Multi-Hierarchical Pattern Recognition of Athlete’s Relative Performance as A Criterion for Predicting Potential Athletes

Abstract

Nonetheless, research that integrates physical fitness and goal orientation as a relative performance and uses them as a criterion predictor in the selection of potential athletes are considerably limited. Thus, this study aims to examine the relative performance quality pattern of 223 male athletes that trains under Terengganu sports development program in relation to physical fitness and psychological components. MATERIALS AND METHODS Participants:The participants of the current study comprised of 223 male adolescent athletes (17.38 ± 1.92 years). The participants were recruited from the interstate championship with various types of sports from Terengganu state in Malaysia. These athletes represented their corresponding divisions in the competition and were reflected the best at the state level for the under 21 year's age groups. These age groups were chosen because of research suggesting that participation motives and achievement behavior changes around this age. 10 The measurements were carried out in the first three months of 2015. The coaches and the managers of the athletes were informed about the purpose of the research. Writing approval was obtained, and all the players signed consent forms. Procedure of Battery Tests: Anthropometric Test: Standard anthropometric testing was conducted which constitutes of height and weight with the subjects dressed in light clothing. Height was measured with a wallmounted wooden stadiometer to the nearest 0.5 cm. Body weight was evaluated with a standardized electronic digital scale to the nearest 0.1 kg. Body mass index (BMI) was measured as body mass in kilograms ABSTRACTObjective: This study investigates the relative performance quality pattern of athletes that trains under Terengganu sports development program based on physical fitness and psychological components. Methods: Relative performance data (223×7) were obtained from various types of sport, and its main tributaries were evaluated for physical fitness and TEOSQ instrument. Multivariate methods of hierarchical agglomerative cluster analysis (HACA), discriminant analysis (DA), principal component analysis (PCA), and principal factor analysis (PFA), were used to study the relative performance variations of the most significant performance quality variables and to determine the origin of relative performance components. Results: Three clusters of performance were shaped in view of HACA. Forward and backward stepwise DA discriminates six and five performance quality variables from the first seven variables. PCA and FA were used to identify the origin of each quality performance variables based on three clustered groups. Three PCs were obtained with 67% total variation for the highperformance group (HPG) region, three PCs with 72% and 64% total variances were obtained for the moderate-performance group (MPG) and low-performance group (LPG) regions, respectively. The general performance sources for the three groups are from cardiovascular and ego orientation sources. The differences between groups are from flexibi...

The Application of Inertial Measurement Units and Wearable Sensors to Measure Selected Physiological Indicators in Archery

“…Moreover, it was indicated in the present study that mobile devices (especially smartphones) have now become an essential part of daily life and with its constantly increasing processing power, they are more and more utilized for biomedical signal processing especially for ECG, EMG as well as the movement of activity analysis 14,15 . Therefore, it is apparent that the utilization of such technology may empower coaches through the data gathered to evaluate the performance of their athletes …”

The strategy differences and movement pattern between medalist and non-medalist taekwondo youth athlete

“…In prior main data analysis, the total of missing data, data error, and outlier were checked to facilitate an analysis [11]. Distribution of normality data as well as outlier were tested using Kolmogorov-Smirnov and box-plot method [12]. The difference effect size (r) is measured by the number of mean and standard deviation as recommended by the former researcher [13].…”

Holding Bow Digital Test for Strength and Endurance Arm Muscles of Archery

“…Archery is a smooth and at the same time a rough motor sports, in which success is determined by the capacity to shoot at targets repeatedly with great precision and accuracy. It is quite evident that for an athlete to achieve victory in sports, a certain level of physical fitness and optimal motor skills are required [1]. From Previous findings, the mastery of certain physical fitness variables and motor skills such as core body strength, upper body strength, handgrip, leg strength and static balance can lead to the desired result for a particular sports performance [2].…”

“…[8]. In previous studies, we learnt that the strength and endurance of the arm muscles has a significant effect to the accuracy of archery [1,3,5]. In order to achieve a perfect score, every archer only needs to keep his movements consistent from the start to the finish.…”

“…However, there is no particular gauge / test used to measure the strength and endurance of arm muscles. Arm muscle strength could be measured by push-ups [1] but this does not provide a valid data because of the various types of push-ups and shooting movements. A tool for measuring arm muscle strength for archery sports was developed.…”