| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1151. | Sara Sorribes Tormo | 0 | 0 | 0 | 0 | 1 | 1 | 11 | 17 | 30 | 1128 | 38 |
| 1152. | Jana Kandarr | 0 | 0 | 0 | 0 | 1 | 1 | 10 | 14 | 26 | 1040 | 40 |
| 1153. | Jared Palmer | 0 | 0 | 0 | 0 | 1 | 1 | 10 | 6 | 18 | 960 | 53 |
| 1154. | José Acasuso | 0 | 0 | 0 | 0 | 1 | 1 | 9 | 20 | 31 | 1042 | 34 |
| 1155. | Rossana de los Ríos | 0 | 0 | 0 | 0 | 1 | 1 | 8 | 17 | 27 | 954 | 35 |
| 1156. | Evgeniya Rodina | 0 | 0 | 0 | 0 | 1 | 1 | 8 | 16 | 26 | 944 | 36 |
| 1157. | Martina Suchá | 0 | 0 | 0 | 0 | 1 | 1 | 8 | 16 | 26 | 944 | 36 |
| 1158. | Wang Yafan | 0 | 0 | 0 | 0 | 1 | 1 | 8 | 9 | 19 | 874 | 46 |
| 1159. | Gilles Moretton | 0 | 0 | 0 | 0 | 1 | 1 | 8 | 7 | 17 | 854 | 50 |
| 1160. | Denisa Šátralová | 0 | 0 | 0 | 0 | 1 | 1 | 8 | 5 | 15 | 834 | 56 |
| 1161. | Federico Delbonis | 0 | 0 | 0 | 0 | 1 | 1 | 7 | 24 | 33 | 966 | 29 |
| 1162. | Jim McManus | 0 | 0 | 0 | 0 | 1 | 1 | 7 | 12 | 21 | 846 | 40 |
| 1163. | Dianne Van Rensburg | 0 | 0 | 0 | 0 | 1 | 1 | 7 | 10 | 19 | 826 | 43 |
| 1164. | Lloyd Bourne | 0 | 0 | 0 | 0 | 1 | 1 | 7 | 8 | 17 | 806 | 47 |
| 1165. | Patricia Medrado | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 19 | 27 | 858 | 32 |
| 1166. | Stéphane Robert | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 14 | 22 | 808 | 37 |
| 1167. | Hugo Gaston | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 13 | 21 | 798 | 38 |
| 1168. | Sabrina Goleš | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 13 | 21 | 798 | 38 |
| 1169. | Warren Maher | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 2 | 10 | 688 | 69 |
| 1170. | Daniela Porzio | 0 | 0 | 0 | 0 | 1 | 1 | 6 | 0 | 8 | 668 | 84 |
| 1171. | Misaki Doi | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 29 | 36 | 900 | 25 |
| 1172. | Grant Stafford | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 15 | 22 | 760 | 35 |
| 1173. | Leonardo Lavalle | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 13 | 20 | 740 | 37 |
| 1174. | Michael Tebbutt | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 11 | 18 | 720 | 40 |
| 1175. | Mike Leach | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 10 | 17 | 710 | 42 |
| 1176. | Cammy MacGregor | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 7 | 14 | 680 | 49 |
| 1177. | Raz Reid | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 6 | 13 | 670 | 52 |
| 1178. | María José Gaidano | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 4 | 11 | 650 | 59 |
| 1179. | Marjorie Blackwood | 0 | 0 | 0 | 0 | 1 | 1 | 5 | 2 | 9 | 630 | 70 |
| 1180. | Filippo Volandri | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 29 | 35 | 842 | 24 |
| 1181. | Wang Xiyu | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 11 | 17 | 662 | 39 |
| 1182. | Anna-Lena Friedsam | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 11 | 17 | 662 | 39 |
| 1183. | Ashlyn Krueger | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 9 | 15 | 642 | 43 |
| 1184. | Dick Norman | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 8 | 14 | 632 | 45 |
| 1185. | Alexander Mronz | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 8 | 14 | 632 | 45 |
| 1186. | Matt Doyle | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 8 | 14 | 632 | 45 |
| 1187. | Stefan Simonsson | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 8 | 14 | 632 | 45 |
| 1188. | Oscar Otte | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 6 | 12 | 612 | 51 |
| 1189. | Martin Laurendeau | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 6 | 12 | 612 | 51 |
| 1190. | Petra Huber | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 6 | 12 | 612 | 51 |
| 1191. | Robert Van't Hof | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 6 | 12 | 612 | 51 |
| 1192. | Dana Gilbert | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 6 | 12 | 612 | 51 |
| 1193. | Dale Collings | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 4 | 10 | 592 | 59 |
| 1194. | Peter Curtis | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 4 | 10 | 592 | 59 |
| 1195. | Christo Steyn | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 3 | 9 | 582 | 65 |
| 1196. | Veronica Burton | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 3 | 9 | 582 | 65 |
| 1197. | Sally Greer | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 2 | 8 | 572 | 72 |
| 1198. | Shirley Brasher | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 1 | 7 | 562 | 80 |
| 1199. | Viviana González | 0 | 0 | 0 | 0 | 1 | 1 | 4 | 0 | 6 | 552 | 92 |
| 1200. | Maureen Drake | 0 | 0 | 0 | 0 | 1 | 1 | 3 | 13 | 18 | 624 | 35 |
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.