Tennis predictions 21 September 2026
AI tennis predictions for every singles match: who wins, the most likely set score and the chance of a deciding set, from player ratings built on 57,590 matches.
20Matches
5Tournaments
14Forecast
9,192Players rated
Strongest calls of the day
10:30SingaporeR6Kyoka Okamura0Leylah Fernandez20–2AI prediction16%High confidence84%ForecastFernandez to win84%Full analysis 04:25SeoulR6Alina Korneeva2Mananchaya Sawangkaew02–0AI prediction84%High confidence16%ForecastKorneeva to win84%Full analysis 07:15SingaporeR6Rebecca Šramková0Maja Chwalinska20–2AI prediction17%High confidence83%ForecastChwalinska to win83%Full analysis
All matches by tournament
WTA Seoul
03:00Katie VolynetsElvina Kalieva
662
300
Volynets71%2–0›03:00Lanlana TararudeeMoyuka Uchijima6662
4721
Tararudee83%2–0›03:00Xinxin YaoMaya Joint6631
2762
Joint71%0–2›04:25Alina KorneevaMananchaya Sawangkaew662
420
Korneeva84%2–0›05:35Kamilla RakhimovaPolina Kudermetova7472
6651
Kudermetova55%0–2›06:05Yue YuanDayeon Back3611
6462
Back70%0–2›08:50Bondar A / Stollar FJoint M / Ruse E-G
09:00Darya AstakhovaMagda Linette160
672
Doubles3672
6161
Astakhova56%2–0›10:30Cho I-H / Cho Y TLiang E S / Yuan Y
4681
63102
Doubles12:05Lee E / Park SoLee Y / Ye Q Y
350
672
DoublesWTA Singapore
03:00Daria KasatkinaAliaksandra Sasnovich
500
762
Kasatkina52%2–0›04:40Kristina MladenovićNao Hibino5641
7362
Hibino60%0–2›06:00Talia GibsonFiona Ferro662
330
Gibson76%2–0›07:15Rebecca ŠramkováMaja Chwalinska420
662
Chwalinska83%0–2›10:30Kyoka OkamuraLeylah Fernandez230
662
Fernandez84%0–2›13:15Storm HunterJoanna Garland3711
6562
Garland55%0–2›WTA WTA Sao Paulo, Brazil Women, Singles
WTA Singapore Doubles
07:30Kato M / Perez ESakkari M / Vekić D
762
510
Doubles08:55Ferro F / Fruhvirtova LTang Q / Xu Y
420
662
DoublesWTA WTA Sao Paulo, Brazil Women Doubles
14:00Dabrowski G / Stefani LRogers A / Zamarripa A
63102
3671
Doubles
How these predictions are made
Every player carries a rating that moves after each match by how surprising the result was — beating a stronger opponent is worth more than beating a weaker one, and a win in an ATP or WTA draw counts for more than one in an ITF event. The win probability comes from the gap between two ratings, adjusted by their head-to-head record. The set score follows from that probability rather than being guessed separately. Where a player has played too few matches, or has never played at tour level, the rating is pulled back towards the average and the match is marked as thin data instead of being dressed up as a confident call. Doubles are excluded: the rating measures singles.
Every player carries a rating that moves after each match by how surprising the result was — beating a stronger opponent is worth more than beating a weaker one, and a win in an ATP or WTA draw counts for more than one in an ITF event. The win probability comes from the gap between two ratings, adjusted by their head-to-head record. The set score follows from that probability rather than being guessed separately. Where a player has played too few matches, or has never played at tour level, the rating is pulled back towards the average and the match is marked as thin data instead of being dressed up as a confident call. Doubles are excluded: the rating measures singles.