Home team advantage in the English Premier League

The home team advantage in association football is a well known phenomenon. The aim of this paper is to offer a different view on the home team advantage. Usually, in association football, every two teams—team A and team B—play each other twice in a season. Once as a home team and once as a visiting, or away team. This gives us two results between teams A and B which are combined together to evaluate whether team A, against its opponent B, recorded a result at its home ground—in the comparison to the away ground—that is better, even, or worse. This leads to a random variable with three possible outcomes, i.e. with trinomial distribution. The combination and comparison of home and away results of the same two teams is the key to eliminate problems with different squad strengths of teams in a league. The bayesian approach is used to determine point and interval estimates of unknown parameters of the source trinomial distribution, i.e. the probability that the result at home will be better, even, or worse. Moreover, it is possible to test a hypothesis that the home team advantage for a selected team is statistically significant.

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Determining the level of ability of football teams by dynamic ratings based on the relative discrepancies in scores between adversaries

Journal of Quantitative Analysis in Sports ◽

10.1515/jqas-2012-0036 ◽

2013 ◽

Vol 9 (1) ◽

pp. 37-50 ◽

Cited By ~ 18

Author(s):

Anthony Costa Constantinou ◽

Norman Elliott Fenton

Keyword(s):

Simple Technique ◽

Simple Approach ◽

Profit Margin ◽

Rating System ◽

Association Football ◽

Premier League ◽

Football Betting ◽

English Premier League ◽

Academic Study

AbstractA rating system provides relative measures of superiority between adversaries. We propose a novel and simple approach, which we call pi-rating, for dynamically rating Association Football teams solely on the basis of the relative discrepancies in scores through relevant match instances. The pi-rating system is applicable to any other sport where the score is considered as a good indicator for prediction purposes, as well as determining the relative performances between adversaries. In an attempt to examine how well the ratings capture a team’s performance, we have a) assessed them against two recently proposed football ELO rating variants and b) used them as the basis of a football betting strategy against published market odds. The results show that the pi-ratings outperform considerably the widely accepted ELO ratings and, perhaps more importantly, demonstrate profitability over a period of five English Premier League seasons (2007/2008–2011/2012), even allowing for the bookmakers’ built-in profit margin. This is the first academic study to demonstrate profitability against market odds using such a relatively simple technique, and the resulting pi-ratings can be incorporated as parameters into other more sophisticated models in an attempt to further enhance forecasting capability.

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Fans’ Perceptions towards Video Assistant Referee (VAR) in the English Premier League

Journal of Risk and Financial Management ◽

10.3390/jrfm14120573 ◽

2021 ◽

Vol 14 (12) ◽

pp. 573

Author(s):

Tommy Hamsund ◽

Nicolas Scelles

Keyword(s):

Real Time ◽

Online Survey ◽

Age Groups ◽

Association Football ◽

Premier League ◽

Younger Age ◽

Potential Benefits ◽

English Premier League ◽

Made In

The video assistant referee (VAR) in association football was developed to help on-field referees judge potentially game-changing decisions correctly by reviewing video evidence in real time. VAR was implemented by the English Premier League (EPL) ahead of the 2019/20 season. Despite its potential benefits, VAR also presents the risk of not being well perceived by fans. This article aims to investigate fans’ perceptions towards VAR in the EPL. Total of 1350 EPL fans from different age groups above 18 years old completed an online survey on their opinion of VAR and changes they felt would make VAR better. The majority of fans were happy for VAR to continue being used in the EPL, but expressed that changes need to be made in terms of how VAR is being used by on-field referees and to assess certain situations. All age groups were generally positive towards the idea of using technology in the EPL to support referee decisions and provide more information to in-stadium fans, but younger age groups showed significantly more positive perceptions than their older counterparts. Implications include advice for the EPL to make changes according to fans’ opinions and to develop frameworks for making changes with fans as stakeholders in mind.

