Tilting refers to losing control due to negative emotions, behaving erratically, and thereby suffering adverse consequences. The term tilt originated in poker playing communities, where it is often a consequence of so called bad beats, i.e. losing with an unlikely-to-lose poker hand. Often resulting in devastating monetary losses, tilting is ubiquitous and well known in poker, but rarely studied despite its significance. In this paper, we argue that tilting is a fertile topic for interdisciplinary research both for psychologists and computer scientists. Specifically, we propose to study the manifestation of tilting via facial emotion expressions, and motivate the development of an automatic tilt-detection system. The scientific understanding of the psychology of tilting can be increased via a computing approach, which has not been previously attempted. Automatic tilting detection will lead to a practical technology that reduces poker players' monetary losses and improves their well being through reduced tilting. We also argue that while tilting is best known as a poker phenomenon, it also exists in other contexts. Thus, the idea we suggest is a novel application of computer vision, affective computing and multimedia technologies in the real world, across many domains.