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Research#Dataset🔬 ResearchAnalyzed: Jan 10, 2026 08:39

New Table Tennis Dataset for Advanced AI Training

Published:Dec 22, 2025 12:25
1 min read
ArXiv

Analysis

This research introduces a novel dataset, Extended OpenTT Games, designed for fine-grained analysis of table tennis play. The focus on shot type and point outcome could significantly improve AI's understanding and prediction capabilities in this domain.
Reference

“Extended OpenTT Games is a table tennis dataset for fine-grained shot type and point outcome.”

PermalinkArXiv
Research#Sports AI🔬 ResearchAnalyzed: Jan 10, 2026 09:13

AI Unlocks Tennis Serve Secrets: Aerodynamic Analysis to Internal Force Reconstruction

Published:Dec 20, 2025 11:32
1 min read
ArXiv

Analysis

This research explores a fascinating application of AI and physics in sports analysis. The deterministic approach, utilizing rigid-body dynamics, could provide valuable insights for performance improvement and injury prevention in tennis.
Reference

“The research focuses on deterministic reconstruction of tennis serve mechanics.”

PermalinkArXiv
Research#Agent🔬 ResearchAnalyzed: Jan 10, 2026 09:17

AI Learns Tennis Strategy: A Deep Dive into Curriculum-Based Learning

Published:Dec 20, 2025 04:22
1 min read
ArXiv

Analysis

This ArXiv article likely presents novel research on using deep reinforcement learning for tennis strategy. The focus on curriculum-based learning and dueling Double Deep Q-Networks suggests a sophisticated approach to address the complexities of the game.
Reference

“The article's context indicates the research focuses on training AI for tennis strategy.”

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Sports Analytics#AI in Sports📝 BlogAnalyzed: Dec 29, 2025 08:24

Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159

Published:Jun 29, 2018 16:24
1 min read
Practical AI

Analysis

This article discusses the application of AI and Machine Learning in tennis, specifically focusing on the work of Stephanie Kovalchik, a Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia. The conversation covers Tennis Australia's use of data for player rating systems, the development of products by the Game Insight Group, including a win forecasting algorithm, and a statistic to measure player workload. The article highlights the practical applications of AI in sports analytics and player performance evaluation.
Reference

“The article doesn't contain a direct quote, but it discusses the topics covered in the conversation.”

PermalinkPractical AI