Estimating the change in soccer's home advantage during the Covid-19 pandemic using bivariate Poisson regression
In wake of the Covid-19 pandemic, 2019–2020 soccer seasons across the world were
postponed and eventually made up during the summer months of 2020. Researchers from a …
postponed and eventually made up during the summer months of 2020. Researchers from a …
Gnnrank: Learning global rankings from pairwise comparisons via directed graph neural networks
Recovering global rankings from pairwise comparisons has wide applications from time
synchronization to sports team ranking. Pairwise comparisons corresponding to matches in …
synchronization to sports team ranking. Pairwise comparisons corresponding to matches in …
Forty years of score-based soccer match outcome prediction: an experimental review
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 …
identify the top-performing methods across diverse classes of existing approaches to the …
Models and Rating Systems for Head-to-Head Competition
ME Glickman, AC Jones - Annual Review of Statistics and Its …, 2024 - annualreviews.org
One of the most important tasks in sports analytics is the development of binary response
models for head-to-head game outcomes to estimate team and player strength. We discuss …
models for head-to-head game outcomes to estimate team and player strength. We discuss …
The open international soccer database for machine learning
How well can machine learning predict the outcome of a soccer game, given the most
commonly and freely available match data? To help answer this question and to facilitate …
commonly and freely available match data? To help answer this question and to facilitate …
A framework of interpretable match results prediction in football with FIFA ratings and team formation
While forecasting football match results has long been a popular topic, a practical model for
football participants, such as coaches and players, has not been considered in great detail …
football participants, such as coaches and players, has not been considered in great detail …
Evaluating soccer match prediction models: a deep learning approach and feature optimization for gradient-boosted trees
Abstract Machine learning models have become increasingly popular for predicting the
results of soccer matches, however, the lack of publicly-available benchmark datasets has …
results of soccer matches, however, the lack of publicly-available benchmark datasets has …
[HTML][HTML] Forecasting football match results using a player rating based model
B Holmes, IG McHale - International Journal of Forecasting, 2024 - Elsevier
The paper presents a model for forecasting the results of football matches, which takes into
account the abilities of the players on each team. The advantage of this approach is that the …
account the abilities of the players on each team. The advantage of this approach is that the …
Learning from comparisons and choices
When tracking user-specific online activities, each user's preference is revealed in the form
of choices and comparisons. For example, a user's purchase history is a record of her …
of choices and comparisons. For example, a user's purchase history is a record of her …
[PDF][PDF] Deep multilayer neural network for predicting the winner of football matches
In this work, we draw attention to prediction of football (soccer) match winner. We propose
the deep multilayer neural network based on elastic net regularization that predicts the …
the deep multilayer neural network based on elastic net regularization that predicts the …