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This study employs Bayesian methodologies to explore the influence of player or positional factors in predicting the probability of a shot resulting in a goal, measured by the expected goals (xG) metric. Utilising publicly available data…

Applications · Statistics 2025-01-14 Alexander Scholtes , Oktay Karakuş

The existing computational models used to estimate motion sickness are incapable of describing the fact that the predictability of motion patterns affects motion sickness. Therefore, the present study proposes a computational model to…

Quantitative Methods · Quantitative Biology 2021-01-18 Takahiro Wada

A discrete implementation on a lattice of the Active Walker Model is presented. After the model's validity is shown in simple simulations, more complex simulations of walkers passing consecutively a lattice from an arbitrary starting point…

Statistical Mechanics · Physics 2007-05-23 S. Schoellmann

Multi-agent trajectory generation in team sports requires models that capture both the diversity of possible plays and realistic spatial coordination between players on plays. Standard generative approaches such as Conditional Variational…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Kevin Song

We present a new approach for identifying situations and behaviours, which we call "moves", from soccer games in the 2D simulation league. Being able to identify key situations and behaviours are useful capabilities for analysing soccer…

Machine Learning · Computer Science 2018-09-13 Olivia Michael , Oliver Obst , Falk Schmidsberger , Frieder Stolzenburg

Assessing the spatial fairness of predictive models involves establishing whether they are statistically penalizing (favoring) individuals associated with certain geographical locations. Literature on this topic makes the fundamental…

Machine Learning · Computer Science 2026-05-25 Francesco Lettich , Mario A. Nascimento , Chiara Pugliese , Chiara Renso

Predicting the future performance of young runners is an important research issue in experimental sports science and performance analysis. We analyse a data set with annual seasonal best performances of male middle distance runners for a…

Applications · Statistics 2022-06-28 Mattia Stival , Mauro Bernardi , Manuela Cattelan , Petros Dellaportas

The expected goal provides a more representative measure of the team and player performance which also suit the low-scoring nature of football instead of score in modern football. The score of a match involves randomness and often may not…

Machine Learning · Computer Science 2023-02-14 Mustafa Cavus , Przemysław Biecek

Football (soccer) is a sport that is characterised by complex game play, where players perform a variety of actions, such as passes, shots, tackles, fouls, in order to score goals, and ultimately win matches. Accurately forecasting the…

Machine Learning · Computer Science 2025-11-25 Michael Horton , Patrick Lucey

This paper proposes a novel framework to assess individual player contributions in football, explicitly accounting for the cooperative nature of shot-ending offensive actions. By incorporating team interaction into player evaluation, it…

Applications · Statistics 2026-05-05 Mattia Cefis , Rodolfo Metulini , Maurizio Carpita

In-game win probability models, which provide a sports team's likelihood of winning at each point in a game based on historical observations, are becoming increasingly popular. In baseball, basketball and American football, they have become…

Machine Learning · Computer Science 2021-08-16 Pieter Robberechts , Jan Van Haaren , Jesse Davis

Football is a very result-driven industry, with goals being rarer than in most sports, so having further parameters to judge the performance of teams and individuals is key. Expected Goals (xG) allow further insight than just a scoreline.…

Machine Learning · Computer Science 2023-09-04 James H. Hewitt , Oktay Karakuş

Inspired by applications in sports where the skill of players or teams competing against each other varies over time, we propose a probabilistic model of pairwise-comparison outcomes that can capture a wide range of time dynamics. We…

Machine Learning · Statistics 2019-05-20 Lucas Maystre , Victor Kristof , Matthias Grossglauser

Evaluating the individual movements for teammates in soccer players is crucial for assessing teamwork, scouting, and fan engagement. It has been said that players in a 90-min game do not have the ball for about 87 minutes on average.…

Artificial Intelligence · Computer Science 2022-07-28 Masakiyo Teranishi , Kazushi Tsutsui , Kazuya Takeda , Keisuke Fujii

Soccer is undeniably the most popular sport world-wide and everyone from general managers and coaching staff to fans and media are interested in evaluating players' performance. Metrics applied successfully in other sports, such as the…

Applications · Statistics 2020-12-04 Konstantinos Pelechrinis , Wayne Winston

With the development of measurement technology, data on the movements of actual games in various sports can be obtained and used for planning and evaluating the tactics and strategy. Defense in team sports is generally difficult to be…

Artificial Intelligence · Computer Science 2022-05-10 Kosuke Toda , Masakiyo Teranishi , Keisuke Kushiro , Keisuke Fujii

Soccer video understanding has motivated the creation of datasets for tasks such as temporal action localization, spatiotemporal action detection (STAD), or multiobject tracking (MOT). The annotation of structured sequences of events (who…

Artificial Intelligence · Computer Science 2025-11-21 Jeremie Ochin , Raphael Chekroun , Bogdan Stanciulescu , Sotiris Manitsaris

This paper presents a novel framework for evaluating players in association football (soccer). Our method uses possession sequences, i.e. sequences of consecutive on-ball actions, for deriving estimates for player strengths. On the surface,…

Applications · Statistics 2024-08-13 Robert Bajons , Kurt Hornik

We investigate the potential occurrence of change points - commonly referred to as "momentum shifts" - in the dynamics of football matches. For that purpose, we model minute-by-minute in-game statistics of Bundesliga matches using hidden…

Applications · Statistics 2020-07-22 Marius Ötting , Roland Langrock , Antonello Maruotti

A mathematical model for behavioral changes by pair interactions (i.e. due to direct contact) of individuals is developed. Three kinds of pair interactions can be distinguished: Imitative processes, avoidance processes, and compromising…

Statistical Mechanics · Physics 2007-05-23 Dirk Helbing
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