WTA Tour
WTA World Ranking - 446 pts
🧱 The Wall
An impenetrable defender who retrieves everything and forces opponents into errors. Rarely beats themselves, with an elite return game that makes every service game a battle.
Strong against
Weak against
Age
34
Plays
Left-Handed
11
Wins
23
Losses
32.4%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2026 | 0/1 | 0/1 | - | - |
| 2025 | 0/1 | 0/1 | - | - |
| 2022 | 1/5 | 1/2 | 0/2 | 0/1 |
| 2021 | 2/5 | 2/4 | 0/1 | - |
| 2020 | 3/1 | - | 3/1 | - |
| 2019 | 1/4 | 0/1 | 1/3 | - |
| 2018 | 0/3 | - | 0/3 | - |
| 2017 | 2/1 | - | 2/1 | - |
| 2016 | 2/1 | - | 2/1 | - |
| 2015 | 0/1 | - | 0/1 | - |
| Career | 11/23 | 3/9 | 8/13 | 0/1 |
Averages · Last 90 days (1 matches)
Serve
Return
Rally
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| Mar 30, 2026 | Charleston | Round of 32 | Yuliia Starodubtseva | Clay | 63 16 26 | L |
| Aug 4, 2025 | W50+H Leipzig | Round of 32 | Julia Avdeeva | Clay | 63 36 67 | L |
| Jul 25, 2022 | Prague | Round of 32 | Anett Kontaveit | Hard | 06 16 | L |
| Jul 11, 2022 | Budapest | Round of 32 | Shuai Zhang | Clay | 57 16 | L |
| Jun 27, 2022 | Wimbledon | Round of 128 | Irina Camelia Begu | Grass | 46 16 | L |
| Apr 4, 2022 | Bogota | Round of 32 | Yuliana Monroy | Clay | 60 63 | W |
| Apr 4, 2022 | Bogota | Round of 16 | Laura Pigossi | Clay | 36 26 | L |
| Mar 21, 2022 | Miami | Round of 128 | Anhelina Kalinina | Hard | 26 63 36 | L |
| Sep 27, 2021 | Nur-Sultan | Round of 32 | Yulia Putintseva | Hard | 16 26 | L |
| Jul 19, 2021 | Gdynia | Quarterfinals | Kristina Kucova | Clay | 76 67 67 | L |
Ekaterine Gorgodze is currently ranked #164 in the WTA singles rankings with 446 points.
Ekaterine Gorgodze (WTA #164) has a career win-loss record of 11-23 (32.4% win rate) and has won 0 WTA titles.
Smashrs tracks Ekaterine'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.
