Tennis Match

Tennis match analysis is a burgeoning field leveraging machine learning to understand and predict match outcomes, focusing on quantifying intangible factors like momentum and player performance. Researchers employ diverse models, including Support Vector Machines, XGBoost, and neural networks (like CNN-RNNs), to analyze various data sources such as player movement, shot selection, and even vocalizations (grunts). These analyses aim to improve player training, provide real-time strategic insights during matches, and offer a more nuanced understanding of competitive dynamics beyond traditional statistics.