Academic journal article International Journal of Sport Finance

Profiting from the English Premier League: Predictive Elicitation, the Kelly Criterion, and Black Swans

Academic journal article International Journal of Sport Finance

Profiting from the English Premier League: Predictive Elicitation, the Kelly Criterion, and Black Swans

Article excerpt

(ProQuest: ... denotes formulae omitted.)

Introduction

Football (soccer) has gained increasing popularity since its contemporary introduction in 1863 in England. Today, it is the most popular sport around the world (Dunning, Joseph, & Maguire, 1993). As a consequence, betting on football through online bookmakers is by far the biggest sport in terms of turnover (Constantinou & Fenton, 2013b; Finnigan & Nordsted 2010). Therefore, the main objective of this paper is to propose a complete football betting strategy based on a simple predictive elicitation approach- the Kelly Criterion-and atypical positive returns (referred to as "black swans").

Although most of the literature on football forecasting has focused on various scoring rules to determine the performance of different methods (Constantinou & Fenton, 2012; Constantinou & Fenton, 2013a; Spann & Skiera, 2009), it is natural to determine their forecast accuracy based on the ability to generate profits against market odds (Cain, Law, & Peel, 2000; Constantinou, Fenton, & Martin, 2013; Constantinou, Fenton, & Neil, 2012; Crowder et al., 2002; Dixon & Pope, 2004; Forrest, Goddard, & Simmons, 2005; Goddard & Asimakopoulos, 2004; Graham & Stott, 2008; Hvattum & Arntzen, 2010; Kuypers, 2000b; Rue & Salvesen, 2000). However, the latter approach depends on the model's forecasting ability relative to the market odds and a betting strategy. We propose to forecast football games outcomes using a simple predictive elicitation approach (Garthwaite, Kadane, & O'Hagan, 2005; Kadane, 1980), where the hyperparameters of a Categorical Dirichlet model are elicited using betting odds from different bookmakers. Regarding the betting strategy, we use the Kelly Criterion, which defines the optimal size of a series of bets that maximizes the wealth growth rate in the long run (Kelly, 1956), and a stopping rule based on atypical positive returns (black swans), which are defined based on historical information. Therefore the novelty of our proposal is to design a complete betting strategy that includes a simple way to forecast match outcomes, determine the percentage of money that should be invested, and includes a stopping rule that might generate profits exploiting the inefficiencies in the betting market at the beginning of the season. In addition, we develop a free graphical user interface (GUI) to apply to our proposal. This is available online at https://github. com/besmarter/UIBets. This GUI is built in MATLAB, but we created an .exe version that does not require this software.

We tested our procedure in the English Premier League for the 2013-2014, 2014- 2015, and 2015-2016 seasons, betting on bet365, one of the major online bookmakers (Štrumbelj, 2014). Our method obtained profitable outcomes: 33.54%, 22.12%, and 49.01% returns, respectively.

The English Premier League

The English Premier League is one of the most important football leagues in the world. It was founded in 1992 after the Football League First Division members decided to break away from the Football League, which was originally founded in 1888. The EPL is composed of 20 clubs. Each club plays 38 matches in a regular season that runs from August to May, totaling 380 matches. Due to being the most watched football league in the world, and its excellent available historical records, it is very attractive for testing the ability of betting strategies to generate profits against market odds. In general, the English Football League system has been considered by many researchers (Cain, Law, & Peel ,2000; Crowder et al., 2002; Dixon & Pope, 2004; Forrest, Goddard, & Simmons, 2005; Goddard & Asimakopoulos, 2004; Kuypers, 2000b). Some methods have been shown to generate positive returns (Cain, Law, & Peel, 2000; Constantinou, Fenton, & Martin, 2013; Constantinou, Fenton, & Neil, 2012; Goddard & Asimakopoulos, 2004; Rue & Salvesen, 2000). …

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