Login | Register

Exploration of Throw-Ins in Soccer Using Machine Learning Algorithms

Title:

Exploration of Throw-Ins in Soccer Using Machine Learning Algorithms

Bancheri, Andreas (2022) Exploration of Throw-Ins in Soccer Using Machine Learning Algorithms. Masters thesis, Concordia University.

[thumbnail of Bancheri_MSc_S2023.pdf]
Preview
Text (application/pdf)
Bancheri_MSc_S2023.pdf - Accepted Version
Available under License Spectrum Terms of Access.
4MB

Abstract

The evolving field of sports analytics is still in the early stages of its adoption. Moreover, soccer analytics utilizing tracking data is even further limited. This research is motivated by Liverpool's integration of a department for throw-in research, assisting them in winning a league title. This research project makes use of the (generously given) German national soccer team (DFB) tracking and event data which includes all player movement during a game, and more specifically, movement before and after a throw-in.

The probability of a throw-in being completed (according to two mutually exclusive definitions) is estimated using various metrics developed using the aforementioned tracking and event data. Binary classification models are used to estimate the completion probability of a given throw-in. The results show that the model provides an encouraging framework of achieving the goal of a universal throw-in metric. Therefore, any given throw-in may be evaluated, providing a meaningful tool to soccer teams, in the footsteps of xG (expected goal) or xPass (expected pass) models.

Divisions:Concordia University > Faculty of Arts and Science > Mathematics and Statistics
Item Type:Thesis (Masters)
Authors:Bancheri, Andreas
Institution:Concordia University
Degree Name:M. Sc.
Program:Mathematics
Date:13 December 2022
Thesis Supervisor(s):Godin, Frédéric and Smith, Joshua
ID Code:991429
Deposited By: Andreas Bancheri
Deposited On:21 Jun 2023 14:47
Last Modified:21 Jun 2023 14:47
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Research related to the current document (at the CORE website)
- Research related to the current document (at the CORE website)
Back to top Back to top