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.

The goal of this article was twofold, and a 2-study approach was conducted. The first study aimed to expose the anthropometrical, physical performance, and motor coordination characteristics that influence dropout from a high-level soccer training program in players aged 8-16 years. The mixed-longitudinal sample included 388 Belgian youth soccer players who were assigned to either a "club group" or a "dropout group." In the second study, cross-sectional data of anthropometry, physical performance, and motor coordination were retrospectively explored to investigate which characteristics influence future contract status (contract vs. no contract group) and first-team playing time for 72 high-level youth soccer players (mean age = 16.2 years). Generally, club players outperformed their dropout peers for motor coordination, soccer-specific aerobic endurance, and speed. Anthropometry and estimated maturity status did not discriminate between club and dropout players. Contract players jumped further (p = 0.011) and had faster times for a 5-m sprint (p = 0.041) than no contract players. The following prediction equation explains 16.7% of the variance in future playing minutes in adolescent youth male soccer players: -2,869.3 + 14.6 × standing broad jump. Practitioners should include the evaluation of motor coordination, aerobic endurance, and speed performances to distinguish high-level soccer players further succeeding a talent development program and future dropout players, between 8 and 16 years. From the age of 16 years, measures of explosivity are supportive when selecting players into a future professional soccer career.

The present study aimed to investigate positional differences in 744 high-level soccer players, aged 8 to 18 years. Players were assigned to six age groups (U9-U19) and divided into four playing positions (goalkeeper (GK), defender (DEF), midfielder (MF) and attacker (ATT)). MANOVA and effect sizes were used to examine anthropometrical and functional characteristics between all positions in all age groups. The main findings of the study were that GKs and DEFs were the tallest and heaviest compared with MFs and ATTs in all age groups. Further, between U9-U15, no significant differences in functional characteristics were found, except for dribbling skill, which MFs performed the best. In the U17-U19 age groups, ATTs seemed to be the most explosive (with GKs), the fastest and the more agile field players. These results suggest that inherent physical capacities (i.e., speed, power, agility) might select players in or reject players from an attacking position, which is still possible from U15-U17. Apparently, players with excellent dribbling skills at younger age are more likely to be selected to play as a MF, although, one might conclude that the typical physical characteristics for different positions at senior level are not yet fully developed among young soccer players between 8 and 14 years.

Being relatively older and having an advanced biological maturation status have been associated with increased likelihood of selection in young elite soccer players. The aims of the study were to investigate the presence of a relative age effect (RAE) and the influence of birth quarter on anthropometry, biological maturity and anaerobic parameters in 374 elite Belgian youth soccer players. The sample was divided into 3 age groups, each subdivided into 4 birth quarters (BQ). Players had their APHV estimated and height, weight, SBJ, CMJ, sprint 5 and 30?m were assessed. Overall, more players were born in BQ1 (42.3%) compared with players born in BQ4 (13.7%). Further, MANCOVA revealed no differences in all parameters between the 4 BQ?s, controlled for age and APHV. These results suggest that relatively youngest players can offset the RAE if they enter puberty earlier. Furthermore, the results demonstrated possible differences between BQ1 and BQ4, suggesting that caution is necessary when estimating differences between players because of large discrepancies between statistical and practical significance. These findings also show that coaches should develop realistic expectations of the physical abilities of younger players and these expectations should be made in the context of biological characteristics rather than chronological age-based standards.

The goal of this study was to investigate differences in physical fitness and sports participation over 2 years in children with relatively high, average, and low motor competence. Physical fitness and gross motor coordination of 501 children between 6-10 years were measured at baseline and baseline+2 years. The sample compromised 2 age cohorts: 6.00-7.99 and 8.00-9.99 years. An age and sex-specific motor quotient at baseline testing was used to subdivide these children into low (MQ < P33), average (P33 ≤ MQ < P66) and high (MQ ≥ P66) motor competence groups. Measures of sports participation were obtained through a physical activity questionnaire in 278 of the same children. Repeated Measures MANCOVA and two separate ANOVAs were used to analyze differences in changes in physical fitness and measures of sports participation respectively. Children with high motor competence scored better on physical fitness tests and participated in sports more often. Since physical fitness levels between groups changed similarly over time, low motor competent children might be at risk for being less physically fit throughout their life. Furthermore, since low motor competent children participate less in sports, they have fewer opportunities of developing motor abilities and physical fitness and this may further prevent them from catching up with their peers with an average or high motor competence.