Exploiting sports-betting market using machine learning

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Exploiting sports-betting market using machine learning

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Exploiting sports-betting market using machine learning

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Forecasting

ISSN

0169-2070

e-ISSN

1872-8200

Svazek periodika

35

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

14

Strana od-do

783-796

Kód UT WoS článku

000469310100030

EID výsledku v databázi Scopus

2-s2.0-85061670248