Stacking-based deep neural network for player scouting in football 1
This work addresses the need for more accurate player scouting in football, though it appears incremental as it builds on existing deep learning and stacking techniques.
The paper tackled the problem of identifying high-potential football players from large databases, proposing a stacking-based deep learning model that achieved significantly better results than classical statistical methods on an open-source dataset.
Datascouting is one of the most known data applications in professional sport, and specifically football. Its objective is to analyze huge database of players in order to detect high potentials that can be then individually considered by human scouts. In this paper, we propose a stacking-based deep learning model to detect high potential football players. Applied on open-source database, our model obtains significantly better results that classical statistical methods.