Search

Purpose: The aim of this study was to investigate the relationship between youth road cycling success and becoming a professional cyclist. Specifically, the authors sought to analyze (1) the differences in the success scores in youth categories between future professional (PRO) and future nonprofessional (NON-PRO) cyclists, (2) whether relative age effect influences youth road cycling career pathways, and (3) whether youth competition success could predict a future career as a professional cyclist. Methods: The number of points gathered in the annual national ranking of 1345 Italian cyclists in the U17, U19, and U23 categories were retrospectively analyzed. Participants were divided into 2 groups: PRO (n = 43) and future NON-PRO (n = 1302), depending on whether they reached the professional level. Results: PRO outperformed NON-PRO in all the youth categories considered (ie, U17, U19, and U23). Older cyclists within the same annual age group were not overrepresented in PRO and do not have an advantage over younger cyclists within all the competition years. The number of points gathered in youth competitions provides an indication of probability of becoming professional cyclists from U17 onward with the predictive value increasing with age category. Conclusions: Handling the transition to a new age group well (especially the U19–U23 transition), and therefore having success competing against older and more experienced cyclists, is an important factor for talent identification in youth cycling.

Purpose: To evaluate the predictive value of a (non-)sport-specific test battery on the future success of young cyclists, test scores were compared with competition performances 2–3 years later. Methods: Three motor coordination, 5 physical performance, and 2 cycling-specific measurements were collected in 111 U15 (13.0–14.9 y) and 67 U17 (15.0–16.9 y) male road cyclists. In addition, maturity status, relative age, and competition history were assessed. National and provincial competition results 2–3 years later, in the U17year2 and U19year2 categories, were submitted to 2 separate 4-stage hierarchical regressions. Results: The results of the model of the U15 group revealed that maturity, relative age, competition history, motor coordination, physical performance, and cycling-specific performance accounted for 22.6% of the variance in competitive success. For the U15 category, only maturity and motor coordination were significant predictors of competitive success in the U17year2 category. Maturity and motor coordination each uniquely explained ±5% of the variance. However, for the U17 group—neither motor coordination, physical performance, nor cycling-specific performance could predict competitive success in the U19year2 category. Conclusions: The current study underlines the importance of general motor coordination as a building block necessary for optimal development in youth cycling. However, considering the lack of predictive value from the U17 category onward, other features may determine further development of youth athletes. Nevertheless, it is questioned why athletes need to possess a minimum level of all physical, motor coordination, and cycling-specific characteristics to experience success and enjoyment in their sport.

In sports, outperforming your peers at young age does not guarantee a professional sports career as an adult. To gain more insight in how performance in youth cycling competitions can be an indicat...

The aim of the study was to identify benchmarks for anthropometric, physical performance, motor coordination, and psychological characteristics by comparing youth badminton players of different levels through the use of a multifactorial test battery. Sixty-one male participants aged 12-18 years were divided into three groups: elite (N = 10), sub-elite (N = 24), and novice (N = 27). Standard test batteries for anthropometry (including measures to estimate biological maturity), physical performance, and motor coordination were applied, as well as the modified PCDEQ2 questionnaire for psychological characteristics of youth athletes (Hill, 2016). Multivariate analyses of covariance (MANCOVAs) with age and biological maturity as covariates were used to investigate differences between skill levels. A discriminant analysis was used to reveal to what extent participants could be correctly assigned to their skill group. Significant differences were found in physical performance (explosive power, flexibility, speed, and endurance), BMI and motor coordination. In the psychological domain, perfectionism was found to be significantly different and elites scored highest. The discriminant analysis showed that 100% of the participants were correctly classified and 80.0% were correctly cross validated. These results significantly add to the previously limited youth players' reference values, and confirm the value of a generic, i.e. without sport-specific testing, multifactorial approach to talent identification in youth badminton.

This study investigated differences in generic and soccer specific motor coordination, as well as speed and agility depending on age and maturity in elite youth soccer players (U10-U15, N = 619). Measurements included body height, body weight and sitting height to estimate age at peak height velocity (APHV); three Körperkoordinationstest für Kinder subtests (i.e. jumping sideways (JS), moving sideways (MS), balancing backwards (BB)) to assess generic motor coordination; the UGent dribbling test for soccer specific motor coordination; a 5m/30m sprint and T-test for speed and agility, respectively. Age specific z-scores of the predicted APHV identified players as earlier, on time or later maturing. (M)ANOVA analyses showed significant age by maturity interaction effects for the speed and agility test cluster, revealing maturity related differences in U14 and U15 players. Next to an overall higher performance with age for all test clusters (η2 0.080-0.468), earlier maturing players outperformed their later maturing peers in 5m/30m sprinting. The opposite was seen for JS and BB. So, players' maturity status should be taken into account to adequately value performance in talent identification. Also, the focus on characteristics that appear to be minimally biased by an earlier maturational timing (i.e. motor coordination) should be increased.

Differences and similarities between table tennis and other racquet sports exist, but are not well documented in the literature, in spite of the relevance for talent identification. In this study we aimed at identifying the key characteristics of table tennis in comparison with tennis and badminton based upon a survey in coaches. A total of 177 licensed coaches from all across the world and with diverse professional backgrounds completed a survey on anthropometric measures, physical performance, and motor coordination skills. On a scale from 1 to 10, coaches indicated to what extent a talent characteristic was important for their sport. MANOVA identified key differences as well as similarities between all three racquet sports and a subsequent discriminant analysis allocated coaches correctly for table tennis, tennis, and badminton 81.01%, 55.6%, and 71.4% respectively. Our results show that table tennis and other racquet sport coaches are well aware of differences between the racquet sports and also the importance and value of testing and assortment of skill components. These findings can assist coaches in future talent orientation and transfer in racquet sports.

The aim of the present study was to identify anthropometric, physical, coordinative and ice-skating specific characteristics that discriminate young elite ice skaters from non-elite skaters and their non-skating peers. 32 skaters aged 9-12 years old (11 elites and 21 non-elites) voluntarily participated in the study. They were submitted to 5 anthropometric, 7 physical, 3 coordination and 5 ice-skating specific tests. Reference values of a representative healthy non-skating sample were taken from the Flemish Sports Compass dataset. Figure skaters appeared to be predominantly average mature (93.8%), were lighter and leaner than the reference sample, and demonstrated better physical characteristics and motor coordination. There was no difference between the elite and non-elite group regarding maturity status and anthropometric or physical parameters. Still, elite skaters scored better than non-elites on the coordination tests jumping sideways and tended to do so on the moving sideways test. Profiles of figure skaters differ clearly from a reference population, while non-sport-specific motor coordination tests allow discrimination between elite and non-elite skaters. The relevance of these findings with respect to talent detection and identification in young ice skaters are discussed.