| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 901. | Maria-Isabel Fernandez | 0 | 0 | 0 | 0 | 2 | 2 | 10 | 1 | 15 | 1230 | 82 |
| 902. | María Vento-Kabchi | 0 | 0 | 0 | 0 | 2 | 2 | 9 | 20 | 33 | 1362 | 41 |
| 903. | Marlene Weingärtner | 0 | 0 | 0 | 0 | 2 | 2 | 9 | 14 | 27 | 1302 | 48 |
| 904. | Petra Jauch-Delhees | 0 | 0 | 0 | 0 | 2 | 2 | 9 | 1 | 14 | 1172 | 84 |
| 905. | Mackenzie McDonald | 0 | 0 | 0 | 0 | 2 | 2 | 8 | 18 | 30 | 1284 | 43 |
| 906. | Andreas Maurer | 0 | 0 | 0 | 0 | 2 | 2 | 5 | 10 | 19 | 1030 | 54 |
| 907. | Szabolcs Baranyi | 0 | 0 | 0 | 0 | 2 | 2 | 5 | 3 | 12 | 960 | 80 |
| 908. | Olga Danilović | 0 | 0 | 0 | 0 | 2 | 2 | 5 | 2 | 11 | 950 | 86 |
| 909. | Daniel Altmaier | 0 | 0 | 0 | 0 | 2 | 2 | 4 | 13 | 21 | 1002 | 48 |
| 910. | Lilia Osterloh | 0 | 0 | 0 | 0 | 2 | 2 | 3 | 18 | 25 | 994 | 40 |
| 911. | Nicolás Jarry | 0 | 0 | 0 | 0 | 2 | 2 | 3 | 16 | 23 | 974 | 42 |
| 912. | Luciano Darderi | 0 | 0 | 0 | 0 | 2 | 2 | 3 | 4 | 11 | 854 | 78 |
| 913. | Laura Robson | 0 | 0 | 0 | 0 | 2 | 2 | 2 | 13 | 19 | 886 | 47 |
| 914. | Jo-Anne Faull | 0 | 0 | 0 | 0 | 2 | 2 | 2 | 8 | 14 | 836 | 60 |
| 915. | Kent Carlsson | 0 | 0 | 0 | 0 | 2 | 2 | 1 | 1 | 6 | 708 | 118 |
| 916. | Gianluca Pozzi | 0 | 0 | 0 | 0 | 2 | 1 | 17 | 20 | 40 | 1716 | 43 |
| 917. | Kristina Brandi | 0 | 0 | 0 | 0 | 2 | 1 | 12 | 20 | 35 | 1426 | 41 |
| 918. | Yoshihito Nishioka | 0 | 0 | 0 | 0 | 2 | 1 | 11 | 24 | 38 | 1408 | 37 |
| 919. | John Feaver | 0 | 0 | 0 | 0 | 2 | 1 | 9 | 17 | 29 | 1222 | 42 |
| 920. | Lindsey Beaven | 0 | 0 | 0 | 0 | 2 | 1 | 9 | 5 | 17 | 1102 | 65 |
| 921. | Simon Youl | 0 | 0 | 0 | 0 | 2 | 1 | 7 | 22 | 32 | 1156 | 36 |
| 922. | Sue Mappin | 0 | 0 | 0 | 0 | 2 | 1 | 7 | 3 | 13 | 966 | 74 |
| 923. | Lea Pericoli | 0 | 0 | 0 | 0 | 2 | 1 | 7 | 1 | 11 | 946 | 86 |
| 924. | Christian Saceanu | 0 | 0 | 0 | 0 | 2 | 1 | 6 | 9 | 18 | 968 | 54 |
| 925. | Mercedes Paz | 0 | 0 | 0 | 0 | 2 | 1 | 5 | 21 | 29 | 1030 | 36 |
| 926. | Regina Rajchrtová | 0 | 0 | 0 | 0 | 2 | 1 | 5 | 8 | 16 | 900 | 56 |
| 927. | Maria Teresa Nasuelli | 0 | 0 | 0 | 0 | 2 | 1 | 5 | 3 | 11 | 850 | 77 |
| 928. | Peter Doohan | 0 | 0 | 0 | 0 | 2 | 1 | 3 | 13 | 19 | 834 | 44 |
| 929. | Ilya Ivashka | 0 | 0 | 0 | 0 | 2 | 1 | 3 | 8 | 14 | 784 | 56 |
| 930. | Elina Avanesyan | 0 | 0 | 0 | 0 | 2 | 1 | 2 | 6 | 11 | 706 | 64 |
| 931. | Francesco Cancellotti | 0 | 0 | 0 | 0 | 2 | 1 | 2 | 3 | 8 | 676 | 85 |
| 932. | Leanne Harrison | 0 | 0 | 0 | 0 | 2 | 1 | 0 | 0 | 3 | 530 | 177 |
| 933. | Colin Dowdeswell | 0 | 0 | 0 | 0 | 2 | 0 | 9 | 15 | 26 | 1092 | 42 |
| 934. | Katarína Studeníková | 0 | 0 | 0 | 0 | 2 | 0 | 5 | 18 | 25 | 890 | 36 |
| 935. | Jil Teichmann | 0 | 0 | 0 | 0 | 2 | 0 | 5 | 13 | 20 | 840 | 42 |
| 936. | Kyōko Nagatsuka | 0 | 0 | 0 | 0 | 2 | 0 | 5 | 10 | 17 | 810 | 48 |
| 937. | Arnaud Di Pasquale | 0 | 0 | 0 | 0 | 2 | 0 | 3 | 11 | 16 | 704 | 44 |
| 938. | Janine Thompson | 0 | 0 | 0 | 0 | 2 | 0 | 3 | 8 | 13 | 674 | 52 |
| 939. | Edda Buding | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 3 | 478 | 159 |
| 940. | Steve Johnson | 0 | 0 | 0 | 0 | 1 | 10 | 11 | 19 | 41 | 2138 | 52 |
| 941. | Iva Budařová | 0 | 0 | 0 | 0 | 1 | 9 | 12 | 13 | 35 | 2026 | 58 |
| 942. | Alona Bondarenko | 0 | 0 | 0 | 0 | 1 | 9 | 5 | 12 | 27 | 1610 | 60 |
| 943. | Tathiana Garbin | 0 | 0 | 0 | 0 | 1 | 8 | 17 | 19 | 45 | 2266 | 50 |
| 944. | Shaun Stafford | 0 | 0 | 0 | 0 | 1 | 8 | 7 | 14 | 30 | 1636 | 55 |
| 945. | Ken Flach | 0 | 0 | 0 | 0 | 1 | 8 | 4 | 6 | 19 | 1382 | 73 |
| 946. | Kateřina Siniaková | 0 | 0 | 0 | 0 | 1 | 7 | 16 | 24 | 48 | 2148 | 45 |
| 947. | Émilie Loit | 0 | 0 | 0 | 0 | 1 | 7 | 15 | 18 | 41 | 2030 | 50 |
| 948. | Nicolas Mahut | 0 | 0 | 0 | 0 | 1 | 7 | 14 | 29 | 51 | 2082 | 41 |
| 949. | Ilana Kloss | 0 | 0 | 0 | 0 | 1 | 7 | 9 | 2 | 19 | 1522 | 80 |
| 950. | Isabelle Demongeot | 0 | 0 | 0 | 0 | 1 | 7 | 7 | 22 | 37 | 1606 | 43 |
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.