Win Probability

Thursday, 1 October 2026
20 rated matches · 3 tournamentsFrozen pre-match predictions · final results
Closest matchXinyu Gao vs Panna Udvardy49% · 51%Toss-up · Beijing · R128 · Analyze match →
Strongest favouriteAlexander Zverev vs Cameron Norrie92% · 8%Strong favourite · Beijing · R32 · Analyze match →
Rated that day20 matches203 tournaments · pre-match predictions

Rated matches

Pre-match probability, frozen at the start · with final result
FinalBeijing · R128 · HardXinyu Gao won 6-2 6-3Xinyu Gao49%Panna Udvardy51%Toss-upUnderdog wonH2H 1–0FinalBeijing · R128 · HardLin Zhu won 6-4 6-2Alycia Parks54%Lin Zhu46%Toss-upUnderdog wonH2H 2–1FinalBeijing · R128 · HardAlina Charaeva won 5-7 7-5 6-2Yuliia Starodubtseva55%Alina Charaeva45%Toss-upUnderdog wonH2H 0–1FinalBeijing · R32 · HardFrancisco Cerundolo won 5-7 6-4 6-3Botic Van De Zandschulp45%Francisco Cerundolo55%Toss-upFavourite wonH2H 0–5FinalTokyo · R32 · HardJaime Faria won 6-4 3-6 6-4Jaime Faria56%Arthur Fery44%Toss-upFavourite wonH2H 0–1FinalBeijing · R128 · HardKatie Volynets won 7-5 7-5Katie Volynets56%Robin Montgomery44%Toss-upFavourite wonH2H 1–0FinalBeijing · R32 · HardJakub Mensik won 6-4 7-6(5)Alexander Bublik43%Jakub Mensik57%Toss-upFavourite wonH2H 3–1FinalTokyo · R32 · HardKyrian Jacquet won 6-3 6-1Holger Rune59%Kyrian Jacquet41%Slight edgeUnderdog wonH2H 0–1FinalBeijing · R32 · HardQuentin Halys won 6-1 7-6(3)Ignacio Buse41%Quentin Halys59%Slight edgeFavourite wonH2H 0–1FinalBeijing · R128 · HardKaterina Siniakova won 6-4 6-3Magda Linette41%Katerina Siniakova59%Slight edgeFavourite wonH2H 3–3FinalBeijing · R32 · HardJuncheng Shang won 5-7 6-3 7-5Juncheng Shang60%Sebastian Baez40%Slight edgeFavourite wonH2H 0–1FinalBeijing · R32 · HardHubert Hurkacz won 5-7 6-3 6-4Learner Tien61%Hubert Hurkacz39%Slight edgeUnderdog wonH2H 0–1FinalBeijing · R32 · HardRoman Safiullin won 6-3 6-2Roman Safiullin38%Flavio Cobolli62%Slight edgeUnderdog wonH2H 1–1FinalTokyo · R32 · HardStefanos Tsitsipas won 4-6 6-3 6-4Tomas Martin Etcheverry36%Stefanos Tsitsipas64%Slight edgeFavourite wonH2H 0–3FinalTokyo · R32 · HardMatteo Berrettini won 1-6 7-6(1) 6-4Alejandro Davidovich Fokina64%Matteo Berrettini36%Slight edgeUnderdog wonH2H 1–2FinalBeijing · R128 · HardPaula Badosa won 4-6 7-6(7) 6-4Paula Badosa65%Daria Kasatkina35%Slight edgeFavourite wonH2H 4–5FinalTokyo · R32 · HardLuciano Darderi won 7-6(3) 6-3Luciano Darderi30%Casper Ruud70%Clear favouriteUnderdog wonH2H 1–1FinalBeijing · R32 · HardAlex De Minaur won 7-6(4) 6-2Alex De Minaur76%Mariano Navone24%Clear favouriteFavourite wonH2H 2–0FinalTokyo · R32 · HardCarlos Alcaraz won 7-6(1) 4-6 6-1Carlos Alcaraz91%Alex Michelsen9%Strong favouriteFavourite wonH2H 0–1FinalBeijing · R32 · HardAlexander Zverev won 7-6(1) 6-4Alexander Zverev92%Cameron Norrie8%Strong favouriteFavourite wonH2H 1–9
Why isn't every match rated? →

Model performance

Measured on predictions the model actually made
Tour familyPredictionsFav. wonAccuracy
ATP / WTA2,396—67%
Challenger Men3,053—63%
Challenger Women786—66%
ITF Men4,224—66%
ITF Women3,874—66%
Yesterday · 30 Sep9 of 20 favourites wonBased on its probabilities, the model expected 12.4 favourites to win.View yesterday →
Biggest shock · last 7 days30 Sep 2026W100 Templeton · R32Amelie Van Impe beat Kayla Day 6-2 6-4Pre-match: Amelie Van Impe 6%Surprise score94

How Win Probability works

Read methodology →
Separate models for each tour family.Pre-match only: probabilities update until the match starts.Frozen at the start and never rewritten afterwards.A statistical estimate, not a certainty; the two probabilities always add up to 100%.