TennisExpert: Towards Expert-Level Analytical Sports Video Understanding
Zhaoyu Liu, Xi Weng, Lianyu Hu, Zhe Hou, Kan Jiang, Jin Song Dong, Yang Liu

TL;DR
TennisExpert introduces a multimodal framework and a large-scale annotated dataset for expert-level understanding of tennis videos, enabling detailed tactical analysis and real-time commentary.
Contribution
The paper presents TennisVL, a comprehensive tennis benchmark dataset, and TennisExpert, a novel multimodal system that captures tactical reasoning and match dynamics.
Findings
Outperforms proprietary baselines like GPT-5, Gemini, and Claude
Effectively captures tactical context and match momentum
Provides publicly available dataset and code for further research
Abstract
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 underexplored due to two key challenges: (1) the lack of large-scale benchmarks with fine-grained annotations and expert-level commentary, and (2) the difficulty of building accurate yet efficient multimodal systems suitable for real-time deployment. To address these challenges, we introduce TennisVL, a large-scale tennis benchmark comprising over 200 professional matches (471.9 hours) and 40,000+ rally-level clips. Unlike existing commentary datasets that focus on descriptive play-by-play narration, TennisVL emphasizes expert analytical commentary capturing tactical reasoning, player decisions, and match momentum. Furthermore, we propose TennisExpert, a…
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Taxonomy
TopicsVideo Analysis and Summarization · Human Pose and Action Recognition · Anomaly Detection Techniques and Applications
