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
34
Height
5'8" (172 cm)
Plays
Right-Handed
138
Wins
122
Losses
53.1%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2024 | 0/4 | - | 0/3 | 0/1 |
| 2022 | 16/14 | 3/3 | 12/8 | 1/3 |
| 2021 | 10/14 | 6/5 | 4/9 | - |
| 2020 | 11/6 | - | 11/6 | - |
| 2019 | 21/17 | 4/6 | 14/9 | 3/2 |
| 2018 | 36/21 | 5/5 | 31/15 | 0/1 |
| 2017 | 28/19 | 5/5 | 22/13 | 1/1 |
| 2016 | 11/13 | 1/2 | 10/10 | 0/1 |
| 2015 | 5/14 | 0/2 | 5/10 | 0/2 |
| Career | 138/122 | 24/28 | 109/83 | 5/11 |
No serve and return data available yet.
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| Sep 25, 2024 | Beijing | Round of 128 | Alycia Parks | Hard | 61 46 26 | L |
| Aug 26, 2024 | Us Open | Round of 128 | Liudmila Samsonova | Hard | 26 57 | L |
| Jul 1, 2024 | Wimbledon | Round of 128 | Emma Navarro | Grass | 06 26 | L |
| Jan 29, 2024 | Hua Hin | Round of 32 | Xiyu Wang | Hard | 16 16 | L |
| Sep 19, 2022 | Tokyo | Round of 32 | Elise Mertens | Hard | 06 36 | L |
| Sep 12, 2022 | Chennai | Round of 16 | Nao Hibino | Hard | 26 36 | L |
| Sep 12, 2022 | Chennai | Round of 32 | Yanina Wickmayer | Hard | 64 16 64 | W |
| Jul 25, 2022 | Prague | Round of 32 | Rebecca Peterson | Hard | 16 63 76 | W |
| Jul 25, 2022 | Prague | Round of 16 | Dalila Jakupovic | Hard | 63 61 | W |
| Jul 25, 2022 | Prague | Semifinals | Anastasia Potapova | Hard | 36 06 | L |
Qiang Wang is currently ranked #9999 in the WTA singles rankings with 0 points.
Qiang Wang (WTA #9999) has a career win-loss record of 138-122 (53.1% win rate) and has won 0 WTA titles.
Smashrs tracks Qiang'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.
