Tennis predictions 13 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.
17Matches
3Tournaments
16Forecast
9,192Players rated
Strongest calls of the day
19:05GuadalajaraR6Peyton Stearns2Emiliana Arango02–0AI prediction83%High confidence17%ForecastStearns to win83%Full analysis 18:15US Open, MenR29Alexander Zverev3Ben Shelton13–1AI prediction77%High confidence23%ForecastZverev to win77%Full analysis 19:20GuadalajaraR6Alycia Parks2Varvara Lepchenko12–0AI prediction67%Medium confidence33%ForecastParks to win67%Full analysis
All matches by tournament
ATP US Open, Men
WTA Guadalajara
CancelledAlycia ParksMayar Sherif
–
–
›16:00Carole MonnetKatrina Scott7662
6721
Scott64%0–2›16:00Nadiia KichenokNao Hibino120
662
Hibino60%0–2›16:05Sara Sorribes TormoCaroline Dolehide6361
4672
Dolehide58%0–2›17:20Iryna ShymanovichLea Ma731
600
Shymanovich62%2–0›19:05Peyton StearnsEmiliana Arango662
320
Stearns83%2–0›19:20Alycia ParksVarvara Lepchenko6172
3651
Parks67%2–0›19:20Kozyreva M / Lumsden MDay K / Zarazua R
20:30Panna UdvardyLois Boisson662
330
Doubles6662
4721
Udvardy64%2–0›21:20Darja VidmanovaJanice Tjen620
762
Tjen52%0–2›23:20Cristina BucsaBianca Andreescu662
430
Bucsa54%2–0›WTA WTA Sao Paulo, Brazil Women, Singles
00:30Maria Florencia UrrutiaAnastasia Tikhonova
210
662
Tikhonova59%0–2›18:25Justina MikulskyteChloe Paquet340
662
Mikulskyte62%2–0›18:30Xiaodi YouVictoria Bosio672
350
Bosio50%0–2›20:10Whitney OsuigweAnastasia Tikhonova662
220
Tikhonova63%0–2›20:20Hayu KinoshitaCadence Brace560
772
Brace54%0–2›
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.