Exploiting sports-betting market using machine learning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00326348" target="_blank" >RIV/68407700:21230/19:00326348 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1016/j.ijforecast.2019.01.001" target="_blank" >https://doi.org/10.1016/j.ijforecast.2019.01.001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijforecast.2019.01.001" target="_blank" >10.1016/j.ijforecast.2019.01.001</a>

Result language
angličtina
Original language name
Exploiting sports-betting market using machine learning
Original language description
We introduce a forecasting system designed to profit from sports-betting market using machine learning. We contribute three main novel ingredients. First, previous attempts to learn models for match-outcome prediction maximized the model's predictive accuracy as the single criterion. Unlike these approaches, we also reduce the model's correlation with the bookmaker's predictions available through the published odds. We show that such an optimized model allows for better profit generation, and the approach is thus a way to `exploit' the bookmaker. The second novelty is in the application of convolutional neural networks for match outcome prediction. The convolution layer enables to leverage a vast number of player-related statistics on its input. Thirdly, we adopt elements of the modern portfolio theory to design a strategy for bet distribution according to the odds and model predictions, trading off profit expectation and variance optimally. These three ingredients combine towards a betting method yielding positive cumulative profits in experiments with NBA data from seasons 2007--2014 systematically, as opposed to alternative methods tested.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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