Loop optimization in the polyhedral model is supported by the expressiveness of affine scheduling functions to model statement iteration ordering. Discovering the best scheduling remains a grand challenge reinforced by the need to build affine functions. Automatic techniques based on solving systems of affine constraints and/or composing affine scheduling primitives are limited either by the affine modeling or by their primitive set. In this paper we propose a radically different approach to affine scheduling construction called superloop scheduling. We leverage basic-block-level instruction reordering techniques and the capacity to agglomerate statement instances into "super" loops offered by modern trace analysis tools. This approach enables deepest possible reasoning about instruction ordering and a global approach to loop optimization, e.g., where tiling and intra-tile optimization is considered along with other transformations.