Purpose: The present study examined whether groups of children with different physical fitness and fitness enjoyment profiles could be identified and, if so, whether the different groups varied from one another in terms of organized sports participation. Method: Five hundred and fifty-eight 8-11-year-olds (56.99% boys) participated in this cross-sectional study. Physical fitness and fitness enjoyment were assessed with seven items from a standardized test battery and a pictorial scale containing pictures referring to the enjoyment in those seven physical fitness tests, respectively. To examine whether groups with different fitness and enjoyment profiles could be identified, we conducted cluster analyses based on children's standardized physical fitness and fitness enjoyment scores. A two-way ANCOVA (sex*cluster) was conducted to investigate differences in weekly organized sports participation among each of the identified groups while controlling for age. Results: Cluster analyses revealed two groups with aligned levels of physical fitness and fitness enjoyment (i.e., relatively low-low and relatively high-high) and two groups with unaligned levels (i.e., relatively low-moderate and relatively high-moderate), respectively. Both groups with relatively high fitness scores were found to spend significantly more time in organized sports (M = 2.01 h and 2.29 h, respectively) than the two groups with relatively low fitness scores (M = 1.08 h and 0.98 h, respectively), irrespective of their enjoyment levels. Conclusion: Increasing physical fitness levels (especially among those children with suboptimal enjoyment levels) may lead to increased organized sports participation, while increased organized sports participation in its turn may lead to higher fitness levels. As such, participation in sports programs should be promoted in children of all age groups.
The aim of this study was to investigate visual behaviour of expert and non-expert ski athletes during an alpine slalom. Fourteen non-experts and five expert slalom skiers completed an alpine slalom course in an indoor ski slope while wearing a head-mounted eye tracking device. Experts completed the slalom clearly faster than non-experts, but no significant difference was found in timing and position of the turn initiation. Although both groups already looked at future obstacles approximately 0,5s before passing the upcoming pole, the higher speed of experts implied that they shifted gaze spatially earlier in the bend than non-experts. Furthermore, experts focussed more on the second next pole while non-expert slalom skiers looked more to the snow surface immediately in front of their body. No difference was found in the fixation frequency, average fixation duration, and quiet eye duration between both groups. These results suggest that experts focus on the timing of their actions while non-experts still need to pay attention to the execution of these actions. These results also might suggest that ski trainers should instruct non-experts and experts to focus on the next pole and, shift their gaze to the second next pole shortly before reaching it. Based on the current study it seems unadvisable to instruct slalom skiers to look several poles ahead during the actual slalom. However, future research should test if these results still hold on a real outdoor slope, including multiple vertical gates.
Along with the increasing popularity of taekwondo, there is a need of evidence-based talent identification (TID) and development programs based upon profiles of future elite athletes. This study first aims to investigate the differences between elite and non-elite taekwondo athletes in anthropometry, physical performance and motor coordination. The second aim is to demonstrate the applicability of z-scores in TID research. A total of 98 Taekwondo athletes between 12 and 17 years old were tested using a generic test battery consisting of four anthropometrical (Height, Weight, Fat Percentage, BMI), six physical performance (Sit & Reach, Sprint 5m, Sprint 30m, Counter Movement Jump, Squat Jump, Endurance Shuttle Run) and three motor coordination tests (Moving Sideways, Jumping Sideways, Walking Backwards). Based on the individual success at international competition level, 18 were categorised as elite athletes and 80 were considered as non-elite. T-tests (step 1) on raw test scores and MANOVAs on z-scores (step 2) were conducted to examine differences between the elite and non-elite taekwondo athletes for anthropometry, physical performance and motor coordination tests. Finally, z-scores were reconverted to raw scores to demonstrate practical significance for coaches. Overall, elite taekwondo athletes score better compared to the non-elite group. The MANOVA analysis better scores for elites on fat percentage (-0.55 versus 0.12;p = 0.006), BMI (-0.37 versus 0,08;p = 0.067) sprint speed 30m (-0.48 versus 0.11;p = 0.029), counter movement jump (0.79 versus -0.18;p = 0.000), squat jump (0.42 versus -0.11;p = 0.041), moving sideways (0.79 versus -0.18;p = 0.000) and walking backwards (0.54 versus -0.12;p = 0.006). This study confirms our knowledge on physical profiles of elite taekwondo athletes and expands our knowledge to the domain of motor coordination. This study showed how the z-score method can be used to distinguish between elite and non-elite athletes, the former being low in number by definition.