2020
DOI: 10.3390/ijerph17218192
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Significant Predictors of Sports Performance in Elite Men Judo Athletes Based on Multidimensional Regression Models

Abstract: Background: This research aimed to identify the most significant predictors of sports level using regression modeling. Methods: This study examined 16 judokas (aged 23 (±2.5)) from four weight categories, with four athletes in each category (66 kg, 73 kg, 81 kg and 90 kg). Each athlete was a member of the Polish National Team, an international master class (IM) or national master class (M). The tests were carried out twice (every two weeks) during the pre-competitive season in the morning, after a 10-min warm-… Show more

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Cited by 12 publications
(13 citation statements)
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“…Lower-limb muscle groups are particularly important in judo. Hence, we suggest paying particular attention to developing the strength of the muscles of the lower extremities in the training process, which is related to the health aspect of judo practitioners [ 29 ]. Certainly, more studies are needed in the field of isokinetic analysis in professional sports.…”
Section: Discussionmentioning
confidence: 99%
“…Lower-limb muscle groups are particularly important in judo. Hence, we suggest paying particular attention to developing the strength of the muscles of the lower extremities in the training process, which is related to the health aspect of judo practitioners [ 29 ]. Certainly, more studies are needed in the field of isokinetic analysis in professional sports.…”
Section: Discussionmentioning
confidence: 99%
“…Smaruj et al [ 36 ] and Kostrzewa et al [ 37 ] mention strength, correct posture, effective movements and balance as critical elements in judo. Due to the activity’s complexity, judo training can also be considered as a tool for increasing the strength of postural muscles, which should be taken into account when planning training for children.…”
Section: General Recommendationsmentioning
confidence: 99%
“…Using a ridge regularisation was motivated by the high dimensional context that may lead to unsteady multivariate linear models, excessively sensitive to an expanded space of solutions. Accordingly, ridge regularisation reduces the space of solutions while solving collinearity problems, which remains common in sports [30][31][32] . It thus prevents biased estimates through penalising estimates of correlated features 33,34 .…”
Section: Data Setmentioning
confidence: 99%