Abstract: We propose a race path synthesis framework based on a data-driven approach that provides good controllability for synthesizing race paths with characteristics preserved for racer animations. We introduce formation field, a data structure that samples regions in formation space that contains formations of exciting and realistic race paths, generated using a set of collected race paths in a path database. By traversing the regions according to a given constraint, we generate a path in formation space that defines how to synthesize the desired race path by interpolation. Because the new race path is synthesized from existing paths with quality guaranteed, it also provides the same level of quality. As the experimental and user study results show, our framework produces good results effectively and is suitable for both real-time applications such as horse racing games and race-path-generating tools.