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Several performance metrics for quantifying the in-game performances of individual football players have been proposed in recent years. Although the majority of the on-the-ball actions during games constitutes of passes, many of the…

Applications · Statistics 2018-10-05 Lotte Bransen , Jan Van Haaren

Quantitative analysis of soccer players' passing ability focuses on descriptive statistics without considering the players' real contribution to the passing and ball possession strategy of their team. Which player is able to help the…

Artificial Intelligence · Computer Science 2016-08-12 Laszlo Gyarmati , Rade Stanojevic

Based on NFL game data we try to predict the outcome of a play in multiple different ways. An application of this is the following: by plugging in various play options one could determine the best play for a given situation in real time.…

Machine Learning · Computer Science 2016-01-05 Brendan Teich , Roman Lutz , Valentin Kassarnig

The strategic orchestration of football matchplays profoundly influences game outcomes, motivating a surge in research aimed at uncovering tactical nuances through social network analysis. In this paper, we delve into the microscopic…

Physics and Society · Physics 2024-08-16 Ming-Xia Li , Li-Gong Xu , Wei-Xing Zhou

Although the data-driven analysis of football players' performance has been developed for years, most research only focuses on the on-ball event including shots and passes, while the off-ball movement remains a little-explored area in this…

Machine Learning · Computer Science 2023-09-06 Yisheng Pei , Varuna De Silva , Mike Caine

Given a monocular video of a soccer match, this paper presents a computational model to estimate the most feasible pass at any given time. The method leverages offensive player's orientation (plus their location) and opponents' spatial…

Computer Vision and Pattern Recognition · Computer Science 2020-04-16 Adrià Arbués-Sangüesa , Adrián Martín , Javier Fernández , Coloma Ballester , Gloria Haro

Continuous-time assessments of game outcomes in sports have become increasingly common in the last decade. In American football, only discrete-time estimates of play value were possible, since the most advanced public football datasets were…

Pressing is a fundamental defensive strategy in football, characterized by applying pressure on the ball owning team to regain possession. Despite its significance, existing metrics for measuring pressing often lack precision or…

Applications · Statistics 2025-07-01 Joris Bekkers

American football is an increasingly popular sport, with a growing audience in many countries in the world. The most watched American football league in the world is the United States' National Football League (NFL), where every offensive…

Machine Learning · Statistics 2021-09-17 Gustavo Pompeu da Silva , Rafael de Andrade Moral

Over the last few decades, the player recruitment process in professional football has evolved into a multi-billion industry and has thus become of vital importance. To gain insights into the general level of their candidate reinforcements,…

Machine Learning · Statistics 2018-09-17 Bart Aalbers , Jan Van Haaren

Line-breaking passes (LBPs) are crucial tactical actions in football, allowing teams to penetrate defensive lines and access high-value spaces. In this study, we present an unsupervised, clustering-based framework for detecting and…

Machine Learning · Computer Science 2025-06-10 Oktay Karakuş , Hasan Arkadaş

In soccer, passing is the most frequent interaction between players and plays a significant role in creating scoring chances. Experts are interested in analyzing players' passing behavior to learn passing tactics, i.e., how players build up…

Human-Computer Interaction · Computer Science 2020-09-08 Xiao Xie , Jiachen Wang , Hongye Liang , Dazhen Deng , Shoubin Cheng , Hui Zhang , Wei Chen , Yingcai Wu

Football forecasting models traditionally rate teams on past match results, that is based on the number of goals scored. Goals, however, involve a high element of chance and thus past results often do not reflect the performances of the…

Applications · Statistics 2021-01-07 Edward Wheatcroft , Ewelina Sienkiewicz

In this paper we present a novel approach to optimise tactical and strategic decision making in football (soccer). We model the game of football as a multi-stage game which is made up from a Bayesian game to model the pre-match decisions…

Artificial Intelligence · Computer Science 2020-03-24 Ryan Beal , Georgios Chalkiadakis , Timothy J. Norman , Sarvapali D. Ramchurn

Technology offers new ways to measure the locations of the players and of the ball in sports. This translates to the trajectories the ball takes on the field as a result of the tactics the team applies. The challenge professionals in soccer…

Computer Vision and Pattern Recognition · Computer Science 2015-08-11 Laszlo Gyarmati , Xavier Anguera

Tackling is a fundamental defensive move in American football, with the main purpose of stopping the forward motion of the ball-carrier. However, current tackling metrics are manually recorded outcomes that are inherently flawed due to…

Applications · Statistics 2025-01-08 Quang Nguyen , Ruitong Jiang , Meg Ellingwood , Ronald Yurko

Analysis of the popular expected goals (xG) metric in soccer has determined that a (slightly) smaller number of high-quality attempts will likely yield more goals than a slew of low-quality ones. This observation has driven a change in…

Artificial Intelligence · Computer Science 2023-02-17 Maaike Van Roy , Pieter Robberechts , Wen-Chi Yang , Luc De Raedt , Jesse Davis

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

With the vast amount of data collected on football and the growth of computing abilities, many games involving decision choices can be optimized. The underlying rule is the maximization of an expected utility of outcomes and the law of…

Machine Learning · Computer Science 2021-03-15 Preston Biro , Stephen G. Walker

When facing a heavily-favored opponent, an underdog must be willing to assume greater-than-average risk. In statistical language, one would say that an underdog must be willing to adopt a strategy whose outcome has a larger-than-average…

Physics and Society · Physics 2011-11-04 Brian Skinner
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