A multilateral modelling of Youth Soccer Performance Index (YSPI)

Maliki, Ahmad Bisyri Husin Musawi; Abdullah, Mohamad Razali; Juahir, Hafizan; Abdullah, Farhana; Abdullah, Nurul Ain Shahirah; Musa, Rabiu Muazu; Mat-Rasid, Siti Musliha; Adnan, A; Kosni, Norlaila Azura; Muhamad, Wan Siti Amalina Wan; Nasir, Nur Afiqah Mohamad

doi:10.1088/1757-899x/342/1/012057

Cited by 31 publications

(26 citation statements)

References 14 publications

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“…It can be used to compress a high dimensional dataset into a lower dimensional dataset. Recent study also revealed PCA is particularly useful when data on a number of useful variables has been gathered, and it is plausible that there is some redundancy in those variables [25][26][27][28][29]. Table 1 shows the descriptive statistics of anthropometric measurement and physical fitness among 600 male participants.…”

Section: Discussionmentioning

confidence: 99%

Determining Youth Profile using Principle Component Analysis for Identifying Talent in Sports

2019

ijrte

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This study attempts to determine youth profile in sports talent identification program. Data of anthropometric and physical fitness included power, agility, speeds, flexibility, strength and endurance were obtained from 600 participants in a sports talent identification program aged 13-15 years. Data analyses were carried out using multivariate analysis of principal component analysis (PCA). PCA revealed three principal components with 71.5% total variation for this studied group. The first component consists of high factor loading in speed variables (10 meter run, 20 meter run, 40 meter run) and endurance (predicted VO₂ max). The second component was constituted by anthropometric variables (weight, height, sitting height and armspan). While third component contains flexibility variable (sit and reach). These selected variables of anthropometric and fitness are, therefore, revealed as the essential attributes those must be prioritized for a talent scouting in sports. Present results had demonstrated youth profile that capable of providing an information that could help coaches in decision making during athlete selection in sports talent identification.

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Section: Discussionmentioning

confidence: 99%

Determining Youth Profile using Principle Component Analysis for Identifying Talent in Sports

2019

ijrte

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“…Principle component analysis (PCA) is a technique commonly applied for decreasing the dimensions of multivariate problems [18]. It cuts the dimensionality of data set by clarifying the correlation amongst a huge number of variables in terms of a smaller number of principal components or PCs without dropping much data [12,[19][20][21][22][41][42][43]. The principles component PC have showed as [16]…”

Section: Principle Component Analysismentioning

confidence: 99%

“…Sodium (Na) and chloroform have a strong and moderate positive loading respectively which are 0.854 and 0.710. Bromoform is a disinfection by-product usually formed during the chlorination of water [42]. This variable described into factor loading D5 with the strong value is 0.830.…”

Section: Group 3: Heavy Metal and Organic Parametersmentioning

confidence: 99%

Spatial Assessment and the Most Significant Parameters for Drinking Water Quality Using Chemometric Technique: A Case Study at Malaysia Water Treatment Plants

Zolkipli¹,

Juahir²,

Ghazali³

et al. 2018

IJET

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The objectives of this study are to determine the most significant spatial variation of drinking water pollutant and to identify the most significant parameters in each group of physico- chemical parameters (PCPs), Inorganic parameters (IOPs), heavy metals and organic parameters (HMOPs) and pesticides parameters (PPs). The Discriminant Analysis (DA) and One- Way Analysis of variance (ANOVA) showed spatial variation on four station categories and the variance of four group parameter in water drinking quality while principle component analysis (PCA) was carried out to identify the most significant of each water quality parameters base on given group. DA and ANOVA successfully reduced the physico and inorganic pollutants concentration with significant value 98.63% and 96.90%. PCA revealed six most significant drinking water quality parameters for PCPs, nine significant parameters for IOPs, fourteen parameters on HMOPs and four significant of PPs with the p value less than 0.05 (p < 0.05). Therefore, this study proves that chemometric method is the alternative way to explain the characteristic of the drinking water quality and could reduce several parameters and sampling points in the future sampling strategy.

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“…Common practice in sports development program interpreted fitness tests through percentile based categorization [11] and development of fitness index [12][13]. Henceforth, present study would propose an analytical baseline of anthropometric and fitness profile for each birth-month quartile.…”

Section: Introductionmentioning

confidence: 98%

Pattern Recognition on Anthropometric and Fitness Components Relative Birth-month Quartiles among Malaysian Boys and Girls

Mat-Rasid*,

Abdullah,

Juahir

et al. 2019

IJRTE

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Biasness selection during talent identification program in sports may occurred due to the chronological age system applied nowadays. The aim of this study is to recognize pattern on anthropometric and fitness components relative birth-month quartiles among studied population. A total of 39372 boys (aged 7.36 ± 0.29 year) and 33723 girls aged (7.34 ± 0.29 year) were classified into four chronological birth-month groups which is first quartile (Q1 - Jan to March), second quartile (Q2-Apr to June), third quartile (Q3 - July to Sept) and fourth quartile (Q4 - Oct to Dec) involved in this study. Multiple analysis of variance (MANOVA) revealed significant difference of F(18, 111336), p < 0.0001, p < 0.05 and F (18, 95358), p-value < 0.0001, alpha=0.05 between four birth-month quartiles for boy and girl participants, respectively. Tukey (HSD) follow up test of analysis of variance revealed that studied population are significantly difference in body weight, standing height, explosive leg power, hand-eye coordination and speed for all the contrast with p-value < 0.0001, alpha=0.05. However, result found no significant different for flexibility within all the contrast for boys and girls. Present study also revelaed a stronger influence of RAE among boys as compared to girls. The information of evidence-based of anthropometric and fitness performance according birth-month quartile would able to reduce RAE that may cause bias and subjective decision making for talent identification in sports.

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A multilateral modelling of Youth Soccer Performance Index (YSPI)

Cited by 31 publications

References 14 publications

Determining Youth Profile using Principle Component Analysis for Identifying Talent in Sports

Determining Youth Profile using Principle Component Analysis for Identifying Talent in Sports

Spatial Assessment and the Most Significant Parameters for Drinking Water Quality Using Chemometric Technique: A Case Study at Malaysia Water Treatment Plants

Pattern Recognition on Anthropometric and Fitness Components Relative Birth-month Quartiles among Malaysian Boys and Girls

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