WTA Tour
WTA World Ranking - 0 pts
🪃 Counterpuncher
Turns defense into offense. Absorbs pace, redirects with precision, and thrives in long rallies by letting opponents beat themselves. Excels at converting break points when they matter most.
Strong against
Weak against
Age
32
Height
5'7" (170 cm)
Plays
Right-Handed
87
Wins
119
Losses
42.2%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2025 | 0/1 | - | 0/1 | - |
| 2024 | 1/6 | 0/1 | 1/5 | - |
| 2021 | 10/17 | 3/4 | 7/13 | - |
| 2020 | 10/4 | - | 10/4 | - |
| 2019 | 23/22 | 3/4 | 20/15 | 0/3 |
| 2018 | 13/12 | 0/3 | 12/7 | 1/2 |
| 2017 | 8/11 | 1/2 | 7/8 | 0/1 |
| 2016 | 13/25 | 0/3 | 10/18 | 3/4 |
| 2015 | 9/21 | 1/2 | 8/16 | 0/3 |
| Career | 87/119 | 8/19 | 75/87 | 4/13 |
No serve and return data available yet.
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| Jan 13, 2025 | Australian Open | Round of 128 | Erika Andreeva | Hard | 16 67 | L |
| Dec 30, 2024 | Brisbane | Round of 64 | Ons Jabeur | Hard | 67 46 | L |
| Oct 28, 2024 | Jiujiang | Round of 32 | Jana Fett | Hard | 64 26 64 | W |
| Oct 28, 2024 | Jiujiang | Round of 16 | Mananchaya Sawangkaew | Hard | 64 16 67 | L |
| Oct 14, 2024 | Osaka | Round of 32 | Kimberly Birrell | Hard | 26 36 | L |
| Sep 16, 2024 | Hua Hin 2 | Round of 32 | Jana Fett | Hard | 62 36 36 | L |
| Aug 26, 2024 | Us Open | Round of 128 | Jessika Ponchet | Hard | 46 16 | L |
| Jul 15, 2024 | Palermo | Round of 32 | Chloe Paquet | Clay | 36 36 | L |
| Nov 8, 2021 | Linz | Round of 32 | Clara Burel | Hard | 64 61 | W |
| Nov 8, 2021 | Linz | Round of 16 | Jasmine Paolini | Hard | 16 62 46 | L |
Saisai Zheng is currently ranked #9999 in the WTA singles rankings with 0 points.
Saisai Zheng (WTA #9999) has a career win-loss record of 87-119 (42.2% win rate) and has won 0 WTA titles.
Smashrs tracks Saisai's upcoming matches with AI-powered predictions across six independent models. Our confidence score reflects the degree of agreement between models - a higher score means stronger consensus. Check back before each match for the latest prediction.
