific PA exposure data is important to an overall risk management strategy. This study has deepened the association between injury and biological maturation variables.

The present study aims (i) to compare the maturational, morphological and fitness attributes of young basketball players of primary and secondary teams of an elite basketball academy, and (ii) to identify the set of morphological and fitness attributes which better discriminate the players from the two teams. A total of 116 male basketball players of an elite basketball academy were divided into primary (team A) and secondary (team B) teams in two age groups (U-14 and U-16). All the players were evaluated during two consecutive seasons and data related to players’ practice experience, maturational, morphological and fitness attributes were collected at the beginning of the competition period. The results of the study suggest that: (i) in both age categories, team A players were older, more mature, bigger in size and had greater fitness profiles than team B players; (ii) stature and abdominal resistance were identified as discriminant attributes for youth basketball player performance; (iii) aerobic capacity for U-14 and agility for U-16 were identified as specific discriminant attributes for performance in youth basketball. Coaches are recommended to avoid premature talent identification and provide players with opportunities to progress through the talent pathway, at least until U-16 age category.

Background: Growth can make young athletes more vulnerable to sports injuries. Increased knowledge about injury profile and its predictors is an important part of an overall risk management strategy but few studies have produced information. Methods: Information about injury profile and sports participation (SP) level was obtained by LESADO and RAPIL II questionnaires. They were distributed to 651 participants aged between 10 and 18 years attending four schools. Maturity measures were evaluated through maturity offset (MO) and Tanner-Whitehouse III method. Bivariate analysis was used to identify the set of candidate predictors for multinomial logistic regression analysis that was used to determine significant predictors of injury type and body area injury location. Results: Regarding injury type predictors recreative boys had more chances of having a sprain or a fracture than a strain. Also, recreative and scholar girls had more chances of having a sprain than a strain. As MO decreased, the chances of girls having a strain or a fracture when compared to sprains were higher. For body area location boys with 10–11 years were more likely to have upper limbs injuries than boys of other ages. This was also confirmed by MO. Spine and trunk injuries were more likely to occur in federate and no sports participation girls. Conclusions: Injury type and body area injury location differed significantly by SP level, age group and MO.

Background: Investigations have reported differences amongst player position groups in elite team-Handball (HB) players. Nevertheless, studies with normative physical fitness data of the HB playing positions at more than two different levels of male HB players have not been reported yet. Objectives: This study aimed: 1) to describe and compare the physical fitness (PF) attributes of male HB players in different playing positions, and 2) to determine which combination of PF measures best discriminate the performance level groups in each one of the individual HB playing position groups. Materials and Methods: One hundred and sixty-one male HB players participated in this study. The participants were divided into five playing position groups: 1) Goalkeeper (GK, n = 24), 2) Wing (W, n = 48), 3) Back left/right (BLR, n = 38), 4) Back center (BC, n = 29), 5) Pivot (Pi, n = 22), complementarily, performance level was recorded for each participant according to the national HB association, i.e. 1) Top Elite, 2) Moderate Elite, 3) Sub-Elite or, 4) Moderately Trained. Stature and body mass measures were taken from each HB player, and six fitness tests were performed (30 -m sprint, handgrip, vertical jumps-SJ and CMJ, sit-ups, and Yo-Yo IE2). Results: Significant differences were observed between HB playing position groups in body size, speed, and lower limb power and handgrip strength. Nevertheless, 1) the performance in Yo-Yo IE2 was the best measure to discriminate the performance level groups when considering the HB goalkeeper group, HB center back group, and HB pivot group; 2) the average leg power (in squat jump) and the number of executions in sit up test successfully discriminated HB wing performance level groups; and, 3) Stature, countermovement jump height and the position in the Yo-Yo IE2, successfully discriminated HB left/right back performance level groups. Conclusions: It can be concluded that HB players profile, 1) differs according to HB playing position group, and, 2) for the same playing position group, it differs according to HB performance level. This study also demonstrated the influence of aerobic capacity for HB excellence, and according to playing positions. Keywords: Team Handball; Body Size; Fitness; Performance Level; Role