Summary The behavioral and neural processes of real-world motor learning remain largely unknown. We demonstrate the feasibility of real-world neuroscience, using wearables for naturalistic full-body motion tracking and mobile brain imaging, to study motor learning in billiards. We highlight the similarities between motor learning in-the-wild and classic toy-tasks in well-known features, such as multiple learning rates, and the relationship between task-related variability and motor learning. However, we found that real-world motor learning affects the whole body, changing motor control from head to toe. Moreover, with a data-driven approach, based on the relationship between variability and learning, we found the arm supination to be the task relevant joint angle. Our EEG recordings highlight groups of subjects with opposing dynamics of post-movement Beta rebound (PMBR), not resolved before in toy-tasks. The first group increased PMBR over learning while the second decreased. These opposite trends were previously reported in error-based learning and skill learning tasks respectively. Behaviorally, the PMBR decreasers better controlled task-relevant variability dynamically leading to lower variability and smaller errors in the learning plateau. We speculate that these PMBR dynamics emerge because subjects must combine multi-modal mechanisms of learning in new ways when faced with the complexity of the real-world.