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Predicting judo champions and medallists using statistical modelling

Rozilee Norjali (UGent) , Marlies Torfs, Mireille Mostaert (UGent) , Johan Pion (UGent) and Matthieu Lenoir (UGent)
(2017) ARCHIVES OF BUDO. 13. p.161-167
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Abstract
Background and Study Aim: In the past decade, several studies have convincingly demonstrated that the identification of characteristics in young children can form a solid basis to identify those subjects with the most chance to excel at the international competition level. The present study aims to predict the performance of young male judo athletes with linear and non-linear predictive statistical models. It is hypothesized that a non-sport specific test battery will allocate athletes to their best achievement level at least three years past baseline. Material and Methods: In this retrospective cross-sectional study, 22 trained male Belgian judo athletes U14 (12.675 +/- 0.910 years) were tested in 2009-2011 using a generic test battery consisting of five anthropometrical, seven physical performance and three motor coordination tests. In 2016 they were allocated to one of three groups depending on their achievement level between 2013-2015. First, Kruskal-Wallis was used to discover indicators that significantly differ across the three groups sampled by achievements. Second, linear discriminant analysis (LDA) was applied to discriminate the participants and allocate them to their respective achievement level. Results: The Kruskal-Wallis test showed significant differences for three indicators (sitting height, weight, Body Mass Index). Using all indicators, discriminant analysis correctly classified 95.5% of the participants. Only 36.4% of cross-validated grouped cases were correctly classified based on all indicators. Therefore, a sequential discriminant analysis, containing the significant tests (three indicators) was applied to improve the cross-validated model from 36.4% to 59.1%. Using all indicators makes the model stronger but using a limited number of indicators makes it easier to assign athletes to the right group. Conclusions: Generic talent characteristics (anthropometry) included in the present study allow for a successful discrimination between drop out, sub-elite and elite judo athletes. In addition to the trainer's opinion and the individual screening of judo specific performance characteristics, this generic test battery provides opportunities for predicting judo performance of young athletes.
Keywords
cross-sectional study, judo achievements, performance characteristics, talent identificatiation, YOUTH SOCCER PLAYERS, BIOLOGICAL MATURATION, TALENT IDENTIFICATION, MOTOR COORDINATION, ELITE, PERFORMANCE, FITNESS, SENIOR, SPORT, POSTURE

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Please use this url to cite or link to this publication:

Chicago
Norjali, Rozilee, Marlies Torfs, Mireille Mostaert, Johan Pion, and Matthieu Lenoir. 2017. “Predicting Judo Champions and Medallists Using Statistical Modelling.” Archives of Budo 13: 161–167.
APA
Norjali, R., Torfs, M., Mostaert, M., Pion, J., & Lenoir, M. (2017). Predicting judo champions and medallists using statistical modelling. ARCHIVES OF BUDO, 13, 161–167.
Vancouver
1.
Norjali R, Torfs M, Mostaert M, Pion J, Lenoir M. Predicting judo champions and medallists using statistical modelling. ARCHIVES OF BUDO. 2017;13:161–7.
MLA
Norjali, Rozilee et al. “Predicting Judo Champions and Medallists Using Statistical Modelling.” ARCHIVES OF BUDO 13 (2017): 161–167. Print.
@article{8550715,
  abstract     = {Background and Study Aim: In the past decade, several studies have convincingly demonstrated that the identification of characteristics in young children can form a solid basis to identify those subjects with the most chance to excel at the international competition level. The present study aims to predict the performance of young male judo athletes with linear and non-linear predictive statistical models. It is hypothesized that a non-sport specific test battery will allocate athletes to their best achievement level at least three years past baseline. 
Material and Methods: In this retrospective cross-sectional study, 22 trained male Belgian judo athletes U14 (12.675 +/- 0.910 years) were tested in 2009-2011 using a generic test battery consisting of five anthropometrical, seven physical performance and three motor coordination tests. In 2016 they were allocated to one of three groups depending on their achievement level between 2013-2015. First, Kruskal-Wallis was used to discover indicators that significantly differ across the three groups sampled by achievements. Second, linear discriminant analysis (LDA) was applied to discriminate the participants and allocate them to their respective achievement level. 
Results: The Kruskal-Wallis test showed significant differences for three indicators (sitting height, weight, Body Mass Index). Using all indicators, discriminant analysis correctly classified 95.5% of the participants. Only 36.4% of cross-validated grouped cases were correctly classified based on all indicators. Therefore, a sequential discriminant analysis, containing the significant tests (three indicators) was applied to improve the cross-validated model from 36.4% to 59.1%. Using all indicators makes the model stronger but using a limited number of indicators makes it easier to assign athletes to the right group. 
Conclusions: Generic talent characteristics (anthropometry) included in the present study allow for a successful discrimination between drop out, sub-elite and elite judo athletes. In addition to the trainer's opinion and the individual screening of judo specific performance characteristics, this generic test battery provides opportunities for predicting judo performance of young athletes.},
  author       = {Norjali, Rozilee and Torfs, Marlies and Mostaert, Mireille and Pion, Johan and Lenoir, Matthieu},
  issn         = {1643-8698},
  journal      = {ARCHIVES OF BUDO},
  keywords     = {cross-sectional study,judo achievements,performance characteristics,talent identificatiation,YOUTH SOCCER PLAYERS,BIOLOGICAL MATURATION,TALENT IDENTIFICATION,MOTOR COORDINATION,ELITE,PERFORMANCE,FITNESS,SENIOR,SPORT,POSTURE},
  language     = {eng},
  pages        = {161--167},
  title        = {Predicting judo champions and medallists using statistical modelling},
  volume       = {13},
  year         = {2017},
}

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