Functional Asymmetries and Force Efficiency in Elite Junior Badminton: Dataset and Analysis Pipelines

This dataset accompanies the study titled “Functional Asymmetries and Force Efficiency in Elite Junior Badminton: A Controlled Trial Using Hop Test Metrics and Neuromuscular Adaptation Indices.” The study investigated the effects of a 4-week biofeedback-guided training intervention aimed at reducing inter-limb asymmetries and enhancing neuromuscular performance in elite junior badminton players. The uploaded materials include: Raw asymmetry and performance data, Supplementary Table S1 (functional outputs by asymmetry subgroups), Full R Markdown analysis script (.Rmd), KNIME machine learning pipeline (.knwf), Visual figures used in publication (correlation matrix, PCA biplot, ROC curve, confusion matrix), A README file detailing the dataset structure and analytical workflow. All data are anonymized and structured according to FAIR principles. The R script and KNIME pipeline enable complete replication of statistical analyses and machine learning procedures, including PCA, LASSO, linear mixed models, and Random Forest classification. This repository is intended for open access use by researchers, coaches, and sport scientists interested in neuromechanical asymmetry, reactivity, and individualized training adaptation in youth athletes.