Regional anomalies in the myocardial motion of the left ventricle (LV) are important biomarkers for several cardiac diseases. Myocardial motion can be captured using a velocity-encoded magnetic resonance imaging method called tissue phase mapping (TPM). The acquired data are pre-processed and represented as regional velocities in cylindrical coordinates at three short-axis slices of the left ventricle over one cardiac cycle. We use a spatio-temporal visualization based on a radial layout where the myocardial regions are laid out in an angular pattern similar to the American Heart Association (AHA) model and the temporal dimension increases with increasing radius. To detect anomalies, we compare patient data against the myocardial motion of a cohort of healthy volunteers. For the healthy volunteer cohort, we compute nested envelopes of central regions for the time series of each region and each of the three velocity directions based on the concept of functional boxplots. A quantitative depiction of deviations from the spatio-temporal pattern of healthy heart motion allows for quick detection of regions of interests, which can then be analyzed in more detail by looking at the actual time series. We evaluated our approach in a qualitative user study with imaging and medical experts. The participants appreciated the proposed encoding and considered it a substantial improvement over the current methods.