| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 51. | Markéta Vondroušová | 1 | 1 | 0 | 3 | 3 | 3 | 8 | 9 | 28 | 6350 | 227 |
| 52. | Sofia Kenin | 1 | 1 | 0 | 0 | 3 | 6 | 9 | 12 | 32 | 5550 | 173 |
| 53. | Sue Barker | 1 | 0 | 3 | 2 | 7 | 5 | 6 | 7 | 31 | 8020 | 259 |
| 54. | Flavia Pennetta | 1 | 0 | 1 | 5 | 7 | 10 | 7 | 18 | 49 | 8580 | 175 |
| 55. | Jeļena Ostapenko | 1 | 0 | 1 | 4 | 1 | 11 | 10 | 14 | 42 | 7010 | 167 |
| 56. | Mirra Andreeva | 1 | 0 | 1 | 2 | 4 | 2 | 3 | 1 | 14 | 5080 | 363 |
| 57. | Anastasia Myskina | 1 | 0 | 0 | 5 | 4 | 5 | 5 | 8 | 28 | 6190 | 221 |
| 58. | Iva Majoli | 1 | 0 | 0 | 5 | 3 | 5 | 9 | 11 | 34 | 6260 | 184 |
| 59. | Linda Nosková | 1 | 0 | 0 | 1 | 1 | 2 | 4 | 7 | 16 | 3280 | 205 |
| 60. | Emma Raducanu | 1 | 0 | 0 | 0 | 2 | 3 | 7 | 3 | 16 | 3390 | 212 |
| 61. | Bianca Andreescu | 1 | 0 | 0 | 0 | 1 | 5 | 6 | 5 | 18 | 3360 | 187 |
| 62. | Chris O'Neil | 1 | 0 | 0 | 0 | 0 | 5 | 12 | 5 | 23 | 3540 | 154 |
| 63. | Barbara Jordan | 1 | 0 | 0 | 0 | 0 | 5 | 8 | 8 | 22 | 3290 | 150 |
| 64. | Helena Suková | 0 | 4 | 3 | 11 | 13 | 10 | 9 | 11 | 61 | 17430 | 286 |
| 65. | Mary Joe Fernández | 0 | 3 | 6 | 8 | 11 | 13 | 2 | 5 | 48 | 16540 | 345 |
| 66. | Wendy Turnbull | 0 | 3 | 4 | 7 | 13 | 9 | 6 | 7 | 49 | 14810 | 302 |
| 67. | Dinara Safina | 0 | 3 | 2 | 2 | 4 | 6 | 5 | 11 | 33 | 8520 | 258 |
| 68. | Ons Jabeur | 0 | 3 | 0 | 4 | 3 | 7 | 4 | 11 | 32 | 7640 | 239 |
| 69. | Elena Dementieva | 0 | 2 | 7 | 3 | 12 | 9 | 7 | 7 | 47 | 13960 | 297 |
| 70. | Andrea Jaeger | 0 | 2 | 5 | 3 | 2 | 0 | 5 | 1 | 18 | 8630 | 479 |
| 71. | Rosemary Casals | 0 | 2 | 4 | 10 | 7 | 4 | 12 | 3 | 42 | 13090 | 312 |
| 72. | Helen Gourlay | 0 | 2 | 3 | 3 | 5 | 10 | 8 | 2 | 33 | 9310 | 282 |
| 73. | Karolína Muchová | 0 | 2 | 3 | 3 | 2 | 5 | 4 | 9 | 28 | 7730 | 276 |
| 74. | Karolína Plíšková | 0 | 2 | 2 | 7 | 3 | 8 | 16 | 13 | 51 | 10180 | 200 |
| 75. | Vera Zvonareva | 0 | 2 | 2 | 2 | 10 | 11 | 9 | 13 | 49 | 9610 | 196 |
| 76. | Olga Morozova | 0 | 2 | 1 | 7 | 5 | 6 | 2 | 1 | 24 | 8520 | 355 |
| 77. | Renáta Tomanová | 0 | 2 | 1 | 3 | 3 | 11 | 10 | 7 | 37 | 7590 | 205 |
| 78. | Amanda Anisimova | 0 | 2 | 1 | 2 | 5 | 4 | 4 | 8 | 26 | 6320 | 243 |
