Advanced low-cost highly accurate sensing technology has transformed gestural interfaces making the recognition of qualitative and expressive content in musical gestures more vital than ever before. Seeking insight into designing rich interactions that support creative, flexible, high bandwidth control and communication, we chose ensemble conducting as a potentially deeply informative paradigm. We performed an exploratory analysis of qualitative aspects of conducting gestures that reveals an important role for the intra-beat variance of time derivatives of the position of the right hand and wrist. In our simplified conducting trials, these correlate well with expressive qualities of the beat at a fundamental level. We analyzed the sostenuto and staccato articulation styles of a focused conducting experiment. The articulation styles were conducted in 4/4 beat pattern at two tempos, one beat per second (60 BPM) and two beats per second (120 BPM). From these beat patterns, we extracted primitive movement features, which were analyzed using Naive Bayes classification. Our results demonstrate that our approach effectively captures unique characteristics of each articulation style tied to subtle changes within each beat.