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How a Bayesian Might Estimate the Distribution of Cronbach’s Alpha From Ordinal-Dynamic Scaled Data

Methodology ◽

10.1027/1614-2241/a000008 ◽

2010 ◽

Vol 6 (2) ◽

pp. 71-82 ◽

Cited By ~ 4

Author(s):

Byron J. Gajewski ◽

Diane K. Boyle ◽

Sarah Thompson

Keyword(s):

Confidence Intervals ◽

Bayesian Approach ◽

Mean Squared Error ◽

Cronbach’S Alpha ◽

Interval Estimates ◽

Response Options ◽

Practical Advice ◽

Cronbach's Alpha ◽

Squared Error ◽

The Bayesian Approach

We demonstrate the utility of a Bayesian-based approach for calculating intervals of Cronbach’s alpha from a psychological instrument having ordinal responses with a dynamic scale. A small number of response options on an instrument will cause traditional-based interval estimates to be biased. Ordinal-based solutions are problematic because there is no clear mechanism for handling the dynamic scale. One way to remedy the bias is to adjust with a Bayesian approach. The Bayesian approach adjusts the bias and allows theoretically simple calculations of Cronbach’s alpha and intervals. We demonstrate the calculations of the Bayesian approach while at the same time offer a comparison to more traditional-based methods using both credible (or confidence) intervals and mean squared error. Practical advice is offered.

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Entrance Fees and a Bayesian Approach to the St. Petersburg Paradox

10.20944/preprints201702.0064.v1 ◽

2017 ◽

Author(s):

Diego Marcondes ◽

Cláudia Peixoto ◽

Kdson Souza ◽

Sergio Wechsler

Keyword(s):

Bayesian Approach ◽

Random Variable ◽

Natural Generalization ◽

Sufficient Condition ◽

Necessary And Sufficient Condition ◽

Fair Coin ◽

Expected Gain ◽

Necessary And Sufficient ◽

Petersburg Paradox ◽

The Bayesian Approach

In his best-selling book An Introduction to Probability Theory and its Applications, W. Feller established a way of ending the St. Petersburg Paradox by the introduction of an entrance fee, and provided it for the case in which the game is played with a fair coin. A natural generalization of his method is to establish the entrance fee for the case in which the probability of head is θ (0 < θ < 1/2). The deduction of those fees is the main result of Section 2. We then propose a Bayesian approach to the problem. When the probability of head is θ (1/2 < θ < 1) the expected gain of the St. Petersburg Game is finite, therefore there is no paradox. However, if one takes θ as a random variable assuming values in (1/2,1) the paradox may hold, what is counter-intuitive. On Section 3 we determine a necessary and sufficient condition for the absence of paradox on the Bayesian approach and on Section 4 we establish the entrance fee for the case in which θ is uniformly distributed in (1/2,1), for in this case there is paradox.

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A Bayesian approach to Mendelian randomization with multiple pleiotropic variants

Biostatistics ◽

10.1093/biostatistics/kxy027 ◽

2018 ◽

Vol 21 (1) ◽

pp. 86-101 ◽

Cited By ~ 11

Author(s):

Carlo Berzuini ◽

Hui Guo ◽

Stephen Burgess ◽

Luisa Bernardinelli

Keyword(s):

Bayesian Approach ◽

Simulation Experiment ◽

Mendelian Randomization ◽

Causal Effect ◽

External Information ◽

Multiple Sources ◽

Unknown Parameters ◽

Interval Estimates ◽

Basic Model ◽

Shrinkage Prior

Summary We propose a Bayesian approach to Mendelian randomization (MR), where instruments are allowed to exert pleiotropic (i.e. not mediated by the exposure) effects on the outcome. By having these effects represented in the model by unknown parameters, and by imposing a shrinkage prior distribution that assumes an unspecified subset of the effects to be zero, we obtain a proper posterior distribution for the causal effect of interest. This posterior can be sampled via Markov chain Monte Carlo methods of inference to obtain point and interval estimates. The model priors require a minimal input from the user. We explore the performance of our method by means of a simulation experiment. Our results show that the method is reasonably robust to the presence of directional pleiotropy and moderate correlation between the instruments. One section of the article elaborates the model to deal with two exposures, and illustrates the possibility of using MR to estimate direct and indirect effects in this situation. A main objective of the article is to create a basis for developments in MR that exploit the potential offered by a Bayesian approach to the problem, in relation with the possibility of incorporating external information in the prior, handling multiple sources of uncertainty, and flexibly elaborating the basic model.

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