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This study proposes a statistically grounded framework for real-time win probability evaluation and player assessment in score-based team sports, based on minute-by-minute cumulative box-score data. We introduce a continuous dominance…

Applications · Statistics 2026-02-24 Yasutaka Shimizu , Atsushi Yamanobe

Cricket betting is a multi-billion dollar market. Therefore, there is a strong incentive for models that can predict the outcomes of games and beat the odds provided by bookers. The aim of this study was to investigate to what degree it is…

Machine Learning · Statistics 2015-11-19 Stylianos Kampakis , William Thomas

Spin plays a pivotal role in ball-based sports. Estimating spin becomes a key skill due to its impact on the ball's trajectory and bouncing behavior. Spin cannot be observed directly, making it inherently challenging to estimate. In table…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Thomas Gossard , Julian Krismer , Andreas Ziegler , Jonas Tebbe , Andreas Zell

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

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

Machine learning has become a common approach to predicting the outcomes of soccer matches, and the body of literature in this domain has grown substantially in the past decade and a half. This chapter discusses available datasets, the…

Machine Learning · Computer Science 2024-03-13 Rory Bunker , Calvin Yeung , Keisuke Fujii

The purpose of this research is to create a machine learning-based smart coaching approach for football that can replace manual analysis with real-time feedback for trainers. In-depth analysis of football player data by humans is…

Signal Processing · Electrical Eng. & Systems 2023-02-08 Rahman Sahinler , Omer Burak Goktas , Berkay Mumcu , Damla Sen , Feyza Kocaturk , Huseyin Uvet

Recent advances of deep learning makes it possible to identify specific events in videos with greater precision. This has great relevance in sports like tennis in order to e.g., automatically collect game statistics, or replay actions of…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Emil Hovad , Therese Hougaard-Jensen , Line Katrine Harder Clemmensen

In the domain of Sport Analytics, Global Positioning Systems devices are intensively used as they permit to retrieve players' movements. Team sports' managers and coaches are interested on the relation between players' patterns of movements…

Applications · Statistics 2018-05-08 Rodolfo Metulini

In this article, we study the dynamics of marking in football matches. To do this, we surveyed and analyzed a database containing the trajectories of players from both teams on the field of play during three professional games. We describe…

Data Analysis, Statistics and Probability · Physics 2022-11-09 A. Chacoma , M. N. Kuperman , O. V. Billoni

A new improved transfer matrix method (TMM) is presented. It is shown that the method not only overcomes the numerical instability found in the original TMM, but also greatly improves the scalability of computation. The new improved TMM has…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Huiqiong Yin , Ruibao Tao

In table tennis, the rotation (spin) of the ball plays a crucial role. A table tennis match will feature a variety of strokes. Each generates different amounts and types of spin. To develop a robot that can compete with a human player, the…

Computer Vision and Pattern Recognition · Computer Science 2020-11-09 Jonas Tebbe , Lukas Klamt , Yapeng Gao , Andreas Zell

Player modeling is an important concept that has gained much attention in game research due to its utility in developing adaptive techniques to target better designs for engagement and retention. Previous work has explored modeling…

Artificial Intelligence · Computer Science 2018-04-03 Sara Bunian , Alessandro Canossa , Randy Colvin , Magy Seif El-Nasr

We propose and throughly investigate a temporalized version of the popular Massey's technique for rating actors in sport competitions. The method can be described as a dynamic temporal process in which team ratings are updated at every…

Social and Information Networks · Computer Science 2017-02-03 Massimo Franceschet , Enrico Bozzo

This study presents a complete pipeline for automated tennis match analysis. Our framework integrates multiple deep learning models to detect and track players and the tennis ball in real time, while also identifying court keypoints for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Venkata Manikanta Desu , Syed Fawaz Ali

Dynamical systems that evolve continuously over time are ubiquitous throughout science and engineering. Machine learning (ML) provides data-driven approaches to model and predict the dynamics of such systems. A core issue with this approach…

Machine Learning · Computer Science 2023-11-23 Aditi S. Krishnapriyan , Alejandro F. Queiruga , N. Benjamin Erichson , Michael W. Mahoney

Despite substantial growth in wind energy technology in recent decades, aerodynamic modeling of wind turbines relies on momentum models derived in the late 19th and early 20th centuries, which are well-known to break down under flow regimes…

Fluid Dynamics · Physics 2024-01-19 Jaime Liew , Kirby S. Heck , Michael F. Howland

In the light of the need to achieve a ranking which is understood by all tennis supporters, the ATP ranking is exposed to constant complaints from players and at the same time exposes new players to be benefited with a good tournament to be…

Social and Information Networks · Computer Science 2017-12-01 Alex Aronson

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

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
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