This work extends Bilinear Discriminant Component Analysis to the case of oscillatory activity with allowed phase‐variability across trials. The proposed method learns a spatial profile together with a multitaper basis which can integrate oscillatory power in a band‐limited fashion. We demonstrate the method for predicting the handedness of a subject’s button press given multivariate EEG data. We show that our method learns multitapers sensitive to oscillatory activity in the 8–12 Hz range with spatial filters selective for lateralized motor cortex. This finding is consistent with the well‐known mu‐rhythm, whose power is known to modulate as a function of which hand a subject plans to move, and thus is expected to be discriminative (predictive) of the subject’s response.