WTA Tour
WTA World Ranking - 0 pts
🛡️ The Spoiler
A defensive specialist who retrieves better than a Grinder but without the elite return game of a Counterpuncher. Neutralises power hitters through court coverage and consistency - and uniquely, holds a winning record against The Complete Package.
Strong against
Weak against
Age
37
Height
5'6" (168 cm)
Plays
Right-Handed
23
Wins
32
Losses
41.8%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2020 | 0/1 | 0/1 | - | - |
| 2017 | 2/3 | - | 2/3 | - |
| 2016 | 6/19 | 5/10 | 1/8 | 0/1 |
| 2015 | 15/9 | 13/4 | 2/4 | 0/1 |
| Career | 23/32 | 18/15 | 5/15 | 0/2 |
No serve and return data available yet.
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| Feb 7, 2020 | Fed Cup QLS R1: GER vs BRA | Round Robin | Laura Siegemund | Clay | 36 36 | L |
| Feb 10, 2017 | Fed Cup G1 RR: BRA vs CHI | Round Robin | Daniela Seguel | Hard | 57 57 | L |
| Feb 10, 2017 | Fed Cup G1 RR: ARG vs BRA | Round Robin | Catalina Pella | Hard | 36 64 62 | W |
| Feb 10, 2017 | Fed Cup G1 RR: BRA vs COL | Round Robin | Mariana Duque Marino | Hard | 46 16 | L |
| Feb 10, 2017 | Fed Cup G1 RR: BRA vs MEX | Round Robin | Renata Zarazua | Hard | 46 63 63 | W |
| Jan 9, 2017 | Hobart | Round of 32 | Sachia Vickery | Hard | 36 67 | L |
| Aug 29, 2016 | US Open | Round of 128 | Carla Suarez Navarro | Hard | 06 06 | L |
| Aug 8, 2016 | Olympics | Round of 64 | Caroline Garcia | Hard | 16 26 | L |
| Aug 1, 2016 | Florianopolis | Round of 32 | Lyudmyla Kichenok | Hard | 36 26 | L |
| Jul 18, 2016 | Bastad | Round of 32 | Lucie Hradecka | Clay | 26 26 | L |
Teliana Pereira is currently ranked #9999 in the WTA singles rankings with 0 points.
Teliana Pereira (WTA #9999) has a career win-loss record of 23-32 (41.8% win rate) and has won 0 WTA titles.
Smashrs tracks Teliana'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.
