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.
30-nov-2018
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
data science
stochastic models
sports analytics
soccer analytics
Paolo Ferragina, Luca Pappalardo, Paolo Cintia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/406603
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