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Basketball games evolve continuously in space and time as players constantly interact with their teammates, the opposing team, and the ball. However, current analyses of basketball outcomes rely on discretized summaries of the game that…

应用统计 · 统计学 2017-01-11 Daniel Cervone , Alex D'Amour , Luke Bornn , Kirk Goldsberry

In team-based invasion sports such as soccer and basketball, analytics is important for teams to understand their performance and for audiences to understand matches better. The present work focuses on performing visual analytics to…

人工智能 · 计算机科学 2019-07-03 Kun Zhao , Takayuki Osogami , Tetsuro Morimura

Value functions are used in sports applications to determine the optimal action players should employ. However, most literature implicitly assumes that the player can perform the prescribed action with known and fixed probability of…

最优化与控制 · 数学 2021-10-05 Timothy C. Y. Chan , Douglas S. Fearing , Craig Fernandes , Stephanie Kovalchik

The spread in the use of tracking systems in sport has made fine-grained spatiotemporal analysis a primary focus of an emerging sports analytics industry. Recently publicized tracking data for men's professional tennis allows for the first…

统计方法学 · 统计学 2022-02-02 Stephanie A. Kovalchik , Jim Albert

Current exergaming sensors and inertial systems attached to sports equipment or the human body can provide quantitative information about the movement or impact e.g. with the ball. However, the scope of these technologies is not to…

人机交互 · 计算机科学 2018-04-27 Boris Bačić

The predictive analysis of match outcomes and player momentum in professional tennis has long been a subject of scholarly debate. In this paper, we introduce a novel approach to game prediction by combining a multi-level fuzzy evaluation…

应用统计 · 统计学 2025-04-15 Kechen Li , Jiaming Liu , Zhenyu Wu , Tianbo Ji

Tennis is so popular that coaches and players are curious about factors other than skill, such as momentum. This article will try to define and quantify momentum, providing a basis for real-time analysis of tennis matches. Based on the…

机器学习 · 计算机科学 2026-03-25 Ruixin Peng , Ziqing Li

Action recognition has attracted increasing attention from RGB input in computer vision partially due to potential applications on somatic simulation and statistics of sport such as virtual tennis game and tennis techniques and tactics…

计算机视觉与模式识别 · 计算机科学 2018-09-26 Jiaxin Cai , Xin Tang

Recent advances in immersive technology have opened new possibilities in sports training, especially for activities requiring precise motor skills, such as tennis. In this paper, we present a virtual reality (VR) tennis training system…

人机交互 · 计算机科学 2025-04-23 Ryan Najami , Rami Ghannam

This paper investigates the Tennis Momentum Model (TMM), which aims to enhance the understanding of match dynamics by integrating key factors such as efficiency, historical scoring probabilities, and real-time scoring data. The model is…

应用统计 · 统计学 2025-09-30 Jackson Graves , Daniel X. Guo , Ridge Shepherd , Alexander Young

This paper represents an analysis on the momentum of tennis match. And due to Generalization performance of it, it can be helpful in constructing a system to predict the result of sports game and analyze the performance of player based on…

机器学习 · 计算机科学 2024-04-23 Jingdi Lei , Tianqi Kang , Yuluan Cao , Shiwei Ren

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.…

机器学习 · 计算机科学 2024-06-04 Andrei Shelopugin

There is a hidden energy in tennis, which cannot be seen or touched. It is the force that controls the flow of the game and is present in all types of matches. This mysterious force is Momentum. This study introduces an evaluation model…

机器学习 · 计算机科学 2024-08-06 Chang Liu , Tongyuan Yang , Yan Zhao

In this work, the novel task of detecting and classifying table tennis strokes solely using the ball trajectory has been explored. A single camera setup positioned in the umpire's view has been employed to procure a dataset consisting of…

计算机视觉与模式识别 · 计算机科学 2023-02-21 Kaustubh Milind Kulkarni , Rohan S Jamadagni , Jeffrey Aaron Paul , Sucheth Shenoy

Technological advances have paved the way for collecting high-resolution network data in basketball, football, and other team-based sports. Such data consist of interactions among players of competing teams indexed by space and time.…

应用统计 · 统计学 2024-02-14 Nicholas Grieshop , Yong Feng , Guanyu Hu , Michael Schweinberger

Sports video analysis is a widespread research topic. Its applications are very diverse, like events detection during a match, video summary, or fine-grained movement analysis of athletes. As part of the MediaEval 2022 benchmarking…

Global Positioning Systems (GPS) are nowadays intensively used in Sport Science as they permit to capture the space-time trajectories of players, with the aim to infer useful information to coaches in addition to traditional statistics. In…

应用统计 · 统计学 2017-07-05 Rodolfo Metulini , Marica Manisera , Paola Zuccolotto

Tennis is one of the most widely followed sports, generating extensive broadcast footage with strong potential for professional analysis, automated coaching, and real-time commentary. However, automatic tennis understanding remains…

计算机视觉与模式识别 · 计算机科学 2026-03-18 Zhaoyu Liu , Xi Weng , Lianyu Hu , Zhe Hou , Kan Jiang , Jin Song Dong , Yang Liu

This paper presents CourtMotion, a spatiotemporal modeling framework for analyzing and predicting game events and plays as they develop in professional basketball. Anticipating basketball events requires understanding both physical motion…

计算机视觉与模式识别 · 计算机科学 2025-12-10 Omer Sela , Michael Chertok , Lior Wolf

Automated tennis stroke analysis has advanced significantly with the integration of biomechanical motion cues alongside deep learning techniques, enhancing stroke classification accuracy and player performance evaluation. Despite these…

计算机视觉与模式识别 · 计算机科学 2025-10-07 Arushi Dashore , Aryan Anumala , Emily Hui , Olivia Yang
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