State-of-the-art pronunciation tutoring (CAPT) systems are based on ASR technology. Consequently, they can provide a distinguished learning feedback which is focused on phonetic features and the positions of articulation errors. In contrast with the relative success with segmental errors, the acquisition and assessment of second language (L2) prosody is still a challenging problem. Although prosodic parameters like f0 contour or duration measures are usually displayed, the consequential evaluation components are generally missing. Considering the strong variation in speech data, functional data analysis (FDA) is a useful concept which statistically analyses interrelations between principal components (e.g., given accentuation) and their contribution to superimposed forms (e.g., resulting f0 contour). This article describes baseline processing and preliminary results of a pilot study on the intonation-based proficiency classification of German by using FDA methods. The experimental part contains the FDA-based classification results compared to a perceptual classification by German natives.