WTA Tour
WTA World Ranking - 0 pts
🤖 Servebot
Lives and dies by the serve. Racks up free points with aces and unreturnable deliveries, holding serve with ease. Return games are the weaker side, making break points critical.
Strong against
Weak against
Age
35
Height
5'11" (181 cm)
Plays
Right-Handed
156
Wins
141
Losses
52.5%
Win %
0
Titles
Career record broken down by surface
| Year | Summary | Clay | Hard | Grass |
|---|---|---|---|---|
| 2025 | 3/4 | - | 3/3 | 0/1 |
| 2024 | 9/19 | 3/6 | 5/11 | 1/2 |
| 2023 | 19/20 | 4/4 | 13/14 | 2/2 |
| 2022 | 28/18 | 14/6 | 11/9 | 3/3 |
| 2021 | 15/21 | 6/5 | 7/13 | 2/3 |
| 2020 | 14/11 | 6/4 | 8/7 | - |
| 2019 | 33/16 | 13/3 | 14/11 | 6/2 |
| 2018 | 26/17 | 7/5 | 18/10 | 1/2 |
| 2017 | 6/4 | 3/1 | 0/2 | 3/1 |
| 2016 | 3/3 | 3/2 | 0/1 | - |
| 2015 | 0/8 | 0/4 | 0/4 | - |
| Career | 156/141 | 59/40 | 79/85 | 18/16 |
No serve and return data available yet.
Last 10 results
| Date | Tournament | Round | Opponent | Surface | Score | Result |
|---|---|---|---|---|---|---|
| Jun 30, 2025 | Wimbledon | Round of 128 | Diane Parry | Grass | 64 36 26 | L |
| Feb 24, 2025 | Merida | Round of 32 | Sloane Stephens | Hard | 62 63 | W |
| Feb 24, 2025 | Merida | Round of 16 | Emma Navarro | Hard | 16 26 | L |
| Jan 27, 2025 | Linz | Round of 16 | Elina Avanesyan | Hard | 64 46 75 | W |
| Jan 27, 2025 | Linz | Quarterfinals | Ekaterina Alexandrova | Hard | 63 26 26 | L |
| Jan 27, 2025 | Linz | Round of 32 | Eva Lys | Hard | 64 57 63 | W |
| Jan 13, 2025 | Australian Open | Round of 128 | Jaqueline Cristian | Hard | 26 64 67 | L |
| Oct 28, 2024 | Jiujiang | Round of 32 | Kamilla Rakhimova | Hard | 16 64 57 | L |
| Oct 21, 2024 | Guangzhou | Round of 32 | Katerina Siniakova | Hard | 26 16 | L |
| Aug 26, 2024 | Us Open | Round of 128 | Jessica Bouzas Maneiro | Hard | 36 06 | L |
Petra Martic is currently ranked #9999 in the WTA singles rankings with 0 points.
Petra Martic (WTA #9999) has a career win-loss record of 156-141 (52.5% win rate) and has won 0 WTA titles.
Smashrs tracks Petra'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.
