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Although orientation has proven to be a key skill of soccer players in orderto succeed in a broad spectrum of plays, body orientation is ayet-little-explored area in sports analytics' research. Despite being aninherently ambiguous concept, player orientation can be defined as theprojection (2D) of the normal vector placed in the center of the upper-torso ofplayers (3D). This research presents a novel technique to obtain playerorientation from monocular video recordings by mapping pose parts (shouldersand hips) in a 2D field by combining OpenPose with a super-resolution network,and merging the obtained estimation with contextual information (ballposition). Results have been validated with players-held EPTS devices,obtaining a median error of 27 degrees/player. Moreover, three novel types oforientation maps are proposed in order to make raw orientation data easy tovisualize and understand, thus allowing further analysis at team- orplayer-level.

Always Look on the Bright Side of the Field: Merging Pose and Contextual Data to Estimate Orientation of Soccer Players