Authors: Adrià Arbués-Sangüesa, Adrián Martín, Javier Fernández, Coloma Ballester, Gloria Haro
Publication: International Conference on Image Processing (ICIP)
Publication year: 2020
Although orientation has proven to be a key skill of soccer players in order to succeed in a broad spectrum of plays, body orientation is a yet-little-explored area in sports analytics’ research. Player orientation can be defined as the projection (2D) of the normal vector placed in the center of the upper-torso of players (3D). This research presents a novel technique to obtain player orientation from monocular video recordings by mapping pose parts (shoulders and hips) in a 2D field, and merging the obtained estimation with contextual information (ball position). Results have been validated with players-held EPTS devices, obtaining a median error of 27 degrees/player. Besides, a feasibility study is also presented, aiming to estimate the most feasible pass at any given time, based on a geometric solution on top of body-orientation. Once analyzed more than 6000 pass events, results show that, by including orientation as a feasibility measure, a robust computational model can be built, reaching more than 0.7 Top-3 accuracy. These models could help both coaches and analysts to have a better understanding of the game and to improve the players’ decision-making process.