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We propose a statistical framework for quantifying the importance of single events that do not provide intermediate rewards but offer implicit incentives through the reward structure at the end of a multi-event contest. Applying the…

Applications · Statistics 2022-07-07 Daniel Goller , Sandro Heiniger

In this paper, we present a new model for ranking sports teams. Our model uses all scoring data from all games to produce a functional rating by the method of least squares. The functional rating can be interpreted as a teams average point…

Applications · Statistics 2019-08-05 Bradley Lowery , Abigail Slater , Kaison Thies

We study the game of go from a complex network perspective. We construct a directed network using a suitable definition of tactical moves including local patterns, and study this network for different datasets of professional tournaments…

Computer Science and Game Theory · Computer Science 2012-04-20 Bertrand Georgeot , Olivier Giraud

Rankings on online platforms help their end-users find the relevant information -- people, news, media, and products -- quickly. Fair ranking tasks, which ask to rank a set of items to maximize utility subject to satisfying group-fairness…

Computers and Society · Computer Science 2023-06-22 Sruthi Gorantla , Anay Mehrotra , Amit Deshpande , Anand Louis

The COVID-19 pandemic has left its marks in the sports world, forcing the full-stop of all sports-related activities in the first half of 2020. Football leagues were suddenly stopped and each country was hesitating between a relaunch of the…

Applications · Statistics 2021-01-27 Hans Van Eetvelde , Lars Magnus Hvattum , Christophe Ley

Unlike other major professional sports, American football lacks comprehensive statistical ratings for player evaluation that are both reproducible and easily interpretable in terms of game outcomes. Existing methods for player evaluation in…

Applications · Statistics 2018-07-13 Ronald Yurko , Samuel Ventura , Maksim Horowitz

Evaluating a soccer player's performance can be challenging due to the high costs and small margins involved in recruitment decisions. Raw observational statistics further complicate an accurate individual skill assessment as they do not…

Applications · Statistics 2024-12-10 Alexandre Andorra , Maximilian Göbel

People are rated and ranked, towards algorithmic decision making in an increasing number of applications, typically based on machine learning. Research on how to incorporate fairness into such tasks has prevalently pursued the paradigm of…

Machine Learning · Computer Science 2019-02-07 Preethi Lahoti , Krishna P. Gummadi , Gerhard Weikum

This note proposes a penalty criterion for assessing correct score forecasting in a soccer match. The penalty is based on hierarchical priorities for such a forecast i.e., i) Win, Draw and Loss exact prediction and ii) normalized Euclidian…

Applications · Statistics 2018-06-06 Jean-Louis Foulley , Gilles Celeux

It is now well known that decentralised optimisation can be formulated as a potential game, and game-theoretical learning algorithms can be used to find an optimum. One of the most common learning techniques in game theory is fictitious…

Machine Learning · Statistics 2011-12-13 Michalis Smyrnakis , David S. Leslie

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.,…

Forecasting sporting events encapsulate a compelling intellectual endeavor, underscored by the substantial financial activity of an estimated $80 billion wagered in global sports betting during 2022, a trend that grows yearly. Motivated by…

In 2019, Anderson et al. proposed the concept of rankability, which refers to a dataset's inherent ability to be meaningfully ranked. In this article, we give an expository review of the linear ordering problem (LOP) and then use it to…

Optimization and Control · Mathematics 2021-04-14 Thomas R. Cameron , Sebastian Charmot , Jonad Pulaj

We show that the Brier game of prediction is mixable and find the optimal learning rate and substitution function for it. The resulting prediction algorithm is applied to predict results of football and tennis matches. The theoretical…

Machine Learning · Computer Science 2009-11-02 Vladimir Vovk , Fedor Zhdanov

Any sports competition needs a timetable, specifying when and where teams meet each other. The recent International Timetabling Competition (ITC2021) on sports timetabling showed that, although it is possible to develop general algorithms,…

The outcome of some football matches has benefited both teams at the expense of a third team because head-to-head results were used for breaking ties. Inspired by these examples, our mathematical analysis identifies all possible collusion…

Physics and Society · Physics 2025-05-20 László Csató

Recent advancements in algorithms for sequential decision-making under imperfect information have shown remarkable success in large games such as limit- and no-limit poker. These algorithms traditionally formalize the games using the…

Computer Science and Game Theory · Computer Science 2023-12-07 Vojtěch Kovařík , David Milec , Michal Šustr , Dominik Seitz , Viliam Lisý

An algorithm that outputs predictions about the state of the world will almost always be designed with the implicit or explicit goal of outputting accurate predictions (i.e., predictions that are likely to be true). In addition, the rise of…

Machine Learning · Computer Science 2025-07-08 David Kinney

The analysis of data such as graphs has been gaining increasing attention in the past years. This is justified by the numerous applications in which they appear. Several methods are present to predict graphs, but much fewer to quantify the…

Methodology · Statistics 2024-04-30 Anna Calissano , Matteo Fontana , Gianluca Zeni , Simone Vantini

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