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Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores

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Main Authors: Lianyee, Kok, Jin, Seng Thung, Jianhong, Gao
Other Authors: kokly@tarc.edu.my
Format: Article
Language:English
Published: Kementerian Pendidikan Tinggi (KPT), Malaysia 2022
Subjects:
Multivariate regression analysis
Kinematic variables
Difficulty value
Vault performance
Gymnastics
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76666
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spelling my.unimap-766662022-11-01T02:39:28Z Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores Lianyee, Kok Jin, Seng Thung Jianhong, Gao kokly@tarc.edu.my Research Division, China Institute of Sports Science, China Faculty of Kinesiology, Shanghai University of Sport, China, Research and Innovation Division, National Sports Institute of Malaysia, Malaysia Department of Sport and Exercise Science, Tunku Abdul Rahman University College, Malaysia Multivariate regression analysis Kinematic variables Difficulty value Vault performance Gymnastics Link to publisher's homepage at https://www.mohejournal.org/aboutus.asp Introduction: Vault kinematic variables have been found to be strongly correlated with vault difficulty (DV) values and judges’ scores. However, the Fédération Internationale de Gymnastique Code of Points (COP) was updated after every Olympic Games rendering previous regression models inadequate. Therefore, the objective of this study was to develop a prediction model for vault performance based on judges’ scores. Methods: Handspring vaults (n = 70) were recorded during the Men’s Artistic Gymnastic qualifying round of the 2017 China National Artistic Gymnastics Championship using a video camera placed 50 m perpendicular to the vault table. Kinematic data were coded and correlated with judges’ official competition final scores (FSs). The vault samples were used to develop a mathematical model (n = 65) and to verify the scores against the predicted model (n = 5). Partial least squares regression was established using the statistical software to calibrate and cross validate the model. Results: The goodness-of-fit of a 3-factor model was utilised (R2 cal = 90.13% and R2 val = 87.30%) and a significant and strong relationship was observed between predicted Y (FS) and reference Y (FS) in both the calibration and validation models (rcal = 0.949, rval = 0.932) with Y-calibration error (RMSEC = 0.1727) and Y-prediction error (RMSEP = 0.1990). Maximum height, 2nd-flight-time and DV were the key variables against FS. Using JSPM, 40% of new samples were within the acceptable range. Conclusion: Kinematic variables and known DV seem adequate to form a JSPM that could offer coaches an alternative scientific approach to monitor vault training. 2022-11-01T02:39:28Z 2022-11-01T02:39:28Z 2021 Article Movement, Health & Exercise (MoHE), vol.10(2), 2021, pages 121-127 2231-9409 (printed) 2289-9510 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76666 en Kementerian Pendidikan Tinggi (KPT), Malaysia
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Multivariate regression analysis
Kinematic variables
Difficulty value
Vault performance
Gymnastics
spellingShingle Multivariate regression analysis
Kinematic variables
Difficulty value
Vault performance
Gymnastics
Lianyee, Kok
Jin, Seng Thung
Jianhong, Gao
Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
description Link to publisher's homepage at https://www.mohejournal.org/aboutus.asp
author2 kokly@tarc.edu.my
author_facet kokly@tarc.edu.my
Lianyee, Kok
Jin, Seng Thung
Jianhong, Gao
format Article
author Lianyee, Kok
Jin, Seng Thung
Jianhong, Gao
author_sort Lianyee, Kok
title Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
title_short Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
title_full Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
title_fullStr Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
title_full_unstemmed Multivariate regression modeling of Chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
title_sort multivariate regression modeling of chinese artistic gymnastic handspring vaulting kinematic performance based on judges scores
publisher Kementerian Pendidikan Tinggi (KPT), Malaysia
publishDate 2022
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/76666
_version_ 1751537955958161408
score 13.222552

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