| # | Player | W | F | S | Q | R16 | R32 | R64 | R128 | APPS | PTS | PTS/APP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 251. | Magüi Serna | 0 | 0 | 0 | 1 | 5 | 7 | 10 | 10 | 33 | 3340 | 101 |
| 252. | Yayuk Basuki | 0 | 0 | 0 | 1 | 5 | 6 | 6 | 13 | 31 | 2960 | 95 |
| 253. | Karina Habšudová | 0 | 0 | 0 | 1 | 5 | 5 | 14 | 17 | 42 | 3430 | 82 |
| 254. | Candy Reynolds | 0 | 0 | 0 | 1 | 5 | 0 | 10 | 11 | 27 | 2440 | 90 |
| 255. | Anne Minter | 0 | 0 | 0 | 1 | 4 | 11 | 13 | 15 | 44 | 3880 | 88 |
| 256. | Naoko Sawamatsu | 0 | 0 | 0 | 1 | 4 | 9 | 13 | 7 | 34 | 3540 | 104 |
| 257. | Anett Kontaveit | 0 | 0 | 0 | 1 | 4 | 7 | 7 | 14 | 33 | 2930 | 89 |
| 258. | Leila Meshki | 0 | 0 | 0 | 1 | 4 | 7 | 3 | 8 | 23 | 2590 | 113 |
| 259. | Lesia Tsurenko | 0 | 0 | 0 | 1 | 4 | 6 | 10 | 25 | 46 | 3120 | 68 |
| 260. | Mona Schallau | 0 | 0 | 0 | 1 | 4 | 5 | 5 | 1 | 16 | 2400 | 150 |
| 261. | Liudmila Samsonova | 0 | 0 | 0 | 1 | 4 | 4 | 7 | 9 | 25 | 2490 | 100 |
| 262. | Laura duPont | 0 | 0 | 0 | 1 | 3 | 10 | 11 | 9 | 34 | 3310 | 97 |
| 263. | Camila Giorgi | 0 | 0 | 0 | 1 | 3 | 9 | 14 | 19 | 46 | 3490 | 76 |
| 264. | Patricia Hy-Boulais | 0 | 0 | 0 | 1 | 3 | 8 | 15 | 14 | 41 | 3380 | 82 |
| 265. | Meghann Shaughnessy | 0 | 0 | 0 | 1 | 3 | 7 | 11 | 18 | 40 | 3010 | 75 |
| 266. | Christina Sandberg | 0 | 0 | 0 | 1 | 3 | 7 | 6 | 3 | 20 | 2510 | 126 |
| 267. | Lisa Bonder | 0 | 0 | 0 | 1 | 3 | 7 | 5 | 8 | 24 | 2490 | 104 |
| 268. | Laura Arraya | 0 | 0 | 0 | 1 | 3 | 6 | 13 | 11 | 34 | 2950 | 87 |
| 269. | Fiorella Bonicelli | 0 | 0 | 0 | 1 | 3 | 6 | 9 | 5 | 24 | 2610 | 109 |
| 270. | Alison Riske-Amritraj | 0 | 0 | 0 | 1 | 3 | 6 | 6 | 28 | 44 | 2630 | 60 |
| 271. | Hsieh Su-wei | 0 | 0 | 0 | 1 | 3 | 4 | 14 | 19 | 41 | 2840 | 69 |
| 272. | Michèle Gurdal | 0 | 0 | 0 | 1 | 3 | 3 | 8 | 8 | 23 | 2180 | 95 |
| 273. | Pascale Paradis | 0 | 0 | 0 | 1 | 3 | 3 | 6 | 20 | 33 | 2160 | 65 |
| 274. | Marise Kruger | 0 | 0 | 0 | 1 | 3 | 1 | 2 | 2 | 9 | 1440 | 160 |
