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Forecasting the Winner of a Live Tennis Match

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

With the rise of live sports betting in recent years, tennis forecasting has expanded from pre-match prediction to models that update win probabilities as a match unfolds. A central challenge in creating such a model is the constant need for models to adapt to score and performance changes. This study examines how pre-match and live information can be most effectively integrated into a model to produce accurate win-probability estimates. The analysis uses 8,222 Grand Slam matches containing a total of 1,505,355 points. Five models were evaluated using a chronological split, with matches from 2

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Evidence & attribution

First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.