  Given a monocular video of a soccer match, this paper presents a
computational model to estimate the most feasible pass at any given time. The
method leverages offensive player's orientation (plus their location) and
opponents' spatial configuration to compute the feasibility of pass events
within players of the same team. Orientation data is gathered from body pose
estimations that are properly projected onto the 2D game field; moreover, a
geometrical solution is provided, through the definition of a feasibility
measure, to determine which players are better oriented towards each other.
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. Finally, the combination of the
orientation feasibility measure with the recently introduced Expected
Possession Value metric is studied; promising results are obtained, thus
showing that existing models can be refined by using orientation as a key
feature. These models could help both coaches and analysts to have a better
understanding of the game and to improve the players' decision-making process.
