Serena Williams versus the field: it’s a refrain that’s held true pretty much the whole year. I had that written down before Maria Sharapova withdrew, so now that there’s one less serious contender, the U.S. Open should be even more of a cakewalk for Serena, right? Not exactly; Sharapova’s withdrawal has caused some interesting ripple effects.
2013 U.S. Open Women’s Preview: Victoria Azarenka might be your tournament favorite
Maria Sharapova’s withdrawal has caused some unanticipated effects, including a prediction not seen all year. Tournament forecasts, draw analysis, and favorite bets below.
US PRESSWIRE
Tennis players are disproportionately judged by how well they do at Slams. That’s understandable since they’re the four times during the year when casual sports fans actually watch, but that belies the fact that Slams are hardly equal tests of skill from year to year. Andy Murray got praised for getting the monkey off his back this time a year ago, but wasn’t he helped by Rafael Nadal’s absence? Or how about the 2011 French Open: Na Li won her only slam to date, but will anyone remember that it was a Serena-less field?
This isn’t to say that certain titles deserve asterisks or something silly like that, but it is a reminder that both the quality of the field and the layout of the draw influence the tournament and deserve some consideration. And for this year’s U.S. Open, factoring in both reveals two really interesting considerations.
1. There will probably be a breakout semifinal run from a player outside the top 10.
2. For the first time all year, Serena Williams is not a clear-cut favorite.
Year in Review: Tracking the Top Four
Below is a 52-week tracking graph of the hard-adjusted Advanced Baseline ranks of the top four players from last year’s U.S. Open until now. It’s a quick way to see what’s changed at the top of the ladder, and how it might cause things to be different this year. (click to enlarge)
As dominant as Serena has been in 2013, it’s easy to forget she hasn’t always been this far ahead of the pack. Victoria Azarenka won the Australian Open in January while Serena lost to Sloane Stephens in the quarterfinals, and Azarenka won Doha by beating Serena in the final. It’s only in the last four months that Serena has gotten her separation from Azarenka and Sharapova, and a close loss to Azarenka in Cincinnati can’t single-handedly undermine the rankings gulf that developed this summer.
Meanwhile, the other two lines on that graph show how far behind the rest of the draw is. Neither Agnieszka Radwanska nor Na Li has shown all that much consistency this year, so they’re hardly a lock to get to their quarterfinal matchup against one another. And that’s to say nothing of the Sara Errani/Caroline Wozniacki quarter. I would bet a lot on that matchup failing to take shape; at least one of them will probably lose in the first four rounds.
