Topological Data Analysis and Graph-Theoretic Approaches for Tennis Match Prediction

arXiv:2607.23509 · cs.LG, math.AT, stat.ML · Submitted 2026-07-26 · Read on arXiv

Jake Schwaderer, Alexander Bastien, Omid Khormali, Alejandro Navarrete, Mia Pesavento, Angelika Elderbrook

cs.LG, math.AT, stat.ML

Submitted: 2026-07-26

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 28× in this paper · explained in 1 episode
• Topological Data Analysis — 13× in this paper
• Persistent Homology — 10× in this paper · explained in 4 episodes
• AUC — 9× in this paper · explained in 2 episodes
• Feature Importance — 6× in this paper · explained in 2 episodes
• Modified Band Depth — 6× in this paper
• XGBoost — 6× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• External Validation — 2× in this paper · explained in 2 episodes
• Feature Engineering — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 14 episodes
• Hierarchical Normalized Averaged Velocity — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Vector of Averaged Bettis — 2× in this paper
• Adam — 1× in this paper · explained in 3 episodes
• Class Imbalance — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Data Leakage — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 3 episodes
• Hierarchical Structure — 1× in this paper · explained in 3 episodes
• Hierarchical Weighted Normalized Averaged Velocity — 1× in this paper
• Overfitting — 1× in this paper · explained in 2 episodes
• Redundancy — 1× in this paper · explained in 2 episodes
• Representation Learning — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 5 episodes
• Topological Data Analysis (TDA) — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 16 episodes

Sources

• Hierarchical Persistence Velocity for Network Anomaly Detection: Theory and Applications to Cryptocurrency Markets

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