The sports domain presents a number of significant computational challenges for artificial
intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that …

We investigate the state-of-the-art in score-based soccer match outcome modelling to
identify the top-performing methods across diverse classes of existing approaches to the …

This paper evaluates the efficiency of online betting markets for European (association)
football leagues. The existing literature shows mixed empirical evidence regarding the …

The task of the 2017 Soccer Prediction Challenge was to use machine learning to predict
the outcome of future soccer matches based on a data set describing the match outcomes of …

The paper describes Dolores, a model designed to predict football match outcomes in one
country by observing football matches in multiple other countries. The model is a mixture of …

Abstract Summary statistics for football matches, such as ball possession and percentage of
completed passes, are not always satisfyingly informative about team strategies seen on the …

The global expansion of the sports betting industry has brought the prediction of outcomes of
sport events into the foreground of scientific research. In this work, soccer outcome …

Although there are many contributions in the time series clustering literature, few studies still
deal with count time series data. This paper aims to develop a fuzzy clustering procedure for …

How to build a football match prediction model and use scientific methods to solve the
prediction problem has become a key point in the application of artificial intelligence in the …

We present 10 different strength-based statistical models that we use to model soccer match
outcomes with the aim of producing a new ranking. The models are of four main types …