Forecast and Draw Analysis
Generated from simulating the tournament 100,000 times before the tournament began, using win probabilities from AB ratings. Full explanation for calculating luck of the draw can be found here.
| Player | Round 2 | Round 3 | Round 4 | QF | SF | Finals | Winner | Expected Points | Change in Expected Points from Draw |
| Victoria Azarenka | 98.1% | 94.2% | 90.1% | 83.6% | 75.5% | 66.6% | 38.8% | 1220.4 | 66.5 |
| Serena Williams | 95.3% | 90.4% | 84.9% | 78.5% | 71.0% | 57.1% | 38.5% | 1139.4 | -32.7 |
| Na Li | 94.8% | 84.9% | 76.5% | 62.9% | 40.4% | 15.5% | 6.7% | 536.5 | 57.3 |
| Aga Radwanska | 93.9% | 85.7% | 75.6% | 61.4% | 37.2% | 14.7% | 5.9% | 511.4 | -21.7 |
| Simona Halep | 88.7% | 78.6% | 58.8% | 39.6% | 25.7% | 7.5% | 2.1% | 345.7 | 84.7 |
| Caroline Wozniacki | 84.3% | 69.3% | 53.6% | 34.6% | 19.3% | 4.9% | 1.1% | 283.3 | 20.6 |
| Samantha Stosur | 92.1% | 73.9% | 56.6% | 37.2% | 8.5% | 4.7% | 1.2% | 256.5 | 21.3 |
| Angelique Kerber | 89.5% | 73.3% | 52.8% | 34.5% | 8.0% | 2.8% | 0.7% | 231.4 | 8.1 |
| Roberta Vinci | 83.9% | 63.2% | 41.6% | 23.7% | 11.7% | 2.5% | 0.5% | 205.7 | 24.2 |
| Sara Errani | 74.9% | 57.4% | 41.1% | 22.2% | 12.8% | 3.1% | 0.7% | 205.1 | -60.8 |
| Venus Williams | 69.7% | 55.4% | 40.7% | 23.9% | 5.3% | 1.9% | 0.4% | 170.6 | 24.0 |
| Elena Vesnina | 80.2% | 61.5% | 33.1% | 17.5% | 7.9% | 1.2% | 0.2% | 162.7 | 22.2 |
| Ekaterina Makarova | 75.0% | 59.2% | 40.6% | 15.5% | 5.6% | 1.4% | 0.3% | 156.9 | -10.7 |
| Maria Kirilenko | 74.5% | 61.2% | 26.6% | 14.0% | 7.0% | 1.3% | 0.3% | 146.1 | 2.5 |
| Petra Kvitova | 86.1% | 48.4% | 30.8% | 15.7% | 2.8% | 1.3% | 0.2% | 135.9 | -50.8 |
| Jelena Jankovic | 63.7% | 51.5% | 35.4% | 12.5% | 4.9% | 1.1% | 0.3% | 134.7 | -42.2 |
| Jamie Hampton | 84.3% | 65.2% | 39.1% | 6.4% | 3.4% | 0.9% | 0.2% | 134.1 | -2.5 |
| Mona Barthel | 81.6% | 63.2% | 30.2% | 13.8% | 1.8% | 0.6% | 0.1% | 129.4 | 15.5 |
| Sorana Cirstea | 79.3% | 61.0% | 31.7% | 9.2% | 3.1% | 0.6% | 0.1% | 124.9 | 5.8 |
| Ana Ivanovic | 81.1% | 56.3% | 36.0% | 5.7% | 2.9% | 1.2% | 0.3% | 124.8 | -28.8 |
| Sloane Stephens | 88.3% | 61.6% | 35.9% | 5.8% | 2.5% | 0.7% | 0.1% | 124.3 | 6.9 |
| Andrea Petkovic | 80.0% | 44.1% | 28.2% | 13.8% | 2.2% | 1.0% | 0.2% | 122.3 | 10.5 |
| Svetlana Kuznetsova | 75.8% | 51.3% | 24.1% | 10.4% | 4.8% | 0.7% | 0.1% | 121.7 | 9.7 |
| Dominika Cibulkova | 78.3% | 58.0% | 31.8% | 4.6% | 2.1% | 0.8% | 0.1% | 112.7 | -22.4 |
| Sabine Lisicki | 70.0% | 53.1% | 27.8% | 8.2% | 2.2% | 0.5% | 0.1% | 108.9 | -2.3 |
| Carla Suarez Navarro | 72.5% | 53.3% | 23.9% | 10.3% | 1.7% | 0.3% | 0.0% | 107.2 | 3.2 |
| Nadia Petrova | 73.7% | 51.7% | 20.2% | 9.7% | 1.4% | 0.5% | 0.1% | 103.1 | -10.0 |
| Kaia Kanepi | 60.3% | 45.0% | 20.9% | 11.3% | 2.3% | 0.7% | 0.1% | 102.2 | -8.0 |
| Klara Zakopalova | 64.5% | 47.6% | 19.1% | 8.1% | 2.7% | 0.4% | 0.1% | 97.6 | 8.7 |
