The Developmental Model of Sports Participation proposes two pathways towards expertise in sports between 6 and 12 years of age: early specialization and early diversification. This study investigated the effect of sampling various sports and of spending many or few hours in sports on fitness and gross motor coordination. Altogether, 735 boys in three age groups (6–8, 8–10, and 10–12 years) were profiled using a fitness test battery. A computerized physical activity questionnaire was used to obtain data on sports participation. In the eldest group, (M)ANCOVA showed a positive effect of sampling various sports on strength, speed, endurance, and gross motor coordination (P < 0.05). A positive effect of many hours per week spent in sports was apparent in every age group. These data suggest an acute positive effect of many hours in sports and a latent positive effect of early sampling on fitness and gross motor coordination. Multiple comparisons revealed that boys aged 10–12 years, who spent many hours in various sports, performed better on standing broad jump (P < 0.05) and gross motor coordination (P < 0.05) than boys specializing in a single sport. Therefore, our results highlight the importance of spending many hours in sports and sampling various sports in the development of fitness and gross motor coordination.

Objective. The purpose of this study was to investigate differences in gross motor coordination in healthy-weight, overweight, and obese children of different ages. Methods. Using a cross-sectional design, data were collected in 954 Flemish primary school children (500 girls, 454 boys) stratified in consecutive age groups (5–7 years, 8–9 years, 10–12 years). Weight status (healthy-weight, overweight, obese) was defined according to the International Obesity Task Force body mass index (BMI) cut-off points for children. Gross motor coordination was assessed by means of the Körperkoordinationstest für Kinder (KTK). Results. Childhood overweight and particularly obesity were found to result in poorer KTK performances (p < 0.001), with the most apparent effect of BMI on items requiring physical properties next to dynamic body coordination. Expressed as an age-related Motor Quotient (MQ), overall KTK performance was featured by a BMI × AGE interaction (p < 0.01). Healthy-weight children displayed similar MQs across age groups (p = 0.999). Overweight and obese children in the 10–12-year-old group showed significantly poorer motor coordination performance compared with the corresponding 5–7-year-old group (p < 0.01). Less than 20% of the healthy-weight participants was identified as being motor impaired, while that proportion increased to 43.3% and up to 70.8% in children with overweight and obesity, respectively. Conclusion. Results indicate that BMI-related differences in gross motor coordination were more pronounced as children belonged to an older age group. Although this outcome needs to be confirmed in future longitudinal research, it emphasizes the need of an early focus on motor skill improvement to encourage overweight and obese children to be physically active.

The aim of the present study was to evaluate the Flemish Sports Compass (FSC), a non‐sport‐specific generic testing battery. It was hypothesised that a set of 22 tests would have sufficient discriminant power to allocate athletes to their own sport based on a unique combination of test scores. First, discriminant analyses were applied to the 22 tests of anthropometry, physical fitness and motor coordination in 141 boys under age 18 (16.1 ± 0.8 years) and post age at peak height velocity (maturity offset = 2.674 ± 0.926) from Flemish Top Sport Academies for badminton, basketball, gymnastics, handball, judo, soccer, table tennis, triathlon and volleyball. Second, nine sequential discriminant analyses were used to assess the ability of a set of relevant performance characteristics classifying participants and non‐participants for the respective sports. Discriminant analyses resulted in a 96.4% correct classification of all participants for the nine different sports. When focusing on relevant performance characteristics, 80.1% to 97.2% of the total test sample was classified correctly within their respective disciplines. The discriminating characteristics were briefly the following: flexibility in gymnastics, explosive lower‐limb strength in badminton and volleyball, speed and agility in badminton, judo, soccer and volleyball, upper‐body strength in badminton, basketball and gymnastics, cardiorespiratory endurance in triathletes, dribbling skills in handball, basketball and soccer and overhead‐throwing skills in badminton and volleyball. The generic talent characteristics of the FSC enable the distinction of adolescent boys according to their particular sport. Implications for talent programmes are discussed.

It was hypothesized that differences in anthropometry, physical performance, and motor coordination would be found between Belgian elite and sub-elite level female volleyball players using a retrospective analysis of test results gathered over a 5-year period. The test sample in this study consisted of 21 young female volleyball players (15.3 ± 1.5 years) who were selected to train at the Flemish Top Sports Academy for Volleyball in 2008. All players (elite, n = 13; sub-elite, n = 8) were included in the same talent development program, and the elite-level athletes were of a high to very high performance levels according to European competition level in 2013. Five multivariate analyses of variance were used. There was no significant effect of playing level on measures of anthropometry (F = 0.455, p = 0.718, (Equation is included in full-text article.)= 0.07), flexibility (F = 1.861, p = 0.188, (Equation is included in full-text article.)= 0.19), strength (F = 1.218, p = 0.355, (Equation is included in full-text article.)= 0.32); and speed and agility (F = 1.176, p = 0.350, (Equation is included in full-text article.)= 0.18). Multivariate analyses of variance revealed significant multivariate effects between playing levels for motor coordination (F = 3.470, p = 0.036, (Equation is included in full-text article.)= 0.59). A Mann-Whitney U test and a sequential discriminant analysis confirmed these results. Previous research revealed that stature and jump height are prerequisites for talent identification in female volleyball. In addition, the results show that motor coordination is an important factor in determining inclusion into the elite level in female volleyball.