| 79. | Jasmine Paolini | 0 | 2 | 0 | 1 | 3 | 3 | 6 | 12 | 27 | 4680 | 173 |
| 80. | Pam Shriver | 0 | 1 | 8 | 10 | 5 | 10 | 9 | 10 | 53 | 15070 | 284 |
| 81. | Jelena Janković | 0 | 1 | 5 | 2 | 14 | 10 | 12 | 12 | 56 | 11680 | 209 |
| 82. | Zina Garrison | 0 | 1 | 4 | 10 | 15 | 7 | 9 | 9 | 55 | 13950 | 254 |
| 83. | Agnieszka Radwańska | 0 | 1 | 4 | 7 | 15 | 8 | 10 | 4 | 49 | 12810 | 261 |
| 84. | Helga Niessen Masthoff | 0 | 1 | 3 | 6 | 1 | 2 | 4 | 0 | 17 | 7000 | 412 |
| 85. | Dianne Fromholtz | 0 | 1 | 3 | 3 | 12 | 9 | 6 | 13 | 47 | 9530 | 203 |
| 86. | Jessica Pegula | 0 | 1 | 2 | 7 | 2 | 6 | 4 | 8 | 30 | 7490 | 250 |
| 87. | Anke Huber | 0 | 1 | 2 | 4 | 13 | 9 | 7 | 7 | 43 | 9430 | 219 |
| 88. | Sara Errani | 0 | 1 | 2 | 4 | 0 | 10 | 13 | 20 | 50 | 6990 | 140 |
| 89. | Eugenie Bouchard | 0 | 1 | 2 | 1 | 2 | 4 | 9 | 8 | 27 | 5000 | 185 |
| 90. | Natasha Zvereva | 0 | 1 | 1 | 6 | 11 | 12 | 13 | 8 | 52 | 9850 | 189 |
| 91. | Judy Tegart-Dalton | 0 | 1 | 1 | 6 | 3 | 5 | 1 | 0 | 17 | 6100 | 359 |
| 92. | Dominika Cibulková | 0 | 1 | 1 | 6 | 2 | 16 | 7 | 13 | 46 | 7840 | 170 |
| 93. | Sabine Lisicki | 0 | 1 | 1 | 3 | 3 | 7 | 10 | 10 | 35 | 5800 | 166 |
| 94. | Kathy Jordan | 0 | 1 | 1 | 2 | 12 | 2 | 4 | 6 | 28 | 6420 | 229 |
| 95. | Betty Stöve | 0 | 1 | 1 | 1 | 10 | 8 | 8 | 7 | 36 | 6580 | 183 |
| 96. | Lucie Šafářová | 0 | 1 | 1 | 1 | 6 | 10 | 15 | 19 | 53 | 6490 | 122 |
| 97. | Danielle Collins | 0 | 1 | 1 | 1 | 2 | 6 | 11 | 10 | 32 | 4640 | 145 |
| 98. | Jennifer Brady | 0 | 1 | 1 | 0 | 2 | 2 | 4 | 7 | 17 | 3170 | 186 |
| 99. | Florența Mihai | 0 | 1 | 1 | 0 | 0 | 1 | 4 | 4 | 11 | 2530 | 230 |
| 100. | Anastasia Pavlyuchenkova | 0 | 1 | 0 | 9 | 2 | 13 | 23 | 19 | 67 | 9140 | 136 |
Open Era Grand Slam Tennis
This site is dedicated to Grand Slam tennis stats from the Open Era – for those of us who love the numbers behind the game. Pick any group of players and see how they rank. Compare, filter, and view the same data from different angles – whether you want to explore dominance, consistency, or longevity. In short: It’s all about turning tennis history into insights you can actually play with.