| Magdalena Rybarikova | 88.6% | 60.5% | 7.9% | 4.0% | 1.8% | 0.4% | 0.1% | 91.5 | -15.7 |
| Anastasia Pavlyuchenkova | 63.9% | 51.2% | 11.9% | 5.4% | 1.3% | 0.3% | 0.0% | 81.9 | -1.0 |
| Laura Robson | 68.5% | 52.0% | 10.6% | 4.8% | 1.3% | 0.2% | 0.0% | 81.9 | -0.1 |
| Shuai Peng | 72.9% | 32.2% | 11.1% | 3.4% | 1.4% | 0.1% | 0.0% | 71.6 | 16.3 |
| Varvara Lepchenko | 76.4% | 32.1% | 15.4% | 1.5% | 0.6% | 0.2% | 0.0% | 71.2 | 7.5 |
| Flavia Pennetta | 71.5% | 23.7% | 11.8% | 3.7% | 1.5% | 0.2% | 0.0% | 69.2 | 9.0 |
| Mirjana Lucic-Baroni | 79.5% | 32.6% | 8.4% | 2.5% | 0.2% | 0.1% | 0.0% | 65.5 | 22.2 |
| Daniela Hantuchova | 75.6% | 21.0% | 10.6% | 4.2% | 0.4% | 0.2% | 0.1% | 65.5 | 9.5 |
| Lucie Safarova | 65.2% | 22.5% | 10.8% | 4.1% | 1.1% | 0.2% | 0.0% | 64.7 | 11.0 |
| Chanelle Scheepers | 76.4% | 20.4% | 9.6% | 3.4% | 0.8% | 0.1% | 0.0% | 64.1 | 18.7 |
| Alize Cornet | 69.8% | 43.7% | 3.8% | 1.6% | 0.5% | 0.1% | 0.0% | 63.0 | -14.9 |
| Urszula Radwanska | 69.0% | 27.6% | 12.2% | 1.6% | 0.5% | 0.1% | 0.0% | 62.6 | 12.0 |
| Bethanie Mattek-Sands | 74.9% | 22.9% | 9.8% | 2.0% | 0.3% | 0.0% | 0.0% | 60.4 | 16.1 |
| Madison Keys | 36.3% | 26.3% | 14.5% | 3.7% | 1.1% | 0.2% | 0.0% | 59.0 | -9.2 |
| Yaroslava Shvedova | 74.7% | 31.5% | 3.1% | 1.4% | 0.5% | 0.1% | 0.0% | 57.7 | 4.1 |
| Coco Vandeweghe | 64.8% | 23.8% | 7.4% | 2.0% | 0.2% | 0.0% | 0.0% | 54.5 | 16.6 |
| Vania King | 39.7% | 25.7% | 9.6% | 4.1% | 0.5% | 0.1% | 0.0% | 53.9 | -4.7 |
| Petra Cetkovska | 67.5% | 10.5% | 6.6% | 2.9% | 0.9% | 0.1% | 0.0% | 53.2 | -8.4 |
| Kimiko Date-Krumm | 65.0% | 22.1% | 7.6% | 1.4% | 0.2% | 0.0% | 0.0% | 52.8 | 14.1 |
| Eugenie Bouchard | 64.2% | 16.6% | 6.9% | 2.6% | 0.3% | 0.1% | 0.0% | 52.0 | 7.9 |
| Kirsten Flipkens | 30.4% | 19.4% | 11.1% | 4.1% | 0.7% | 0.2% | 0.0% | 50.0 | -49.5 |
| Jie Zheng | 57.7% | 15.6% | 7.4% | 2.2% | 0.3% | 0.0% | 0.0% | 49.2 | 5.7 |
| Monica Puig | 65.1% | 16.9% | 6.5% | 1.1% | 0.2% | 0.0% | 0.0% | 48.9 | 10.5 |
| Donna Vekic | 70.3% | 12.4% | 4.6% | 1.3% | 0.4% | 0.0% | 0.0% | 48.1 | 9.8 |
| Kurumi Nara | 58.5% | 18.3% | 5.6% | 0.9% | 0.1% | 0.0% | 0.0% | 45.7 | 11.9 |
| Aleksandra Wozniak | 78.7% | 4.7% | 2.5% | 1.0% | 0.4% | 0.1% | 0.0% | 45.6 | -4.5 |
| Camila Giorgi | 56.9% | 18.4% | 4.7% | 1.1% | 0.2% | 0.1% | 0.0% | 45.5 | 11.7 |
| Su-wei Hsieh | 35.5% | 22.3% | 6.9% | 2.1% | 0.4% | 0.0% | 0.0% | 44.0 | 1.3 |
| Stefanie Voegele | 54.0% | 16.6% | 4.4% | 1.5% | 0.2% | 0.0% | 0.0% | 43.6 | 6.9 |
| Alison Riske | 55.5% | 17.4% | 4.2% | 1.0% | 0.1% | 0.0% | 0.0% | 43.3 | 6.6 |
| Marina Erakovic | 63.1% | 8.4% | 3.8% | 1.3% | 0.3% | 0.0% | 0.0% | 42.8 | 3.2 |
| Kristina Mladenovic | 53.2% | 16.7% | 5.4% | 0.4% | 0.1% | 0.0% | 0.0% | 42.1 | 6.7 |
| Christina McHale | 51.2% | 16.4% | 5.5% | 0.4% | 0.2% | 0.0% | 0.0% | 41.8 | 1.7 |
