Literature DB >> 27991485

Construct validity of tests that measure kick performance for young soccer players based on cluster analysis: exploring the relationship between coaches rating and actual measures.

Luiz H Palucci Vieira1,2, Vitor L de Andrade2, Rodrigo L Aquino2,3,4, Renato Moraes1,2, Fabio A Barbieri5, Sérgio A Cunha6, Bruno L Bedo2, Paulo R Santiago7,2.   

Abstract

BACKGROUND: The main aim of this study was to verify the relationship between the classification of coaches and actual performance in field tests that measure the kicking performance in young soccer players, using the K-means clustering technique.
METHODS: Twenty-three U-14 players performed 8 tests to measure their kicking performance. Four experienced coaches provided a rating for each player as follows: 1: poor; 2: below average; 3: average; 4: very good; 5: excellent as related to three parameters (i.e. accuracy, power and ability to put spin on the ball).
RESULTS: The scores interval established from k-means cluster metric was useful to originating five groups of performance level, since ANOVA revealed significant differences between clusters generated (P<0.01). Accuracy seems to be moderately predicted by the penalty kick, free kick, kicking the ball rolling and Wall Volley Test (0.44≤r≤0.56), while the ability to put spin on the ball can be measured by the free kick and the corner kick tests (0.52≤r≤0.61). Body measurements, age and PHV did not systematically influence the performance. The Wall Volley Test seems to be a good predictor of other tests.
CONCLUSIONS: Five tests showed reasonable construct validity and can be used to predict the accuracy (penalty kick, free kick, kicking a rolling ball and Wall Volley Test) and ability to put spin on the ball (free kick and corner kick tests) when kicking in soccer. In contrast, the goal kick, kicking the ball when airborne and the vertical kick tests exhibited low power of discrimination and using them should be viewed with caution.

Mesh:

Year:  2016        PMID: 27991485     DOI: 10.23736/S0022-4707.16.06863-8

Source DB:  PubMed          Journal:  J Sports Med Phys Fitness        ISSN: 0022-4707            Impact factor:   1.637


  1 in total

1.  Research and Development of User Clustering-Based Content Similarity Algorithms in Dance-Assisted Choreography Techniques.

Authors:  Yanyan Wu; Min Liu
Journal:  Comput Intell Neurosci       Date:  2022-09-23
  1 in total

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