| 275. | Elizabeth Smylie | 0 | 0 | 0 | 1 | 2 | 8 | 9 | 23 | 43 | 2810 | 65 |
| 276. | JoAnne Russell | 0 | 0 | 0 | 1 | 2 | 6 | 7 | 11 | 27 | 2290 | 85 |
| 277. | Eva Pfaff | 0 | 0 | 0 | 1 | 2 | 4 | 11 | 19 | 37 | 2390 | 65 |
| 278. | Marie Bouzková | 0 | 0 | 0 | 1 | 2 | 4 | 8 | 15 | 30 | 2140 | 71 |
| 279. | Veronika Kudermetova | 0 | 0 | 0 | 1 | 2 | 4 | 6 | 13 | 26 | 1980 | 76 |
| 280. | Sabine Hack | 0 | 0 | 0 | 1 | 2 | 4 | 6 | 13 | 26 | 1980 | 76 |
| 281. | Tatiana Golovin | 0 | 0 | 0 | 1 | 2 | 4 | 4 | 6 | 17 | 1770 | 104 |
| 282. | Linda Tuero | 0 | 0 | 0 | 1 | 2 | 4 | 3 | 2 | 12 | 1660 | 138 |
| 283. | Barbara Hawcroft | 0 | 0 | 0 | 1 | 2 | 4 | 1 | 0 | 8 | 1500 | 188 |
| 284. | Shinobu Asagoe | 0 | 0 | 0 | 1 | 2 | 3 | 6 | 13 | 25 | 1850 | 74 |
| 285. | Elena Bovina | 0 | 0 | 0 | 1 | 2 | 3 | 6 | 7 | 19 | 1790 | 94 |
| 286. | Kathleen Harter | 0 | 0 | 0 | 1 | 2 | 3 | 5 | 5 | 16 | 1700 | 106 |
| 287. | Sybille Bammer | 0 | 0 | 0 | 1 | 2 | 2 | 8 | 11 | 24 | 1840 | 77 |
| 288. | Lucia Romanov-Stark | 0 | 0 | 0 | 1 | 2 | 2 | 4 | 6 | 15 | 1510 | 101 |
| 289. | Dája Bedáňová | 0 | 0 | 0 | 1 | 2 | 2 | 3 | 6 | 14 | 1440 | 103 |
| 290. | Naoko Sato | 0 | 0 | 0 | 1 | 2 | 2 | 3 | 3 | 11 | 1410 | 128 |
| 291. | Patricia Coleman | 0 | 0 | 0 | 1 | 2 | 2 | 3 | 0 | 8 | 1380 | 173 |
| 292. | Ágnes Szávay | 0 | 0 | 0 | 1 | 2 | 1 | 6 | 7 | 17 | 1530 | 90 |
| 293. | Jan Lehane | 0 | 0 | 0 | 1 | 2 | 1 | 0 | 0 | 4 | 1040 | 260 |
| 294. | Odile de Roubin | 0 | 0 | 0 | 1 | 2 | 0 | 6 | 6 | 15 | 1390 | 93 |
| 295. | Kathy Kuykendall | 0 | 0 | 0 | 1 | 2 | 0 | 3 | 0 | 6 | 1120 | 187 |
| 296. | Cynthia Doerner | 0 | 0 | 0 | 1 | 1 | 9 | 9 | 3 | 23 | 2500 | 109 |
| 297. | Kimberly Po | 0 | 0 | 0 | 1 | 1 | 9 | 7 | 11 | 29 | 2440 | 84 |
| 298. | Cecilia Martinez | 0 | 0 | 0 | 1 | 1 | 9 | 5 | 1 | 17 | 2200 | 129 |
| 299. | Alicia Molik | 0 | 0 | 0 | 1 | 1 | 8 | 10 | 19 | 39 | 2600 | 67 |
| 300. | Terry Phelps | 0 | 0 | 0 | 1 | 1 | 7 | 7 | 11 | 27 | 2180 | 81 |
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.