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Related papers: Forecasting Soccer Matches through Distributions

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We consider the task of determining a football player's ability for a given event type, for example, scoring a goal. We propose an interpretable Bayesian model which is fit using variational inference methods. We implement a Poisson model…

Applications · Statistics 2020-09-24 Gavin A. Whitaker , Ricardo Silva , Daniel Edwards , Ioannis Kosmidis

In the pursuit of natural language understanding, there has been a long standing interest in tracking state changes throughout narratives. Impressive progress has been made in modeling the state of transaction-centric dialogues and…

Computation and Language · Computer Science 2021-06-04 Ruochen Zhang , Carsten Eickhoff

For NCAA football, we provide a method for sports bettors to determine if they have a positive expected value bet based on the betting lines available to them and how they believe the game will end. The method we develop modifies…

Applications · Statistics 2022-12-19 Ryan Sides , Jane L. Harvill

The Elo rating system is a highly successful ranking algorithm for games of skill where, by construction, one team wins and the other loses. A primary limitation of the original Elo algorithm is its inability to predict information beyond a…

Methodology · Statistics 2018-02-05 J. Scott Moreland , Matthew C. Superdock

Fantasy Premier League (FPL) performance predictors tend to base their algorithms purely on historical statistical data. The main problems with this approach is that external factors such as injuries, managerial decisions and other…

Machine Learning · Computer Science 2019-12-17 Nicholas Bonello , Joeran Beel , Seamus Lawless , Jeremy Debattista

The organisers of major sports competitions use different policies with respect to constraints in the group draw. Our paper aims to rationalise these choices by analysing the trade-off between attractiveness (the number of games played by…

Optimization and Control · Mathematics 2026-04-23 László Csató

One of the most important and challenging problems in football is predicting future player performance when transferred to another club within and between different leagues. In addition to being the most valuable prediction a team makes, it…

Machine Learning · Computer Science 2022-01-28 Daniel Dinsdale , Joe Gallagher

Estimation of football players' skills is one of the key tasks in sports analytics. This paper introduces multiple extensions to a widely used model, expected possession value (EPV), to address some key challenges such as selection problem.…

Machine Learning · Computer Science 2024-06-04 Andrei Shelopugin

The expected possession value (EPV) of a soccer possession represents the likelihood of a team scoring or receiving the next goal at any time instance. By decomposing the EPV into a series of subcomponents that are estimated separately, we…

Machine Learning · Computer Science 2021-08-05 Javier Fernandez , Luke Bornn , Daniel Cervone

In football, attacking teams attempt to break through the opponent's defensive line to create scoring opportunities. This action, known as a Line Break, is a critical indicator of offensive effectiveness and tactical performance, yet…

Machine Learning · Computer Science 2025-11-04 Shoma Yagi , Jun Ichikawa , Genki Ichinose

Many popular sports involve matches between two teams or players where each team have the possibility of scoring points throughout the match. While the overall match winner and result is interesting, it conveys little information about the…

Applications · Statistics 2020-12-23 Claus Thorn Ekstrøm , Andreas Kryger Jensen

The research area of algorithms with predictions has seen recent success showing how to incorporate machine learning into algorithm design to improve performance when the predictions are correct, while retaining worst-case guarantees when…

Machine Learning · Computer Science 2022-12-06 Michael Dinitz , Sungjin Im , Thomas Lavastida , Benjamin Moseley , Sergei Vassilvitskii

Penalties are fraught and game-changing moments in soccer games that teams explicitly prepare for. Consequently, there has been substantial interest in analyzing them in order to provide advice to practitioners. From a data science…

Machine Learning · Computer Science 2025-06-02 Lotte Bransen , Tim Janssen , Jesse Davis

We propose a betting strategy based on Bayesian logistic regression modeling for the probability forecasting game in the framework of game-theoretic probability by Shafer and Vovk (2001). We prove some results concerning the strong law of…

Probability · Mathematics 2013-02-13 Masayuki Kumon , Jing Li , Akimichi Takemura , Kei Takeuchi

Soccer is a globally popular sport with a vast audience, in this paper, we consider constructing an automatic soccer game commentary model to improve the audiences' viewing experience. In general, we make the following contributions: First,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Jiayuan Rao , Haoning Wu , Chang Liu , Yanfeng Wang , Weidi Xie

The outputs of win probability models are often used to evaluate player actions. However, in some sports, such as the popular esport Counter-Strike, there exist important team-level decisions. For example, at the beginning of each round in…

Computer Science and Game Theory · Computer Science 2021-09-28 Peter Xenopoulos , Bruno Coelho , Claudio Silva

The problem of evaluating the performance of soccer players is attracting the interest of many companies and the scientific community, thanks to the availability of massive data capturing all the events generated during a match (e.g.,…

With an exploding global market and the recent introduction of online cash prize tournaments, fantasy sports contests are quickly becoming a central part of the social gaming and sports industries. For sports fans and online media…

Data Structures and Algorithms · Computer Science 2016-11-07 Christopher Musco , Maxim Sviridenko , Justin Thaler

With the increasingly detailed investigation of game play and tactics in invasive team sports such as soccer, it becomes ever more important to present causes, actions and findings in a meaningful manner. Visualizations, especially when…

Computer Vision and Pattern Recognition · Computer Science 2021-05-12 Maximilian T. Fischer , Daniel A. Keim , Manuel Stein

We propose an original model for inferring team strengths using a Markov Random Field, which can be used to generate historical estimates of the offensive and defensive strengths of a team over time. This model was designed to be applied to…

Machine Learning · Statistics 2013-05-10 John Zech , Frank Wood