This paper presents a method for analyzing expressive timing data from music performances. The goal is to uncover rules which explain a performer's systematic timing manipulations in terms of structural features of the music such as form, harmonic progression, texture, and rhythm. A multi-tiered approach is adopted, in which one first identifies a continuous tempo curve by performing non-linear regression on the durations of performed time spans at all levels in the metric hierarchy. Once the effect of tempo has been factored out, subsequent tiers of analysis examine how the performed subdivision of each metric layer (e.g., quarter note) typically deviates from an even rendering of the next lowest layer (e.g., two equal eighth notes) as a function of time. Structural features in the music are identified that contribute to a performer's tempo fluctuations and metric deviations.