Constraint Programming and Machine Learning for Interactive Soccer Analysis

A soccer competition consists of n teams playing against each other in a league or tournament system, according to a single or double round-robin schedule. These competitions offer an excellent opportunity to model interesting problems related to questions that soccer fans frequently ask about their favourite teams. For instance, at some stage of the competition, fans might be interested in determining whether a given team still has chances of winning the competition (i.e., finishing first in a league or being within the first k teams in a tournament to qualify to the playoff). This problem relates to the elimination problem, which is NP-complete for the actual FIFA pointing rule system (0, 1, 3), zero point to a loss, one point to a tie, and three points to a win. In this paper, we combine constraint programming with machine learning to model a general soccer scenario in a real-time application.