Strength & Conditioning

Document Type



Principal component analysis (PCA) of waveforms can provide useful information about biomechanical patterns throughout a movement. The purposes of this study were to 1) use PCA to identify interlimb asymmetries in the ground reaction force (GRF) time-series data of the left and right leg during a bi-lateral countermovement jump (CMJ) and 2) determine if asymmetries in GRF time-series were associated with CMJ performance. Eight female collegiate soccer players performed three maximal effort CMJ. PCA extracted five principal components (PC) scores, eigenvalues, and eigenvectors from the GRF data. PC2 scores differed significantly between two legs, but only PC3 scores were positively correlated with CMJ height. Future research should investigate whether identified asymmetries in GRF time-series data are associated with sport performance or injury risk.