| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 851. | Miomir Kecmanović | 0 | 0 | 0 | 0 | 2 | 5 | 12 | 12 | 31 | 1786 | 58 |
| 852. | Bethanie Mattek-Sands | 0 | 0 | 0 | 0 | 2 | 5 | 11 | 24 | 42 | 1848 | 44 |
| 853. | Åsa Svensson | 0 | 0 | 0 | 0 | 2 | 5 | 11 | 19 | 37 | 1798 | 49 |
| 854. | Alycia Moulton | 0 | 0 | 0 | 0 | 2 | 5 | 11 | 8 | 26 | 1688 | 65 |
| 855. | Monica Niculescu | 0 | 0 | 0 | 0 | 2 | 5 | 10 | 31 | 48 | 1860 | 39 |
| 856. | Radka Zrubáková | 0 | 0 | 0 | 0 | 2 | 5 | 10 | 22 | 39 | 1770 | 45 |
| 857. | Javier Frana | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 14 | 27 | 1458 | 54 |
| 858. | Laura Granville | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 13 | 26 | 1448 | 56 |
| 859. | Brandon Nakashima | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 9 | 22 | 1408 | 64 |
| 860. | Clara Tauson | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 8 | 21 | 1398 | 67 |
| 861. | Lita Liem Sugiarto | 0 | 0 | 0 | 0 | 2 | 5 | 6 | 4 | 17 | 1358 | 80 |
| 862. | Terry Moor | 0 | 0 | 0 | 0 | 2 | 5 | 5 | 7 | 19 | 1330 | 70 |
| 863. | Nuno Borges | 0 | 0 | 0 | 0 | 2 | 5 | 4 | 8 | 19 | 1282 | 67 |
| 864. | Andrew Ilie | 0 | 0 | 0 | 0 | 2 | 5 | 3 | 12 | 22 | 1264 | 57 |
| 865. | Bohdan Ulihrach | 0 | 0 | 0 | 0 | 2 | 4 | 14 | 16 | 36 | 1832 | 51 |
| 866. | Corentin Moutet | 0 | 0 | 0 | 0 | 2 | 4 | 11 | 13 | 30 | 1628 | 54 |
| 867. | Klára Koukalová | 0 | 0 | 0 | 0 | 2 | 4 | 10 | 34 | 50 | 1780 | 36 |
| 868. | Pam Casale | 0 | 0 | 0 | 0 | 2 | 4 | 9 | 6 | 21 | 1442 | 69 |
| 869. | Lele Forood | 0 | 0 | 0 | 0 | 2 | 4 | 9 | 6 | 21 | 1442 | 69 |
| 870. | Jeremy Bates | 0 | 0 | 0 | 0 | 2 | 4 | 8 | 22 | 36 | 1544 | 43 |
| 871. | Lee Hyung-taik | 0 | 0 | 0 | 0 | 2 | 4 | 8 | 15 | 29 | 1474 | 51 |
| 872. | Jarmila Wolfe | 0 | 0 | 0 | 0 | 2 | 4 | 7 | 22 | 35 | 1486 | 42 |
| 873. | Aravane Rezaï | 0 | 0 | 0 | 0 | 2 | 4 | 7 | 13 | 26 | 1396 | 54 |
| 874. | Andrei Olhovskiy | 0 | 0 | 0 | 0 | 2 | 4 | 7 | 11 | 24 | 1376 | 57 |
| 875. | Robert Seguso | 0 | 0 | 0 | 0 | 2 | 4 | 6 | 9 | 21 | 1298 | 62 |
| 876. | Marita Redondo | 0 | 0 | 0 | 0 | 2 | 4 | 6 | 5 | 17 | 1258 | 74 |
| 877. | Tomáš Macháč | 0 | 0 | 0 | 0 | 2 | 4 | 5 | 6 | 17 | 1210 | 71 |
| 878. | Matt Anger | 0 | 0 | 0 | 0 | 2 | 4 | 4 | 5 | 15 | 1142 | 76 |
| 879. | Nina Bohm | 0 | 0 | 0 | 0 | 2 | 4 | 2 | 2 | 10 | 996 | 100 |
| 880. | Dušan Lajović | 0 | 0 | 0 | 0 | 2 | 3 | 15 | 26 | 46 | 1880 | 41 |
| 881. | Ann Henricksson | 0 | 0 | 0 | 0 | 2 | 3 | 13 | 11 | 29 | 1614 | 56 |
| 882. | Iveta Benešová | 0 | 0 | 0 | 0 | 2 | 3 | 12 | 25 | 42 | 1696 | 40 |
| 883. | Olivier Delaître | 0 | 0 | 0 | 0 | 2 | 3 | 11 | 14 | 30 | 1528 | 51 |
| 884. | Daria Saville | 0 | 0 | 0 | 0 | 2 | 3 | 10 | 20 | 35 | 1530 | 44 |
| 885. | Donald Young | 0 | 0 | 0 | 0 | 2 | 3 | 9 | 22 | 36 | 1492 | 41 |
| 886. | Gala León García | 0 | 0 | 0 | 0 | 2 | 3 | 7 | 21 | 33 | 1366 | 41 |
| 887. | Petra Cetkovská | 0 | 0 | 0 | 0 | 2 | 3 | 7 | 11 | 23 | 1266 | 55 |
| 888. | Ginger Helgeson-Nielsen | 0 | 0 | 0 | 0 | 2 | 3 | 7 | 10 | 22 | 1256 | 57 |
| 889. | Milan Holeček | 0 | 0 | 0 | 0 | 2 | 3 | 7 | 9 | 21 | 1246 | 59 |
| 890. | Alisa Kleybanova | 0 | 0 | 0 | 0 | 2 | 3 | 7 | 4 | 16 | 1196 | 75 |
| 891. | Teymuraz Gabashvili | 0 | 0 | 0 | 0 | 2 | 3 | 6 | 21 | 32 | 1308 | 41 |
| 892. | Teimuraz Kakulia | 0 | 0 | 0 | 0 | 2 | 3 | 6 | 5 | 16 | 1148 | 72 |
| 893. | Hana Strachoňová | 0 | 0 | 0 | 0 | 2 | 3 | 6 | 3 | 14 | 1128 | 81 |
| 894. | Ian Fletcher | 0 | 0 | 0 | 0 | 2 | 3 | 6 | 2 | 13 | 1118 | 86 |
| 895. | Nick Saviano | 0 | 0 | 0 | 0 | 2 | 3 | 4 | 12 | 21 | 1102 | 52 |
| 896. | Damir Keretić | 0 | 0 | 0 | 0 | 2 | 3 | 3 | 7 | 15 | 994 | 66 |
| 897. | Betty Ann Grubb Stuart | 0 | 0 | 0 | 0 | 2 | 3 | 3 | 3 | 11 | 954 | 87 |
| 898. | Denise Carter | 0 | 0 | 0 | 0 | 2 | 3 | 2 | 1 | 8 | 876 | 110 |
| 899. | Marilyn Tesch | 0 | 0 | 0 | 0 | 2 | 3 | 1 | 0 | 6 | 808 | 135 |
| 900. | Gerald Battrick | 0 | 0 | 0 | 0 | 2 | 2 | 10 | 8 | 22 | 1300 | 59 |
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.