| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. | Chris Evert | 18 | 16 | 18 | 2 | 0 | 2 | 0 | 0 | 56 | 70510 | 1259 |
| 2. | Novak Djokovic | 24 | 14 | 16 | 11 | 5 | 7 | 3 | 2 | 82 | 83859 | 1023 |
| 3. | Martina Navratilova | 18 | 14 | 12 | 9 | 6 | 1 | 3 | 4 | 67 | 67639 | 1010 |
| 4. | Roger Federer | 20 | 11 | 15 | 12 | 11 | 5 | 1 | 6 | 81 | 72718 | 898 |
| 5. | Ivan Lendl | 8 | 11 | 9 | 6 | 8 | 4 | 4 | 7 | 57 | 41292 | 724 |
| 6. | Evonne Goolagong Cawley | 7 | 11 | 4 | 4 | 2 | 3 | 2 | 0 | 33 | 33196 | 1006 |
| 7. | Serena Williams | 23 | 10 | 7 | 14 | 10 | 11 | 3 | 3 | 81 | 72794 | 899 |
| 8. | Steffi Graf | 22 | 9 | 6 | 5 | 6 | 2 | 2 | 2 | 54 | 63341 | 1173 |
| 9. | Venus Williams | 7 | 9 | 7 | 16 | 11 | 13 | 11 | 21 | 95 | 41408 | 436 |
| 10. | Rafael Nadal | 22 | 8 | 8 | 9 | 7 | 5 | 6 | 3 | 68 | 65953 | 970 |
| 11. | Arantxa Sánchez Vicario | 4 | 8 | 10 | 13 | 8 | 2 | 6 | 7 | 58 | 32953 | 568 |
| 12. | Andy Murray | 3 | 8 | 10 | 9 | 8 | 7 | 7 | 8 | 60 | 29991 | 500 |
| 13. | Jimmy Connors | 8 | 7 | 16 | 10 | 2 | 4 | 4 | 7 | 58 | 41862 | 722 |
| 14. | Andre Agassi | 8 | 7 | 11 | 10 | 6 | 3 | 7 | 9 | 61 | 39036 | 640 |
| 15. | Martina Hingis | 5 | 7 | 7 | 5 | 3 | 5 | 2 | 3 | 37 | 27301 | 738 |
| 16. | Björn Borg | 11 | 5 | 1 | 4 | 4 | 1 | 1 | 0 | 27 | 31588 | 1170 |
| 17. | Maria Sharapova | 5 | 5 | 10 | 5 | 15 | 7 | 4 | 7 | 58 | 29947 | 516 |
| 18. | Stefan Edberg | 6 | 5 | 8 | 7 | 7 | 4 | 13 | 4 | 54 | 29719 | 550 |
| 19. | Justine Henin | 7 | 5 | 5 | 2 | 8 | 1 | 3 | 4 | 35 | 26794 | 766 |
| 20. | Daniil Medvedev | 1 | 5 | 3 | 2 | 7 | 4 | 3 | 11 | 36 | 13484 | 375 |
| 21. | Pete Sampras | 14 | 4 | 5 | 6 | 7 | 2 | 7 | 7 | 52 | 41286 | 794 |
| 22. | Monica Seles | 9 | 4 | 5 | 13 | 3 | 3 | 2 | 1 | 40 | 32971 | 824 |
| 23. | John McEnroe | 7 | 4 | 8 | 7 | 7 | 2 | 4 | 6 | 45 | 29747 | 661 |
| 24. | Billie Jean King | 8 | 4 | 5 | 11 | 1 | 2 | 0 | 1 | 32 | 29535 | 923 |
| 25. | Boris Becker | 6 | 4 | 8 | 5 | 8 | 5 | 5 | 5 | 46 | 27545 | 599 |
| 26. | Lindsay Davenport | 3 | 4 | 11 | 13 | 10 | 5 | 6 | 3 | 55 | 27413 | 498 |
| 27. | Mats Wilander | 7 | 4 | 3 | 6 | 6 | 5 | 8 | 5 | 44 | 25944 | 590 |
| 28. | Hana Mandlíková | 4 | 4 | 6 | 9 | 7 | 8 | 5 | 1 | 44 | 23705 | 539 |
| 29. | Kim Clijsters | 4 | 4 | 8 | 3 | 6 | 3 | 5 | 3 | 36 | 22095 | 614 |
| 30. | Guillermo Vilas | 4 | 4 | 4 | 7 | 8 | 7 | 6 | 9 | 49 | 21653 | 442 |
| 31. | Aryna Sabalenka | 4 | 4 | 6 | 2 | 3 | 4 | 4 | 5 | 32 | 19642 | 614 |
| 32. | Ken Rosewall | 4 | 4 | 5 | 2 | 4 | 3 | 1 | 0 | 23 | 18768 | 816 |
| 33. | Mary Pierce | 2 | 4 | 0 | 8 | 16 | 8 | 8 | 6 | 52 | 16924 | 325 |
| 34. | Andy Roddick | 1 | 4 | 5 | 9 | 5 | 9 | 6 | 7 | 46 | 16763 | 364 |
| 35. | Helena Suková | 0 | 4 | 3 | 11 | 13 | 10 | 9 | 11 | 61 | 16057 | 263 |
| 36. | Victoria Azarenka | 2 | 3 | 4 | 9 | 12 | 16 | 10 | 13 | 69 | 19295 | 280 |
| 37. | Jim Courier | 4 | 3 | 4 | 4 | 7 | 4 | 8 | 8 | 42 | 18784 | 447 |
| 38. | Jana Novotná | 1 | 3 | 5 | 13 | 9 | 8 | 4 | 7 | 50 | 17707 | 354 |
| 39. | Alexander Zverev | 1 | 3 | 7 | 6 | 7 | 8 | 4 | 5 | 41 | 16002 | 390 |
| 40. | Simona Halep | 2 | 3 | 4 | 7 | 6 | 3 | 8 | 13 | 46 | 15699 | 341 |
| 41. | Mary Joe Fernández | 0 | 3 | 6 | 8 | 11 | 13 | 2 | 5 | 48 | 15316 | 319 |
| 42. | Michael Chang | 1 | 3 | 4 | 5 | 7 | 9 | 16 | 12 | 57 | 14233 | 250 |
| 43. | Wendy Turnbull | 0 | 3 | 4 | 7 | 13 | 9 | 6 | 7 | 49 | 13653 | 279 |
| 44. | Goran Ivanišević | 1 | 3 | 3 | 7 | 5 | 9 | 9 | 14 | 51 | 13467 | 264 |
| 45. | Ilie Năstase | 2 | 3 | 1 | 6 | 5 | 7 | 10 | 9 | 43 | 13360 | 311 |
| 46. | Tony Roche | 0 | 3 | 5 | 4 | 5 | 4 | 2 | 2 | 25 | 10706 | 428 |
| 47. | Dominic Thiem | 1 | 3 | 2 | 2 | 7 | 2 | 7 | 13 | 37 | 10266 | 277 |
| 48. | Dinara Safina | 0 | 3 | 2 | 2 | 4 | 6 | 5 | 11 | 33 | 7940 | 241 |
| 49. | Ons Jabeur | 0 | 3 | 0 | 4 | 3 | 7 | 4 | 11 | 32 | 7072 | 221 |
| 50. | Casper Ruud | 0 | 3 | 1 | 0 | 4 | 5 | 11 | 5 | 29 | 6578 | 227 |
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.