BEDLAM2.0 is a large-scale synthetic video dataset of animated bodies in simulated clothing, designed to train and test algorithms on the task of 3D human pose and shape estimation. With more than 8 million images, it is a significant expansion of the popular BEDLAM dataset that increases pose and body shape variation, and adds shoes and strand-based hair. Most importantly, it introduces a wide range of realistic cameras and camera motions.