This algorithm simulates the outcomes of an entire season of each team of a football league only relying on technical data (i.e., excluding the goals scored), by exploiting a machine learning model trained on data from past seasons. The simulation produces a team ranking which is close to the actual ranking. This result suggests that a complex systems’ view on soccer has the potential of revealing hidden patterns regarding the relation between performance and success.