AIMC Topic: Basketball
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Learning spatio-temporal context for basketball action pose estimation with a multi-stream network.
Scientific reports
Aug 9, 2025
Accurate athlete pose estimation in basketball is crucial for game analysis, player training, and tactical decision-making. However, existing pose estimation methods struggle to effectively address common challenges in basketball, such as motion blur...
Enhancing game outcome prediction in the Chinese basketball league through a machine learning framework based on performance data.
Scientific reports
Jul 3, 2025
Basketball remains among the most globally popular sports, with its various competitions drawing substantial attention. The analysis and modeling of basketball game data have long been central topics in sports analytics. In recent years, integrating ...
The application of artificial intelligence techniques in predicting game outcomes of professional basketball league: A systematic review.
PloS one
Jun 26, 2025
BACKGROUND: Predicting basketball game outcomes is a critical area in sports science and data analysis, providing concrete benefits for optimizing coaching strategies, improving team management, and informing betting decisions.
Machine learning-based analysis of defensive strategies in basketball using player movement data.
Scientific reports
Apr 22, 2025
The analysis of basketball strategies has traditionally relied on manual observation and limited data. As tracking technology progresses, there is potential for applying Artificial Intelligence specifically to strategy, delivering insights into defen...
Early specialization in formative basketball: A machine learning analysis of shooting patterns in U14 and professional players.
Journal of sports sciences
Dec 12, 2024
Growing evidence supports that early sport specialization in children and adolescents may compromise long-term athlete development and high-performance acquisition. This study aimed to determine the presence of specialised shooting roles in formative...
Basketball robot object detection and distance measurement based on ROS and IBN-YOLOv5s algorithms.
PloS one
Nov 21, 2024
With the combination of artificial intelligence and robotics technology, more and more professional robots are entering the public eye. Basketball robot competition, as a very good target system for autonomous robot research, is very suitable for con...
Predicting Basketball Shot Outcome From Visuomotor Control Data Using Explainable Machine Learning.
Journal of sport & exercise psychology
Sep 6, 2024
Quiet eye (QE), the visual fixation on a target before initiation of a critical action, is associated with improved performance. While QE is trainable, it is unclear whether QE can directly predict performance, which has implications for training int...
Integration of machine learning XGBoost and SHAP models for NBA game outcome prediction and quantitative analysis methodology.
PloS one
Jul 23, 2024
This study investigated the application of artificial intelligence in real-time prediction of professional basketball games, identifying the variations within performance indicators that are critical in determining the outcomes of the games. Utilizin...
Basketball technique action recognition using 3D convolutional neural networks.
Scientific reports
Jun 7, 2024
This research investigates the recognition of basketball techniques actions through the implementation of three-dimensional (3D) Convolutional Neural Networks (CNNs), aiming to enhance the accurate and automated identification of various actions in b...
HoopTransformer: Advancing NBA Offensive Play Recognition with Self-Supervised Learning from Player Trajectories.
Sports medicine (Auckland, N.Z.)
May 30, 2024
BACKGROUND AND OBJECTIVE: Understanding and recognizing basketball offensive set plays, which involve intricate interactions between players, have always been regarded as challenging tasks for untrained humans, not to mention machines. In this study,...
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