| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 401. | Francisco Clavet | 0 | 0 | 0 | 0 | 4 | 8 | 12 | 19 | 43 | 2170 | 50 |
| 402. | Christo van Rensburg | 0 | 0 | 0 | 0 | 4 | 7 | 6 | 6 | 23 | 1680 | 73 |
| 403. | John Fitzgerald | 0 | 0 | 0 | 0 | 4 | 6 | 13 | 21 | 44 | 2055 | 47 |
| 404. | Juan Mónaco | 0 | 0 | 0 | 0 | 4 | 5 | 9 | 26 | 44 | 1835 | 42 |
| 405. | Syd Ball | 0 | 0 | 0 | 0 | 4 | 5 | 9 | 10 | 28 | 1675 | 60 |
| 406. | Michaël Llodra | 0 | 0 | 0 | 0 | 4 | 3 | 16 | 29 | 52 | 2000 | 38 |
| 407. | Wayne Arthurs | 0 | 0 | 0 | 0 | 4 | 3 | 7 | 19 | 33 | 1495 | 45 |
| 408. | Bob Hewitt | 0 | 0 | 0 | 0 | 4 | 3 | 6 | 11 | 24 | 1370 | 57 |
| 409. | Francisco Cerúndolo | 0 | 0 | 0 | 0 | 4 | 3 | 5 | 8 | 20 | 1295 | 65 |
| 410. | Marcel Granollers | 0 | 0 | 0 | 0 | 4 | 2 | 21 | 17 | 44 | 2015 | 46 |
| 411. | Manuel Santana | 0 | 0 | 0 | 0 | 4 | 1 | 0 | 1 | 6 | 820 | 137 |
| 412. | Olivier Rochus | 0 | 0 | 0 | 0 | 3 | 8 | 11 | 26 | 48 | 2015 | 42 |
| 413. | Denis Istomin | 0 | 0 | 0 | 0 | 3 | 6 | 14 | 22 | 45 | 1930 | 43 |
| 414. | Pierre Barthès | 0 | 0 | 0 | 0 | 3 | 6 | 7 | 3 | 19 | 1425 | 75 |
| 415. | Buster Mottram | 0 | 0 | 0 | 0 | 3 | 6 | 6 | 6 | 21 | 1410 | 67 |
| 416. | Bernard Mitton | 0 | 0 | 0 | 0 | 3 | 6 | 3 | 13 | 25 | 1345 | 54 |
| 417. | Daniel Vacek | 0 | 0 | 0 | 0 | 3 | 5 | 8 | 17 | 33 | 1520 | 46 |
| 418. | Erik van Dillen | 0 | 0 | 0 | 0 | 3 | 5 | 6 | 17 | 31 | 1430 | 46 |
| 419. | Carlos Costa | 0 | 0 | 0 | 0 | 3 | 5 | 6 | 11 | 25 | 1370 | 55 |
| 420. | Carl-Uwe Steeb | 0 | 0 | 0 | 0 | 3 | 5 | 5 | 16 | 29 | 1375 | 47 |
| 421. | Jeff Borowiak | 0 | 0 | 0 | 0 | 3 | 4 | 10 | 13 | 30 | 1480 | 49 |
| 422. | Paradorn Srichaphan | 0 | 0 | 0 | 0 | 3 | 4 | 7 | 15 | 29 | 1365 | 47 |
| 423. | Cliff Letcher | 0 | 0 | 0 | 0 | 3 | 4 | 6 | 6 | 19 | 1230 | 65 |
| 424. | John Frawley | 0 | 0 | 0 | 0 | 3 | 4 | 2 | 6 | 15 | 1050 | 70 |
| 425. | Ugo Humbert | 0 | 0 | 0 | 0 | 3 | 3 | 7 | 18 | 31 | 1305 | 42 |
| 426. | Greg Holmes | 0 | 0 | 0 | 0 | 3 | 3 | 4 | 6 | 16 | 1050 | 66 |
| 427. | Jordan Thompson | 0 | 0 | 0 | 0 | 3 | 2 | 15 | 22 | 42 | 1615 | 38 |
| 428. | Scott Draper | 0 | 0 | 0 | 0 | 3 | 2 | 7 | 22 | 34 | 1255 | 37 |
| 429. | Dmitry Tursunov | 0 | 0 | 0 | 0 | 2 | 11 | 10 | 24 | 47 | 2040 | 43 |
| 430. | Dan Evans | 0 | 0 | 0 | 0 | 2 | 11 | 5 | 15 | 33 | 1725 | 52 |
| 431. | Leonardo Mayer | 0 | 0 | 0 | 0 | 2 | 9 | 10 | 18 | 39 | 1800 | 46 |
| 432. | Richard Fromberg | 0 | 0 | 0 | 0 | 2 | 8 | 12 | 23 | 45 | 1850 | 41 |
| 433. | Sargis Sargsian | 0 | 0 | 0 | 0 | 2 | 8 | 12 | 13 | 35 | 1750 | 50 |
| 434. | Jack Sock | 0 | 0 | 0 | 0 | 2 | 8 | 10 | 11 | 31 | 1640 | 53 |
| 435. | Albert Montañés | 0 | 0 | 0 | 0 | 2 | 8 | 8 | 35 | 53 | 1790 | 34 |
| 436. | Guillermo García López | 0 | 0 | 0 | 0 | 2 | 7 | 24 | 24 | 57 | 2310 | 41 |
| 437. | Taylor Dent | 0 | 0 | 0 | 0 | 2 | 7 | 8 | 10 | 27 | 1450 | 54 |
| 438. | Mikhail Kukushkin | 0 | 0 | 0 | 0 | 2 | 6 | 10 | 27 | 45 | 1620 | 36 |
| 439. | Jiří Veselý | 0 | 0 | 0 | 0 | 2 | 6 | 10 | 21 | 39 | 1560 | 40 |
| 440. | João Sousa | 0 | 0 | 0 | 0 | 2 | 6 | 9 | 21 | 38 | 1515 | 40 |
| 441. | Alexei Popyrin | 0 | 0 | 0 | 0 | 2 | 6 | 7 | 16 | 31 | 1375 | 44 |
| 442. | Thierry Tulasne | 0 | 0 | 0 | 0 | 2 | 6 | 7 | 13 | 28 | 1345 | 48 |
| 443. | Rolf Gehring | 0 | 0 | 0 | 0 | 2 | 6 | 1 | 7 | 16 | 1015 | 63 |
| 444. | Richey Reneberg | 0 | 0 | 0 | 0 | 2 | 5 | 15 | 24 | 46 | 1725 | 38 |
| 445. | Miomir Kecmanović | 0 | 0 | 0 | 0 | 2 | 5 | 12 | 12 | 31 | 1470 | 47 |
| 446. | Javier Frana | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 14 | 27 | 1220 | 45 |
| 447. | Brandon Nakashima | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 9 | 22 | 1170 | 53 |
| 448. | Terry Moor | 0 | 0 | 0 | 0 | 2 | 5 | 5 | 7 | 19 | 1105 | 58 |
| 449. | Nuno Borges | 0 | 0 | 0 | 0 | 2 | 5 | 4 | 8 | 19 | 1070 | 56 |
| 450. | Andrew Ilie | 0 | 0 | 0 | 0 | 2 | 5 | 3 | 12 | 22 | 1065 | 48 |
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.