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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/124253
Machine Learning aplicado a las cuotas en las apuestas deportivas
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(spa) En este trabajo, se implementarán diferentes técnicas de Aprendizaje automático (Machine Learning) y se aplicarán en las apuestas deportivas. En concreto, el caso que se va a estudiar, consiste en predecir el resultado final de diferentes partidos de fútbol de la liga Italiana. Para ello, se contará con las cuotas de 7 casas de apuestas diferentes para las 5 últimas temporadas.
Entre los métodos usados, se encuentra el de KNN, SVM, QDA y Árboles de decisión entre otros. El objetivo principal, consistirá, en determinar que combinación de clasificador y casa de apuestas, produce un beneficio más grande. Para ello, se realizará un estudio de validación cruzada y se ajustarán los parámetros de cada clasificador, para obtener el mejor resultado.
(eng) In this work, different techniques of Machine Learning will be implemented and applied in sports betting. In particular, the case that will be studied, is to predict the final result of different football matches in the Italian league. To do this, we will have the odds of 7 different betting houses for the last 5 seasons. Among the methods used, is that of KNN, SVM, QDA and Decision Trees among others. The main objective, will consist, in determining which combination of classifier and betting house, produces a bigger benefit. For this, a cross-validation study will be carried out and the parameters of each classifier will be adjusted to obtain the best result.
(eng) In this work, different techniques of Machine Learning will be implemented and applied in sports betting. In particular, the case that will be studied, is to predict the final result of different football matches in the Italian league. To do this, we will have the odds of 7 different betting houses for the last 5 seasons. Among the methods used, is that of KNN, SVM, QDA and Decision Trees among others. The main objective, will consist, in determining which combination of classifier and betting house, produces a bigger benefit. For this, a cross-validation study will be carried out and the parameters of each classifier will be adjusted to obtain the best result.
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Treballs Finals de Grau en Estadística UB-UPC, Facultat d'Economia i Empresa (UB) i Facultat de Matemàtiques i Estadística (UPC), Curs: 2017-2018, Tutor: Josep Anton Sànchez Espigares
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BUSTILLO RODRÍGUEZ, Pablo. Machine Learning aplicado a las cuotas en las apuestas deportivas. [consulted: 17 of October of 2026]. Available at: https://hdl.handle.net/2445/124253