This thesis aims to capture soccer teams behavior using a stochastic approach on a graph built on top of the Wyscout dataset, a market-leading company in data scouting for soccer. The main contributions of the thesis are twofold: first, it proposes a stochastic representation of a soccer game via a weighted graph properly derived from the Wyscout dataset. Secondly, it analyses every game through a stochastic model to detect the way teams move the ball together with the way they move onto the field and the performance that they achieve.
Capturing football-teams behavior with a stochastic model / Barbone, M Laureando Relatori Paolo Ferragina; Pappalardo, Luca; Cintia, Paolo. - (2018 Nov 30).
Capturing football-teams behavior with a stochastic model
Luca Pappalardo;Paolo Cintia
2018
Abstract
This thesis aims to capture soccer teams behavior using a stochastic approach on a graph built on top of the Wyscout dataset, a market-leading company in data scouting for soccer. The main contributions of the thesis are twofold: first, it proposes a stochastic representation of a soccer game via a weighted graph properly derived from the Wyscout dataset. Secondly, it analyses every game through a stochastic model to detect the way teams move the ball together with the way they move onto the field and the performance that they achieve.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


