WTA Tour
WTA World Ranking - 100 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
32
Height
5'3" (160 cm)
Plays
Left-Handed
56
Wins
86
Losses
39.4%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2026 | 0/1 | 0/1 | - | - |
| 2025 | 0/1 | - | 0/1 | - |
| 2024 | 7/19 | 2/7 | 5/11 | 0/1 |
| 2023 | 22/23 | 5/5 | 17/16 | 0/2 |
| 2022 | 18/15 | 12/5 | 6/8 | 0/2 |
| 2021 | 4/15 | 1/4 | 3/9 | 0/2 |
| 2020 | 3/2 | 3/1 | 0/1 | - |
| 2019 | 1/6 | 1/5 | 0/1 | - |
| 2018 | 0/2 | 0/2 | - | - |
| 2017 | 1/2 | 1/2 | - | - |
| Career | 56/86 | 25/32 | 31/47 | 0/7 |
Averages · Last 90 days (1 matches)
Serve
Return
Rally
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| May 5, 2026 | Rome | Round of 128 | Talia Gibson | Clay | 46 60 36 | L |
| Sep 8, 2025 | Guadalajara | Round of 32 | Rebecca Marino | Hard | 26 36 | L |
| Oct 28, 2024 | Jiujiang | Round of 32 | Wushuang Zheng | Hard | 61 62 | W |
| Oct 28, 2024 | Jiujiang | Round of 16 | Anna Bondar | Hard | 76 62 | W |
| Oct 28, 2024 | Jiujiang | Quarterfinals | Rebecca Sramkova | Hard | 36 63 26 | L |
| Sep 25, 2024 | Beijing | Round of 128 | Taylor Townsend | Hard | 26 64 36 | L |
| Sep 9, 2024 | Guadalajara | Round of 32 | Caroline Dolehide | Hard | 63 62 | W |
| Sep 9, 2024 | Guadalajara | Round of 16 | Renata Zarazua | Hard | 64 63 | W |
| Sep 9, 2024 | Guadalajara | Quarterfinals | Olivia Gadecki | Hard | 26 63 16 | L |
| Aug 26, 2024 | Us Open | Round of 128 | Taylor Townsend | Hard | 26 57 | L |
Martina Trevisan is currently ranked #516 in the WTA singles rankings with 100 points.
Martina Trevisan (WTA #516) has a career win-loss record of 56-86 (39.4% win rate) and has won 0 WTA titles.
Smashrs tracks Martina'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.