| Michelle Larcher de Brito | 58.6% | 14.9% | 3.0% | 0.6% | 0.2% | 0.0% | 0.0% | 41.7 | 9.1 |
| Casey Dellacqua | 52.7% | 23.6% | 1.5% | 0.4% | 0.1% | 0.0% | 0.0% | 41.6 | 0.7 |
| Grace Min | 51.4% | 15.6% | 4.0% | 1.2% | 0.2% | 0.0% | 0.0% | 41.6 | 6.5 |
| Monica Niculescu | 66.3% | 5.1% | 2.2% | 1.0% | 0.4% | 0.1% | 0.0% | 41.0 | -15.2 |
| Virginie Razzano | 36.2% | 25.3% | 4.3% | 1.3% | 0.1% | 0.0% | 0.0% | 40.8 | -1.4 |
| Julia Goerges | 48.9% | 15.8% | 5.3% | 0.3% | 0.1% | 0.0% | 0.0% | 40.0 | 0.3 |
| Karin Knapp | 48.6% | 14.3% | 3.9% | 1.1% | 0.2% | 0.0% | 0.0% | 39.9 | 5.2 |
| Shelby Rogers | 56.0% | 16.9% | 1.4% | 0.3% | 0.0% | 0.0% | 0.0% | 39.2 | 10.7 |
| Ayumi Morita | 25.1% | 13.7% | 6.7% | 2.1% | 0.9% | 0.1% | 0.0% | 38.6 | -16.3 |
| Ajla Tomljanovic | 47.3% | 19.8% | 1.2% | 0.3% | 0.1% | 0.0% | 0.0% | 37.3 | 0.9 |
| Ashleigh Barty | 54.4% | 13.3% | 1.5% | 0.3% | 0.0% | 0.0% | 0.0% | 37.1 | 11.8 |
| Karolina Anna Schmiedlova | 46.0% | 12.7% | 2.8% | 0.7% | 0.1% | 0.0% | 0.0% | 35.9 | 3.7 |
| Vera Dushevina | 30.0% | 17.3% | 5.8% | 1.0% | 0.1% | 0.0% | 0.0% | 35.8 | -4.8 |
| Anabel Medina Garrigues | 46.8% | 12.4% | 3.7% | 0.2% | 0.0% | 0.0% | 0.0% | 35.6 | 4.6 |
| Polona Hercog | 25.0% | 14.3% | 6.2% | 1.3% | 0.3% | 0.0% | 0.0% | 34.4 | -10.4 |
| Kiki Bertens | 42.3% | 9.6% | 3.7% | 0.9% | 0.1% | 0.0% | 0.0% | 34.4 | -1.5 |
| Tsvetana Pironkova | 44.5% | 11.5% | 2.5% | 0.5% | 0.0% | 0.0% | 0.0% | 34.1 | 2.8 |
| Jana Cepelova | 43.1% | 11.8% | 2.4% | 0.5% | 0.1% | 0.0% | 0.0% | 33.7 | 5.0 |
| Lourdes Dominguez-Lino | 31.5% | 18.5% | 2.0% | 0.5% | 0.1% | 0.0% | 0.0% | 32.6 | -2.0 |
| Lauren Davis | 27.5% | 14.6% | 4.2% | 1.1% | 0.1% | 0.0% | 0.0% | 32.2 | -1.8 |
| Caroline Garcia | 44.0% | 12.5% | 0.9% | 0.2% | 0.0% | 0.0% | 0.0% | 32.2 | 6.6 |
| Alexandra Cadantu | 41.5% | 10.8% | 2.3% | 0.2% | 0.0% | 0.0% | 0.0% | 31.9 | 4.5 |
| Estrella Cabeza-Candela | 45.6% | 10.2% | 0.9% | 0.2% | 0.0% | 0.0% | 0.0% | 31.8 | 8.2 |
| Yanina Wickmayer | 25.5% | 15.7% | 3.4% | 0.9% | 0.3% | 0.0% | 0.0% | 31.8 | -9.4 |
| Lesya Tsurenko | 34.8% | 7.9% | 2.7% | 0.7% | 0.1% | 0.0% | 0.0% | 29.8 | -3.9 |
| Eleni Daniilidou | 41.4% | 8.1% | 1.2% | 0.2% | 0.0% | 0.0% | 0.0% | 29.6 | 3.6 |
| Julia Glushko | 26.3% | 12.8% | 2.4% | 0.6% | 0.0% | 0.0% | 0.0% | 28.4 | -4.0 |
| Karolina Pliskova | 35.9% | 6.2% | 1.8% | 0.5% | 0.1% | 0.0% | 0.0% | 28.4 | -1.1 |
| Aleksandra Krunic | 35.2% | 8.4% | 1.6% | 0.3% | 0.1% | 0.0% | 0.0% | 28.2 | 3.3 |
| Maria Joao Koehler | 30.2% | 12.9% | 0.6% | 0.2% | 0.1% | 0.0% | 0.0% | 27.4 | -4.0 |
| Paula Ormaechea | 35.0% | 7.5% | 1.5% | 0.2% | 0.0% | 0.0% | 0.0% | 27.4 | 1.4 |
| Irina-Camelia Begu | 31.1% | 7.8% | 2.1% | 0.2% | 0.0% | 0.0% | 0.0% | 26.6 | -2.3 |
| Maria-Teresa Torro-Flor | 36.9% | 3.8% | 1.3% | 0.3% | 0.0% | 0.0% | 0.0% | 26.4 | -1.3 |
| Mallory Burdette | 24.2% | 9.6% | 2.4% | 0.5% | 0.1% | 0.0% | 0.0% | 26.3 | -8.0 |
| Alisa Kleybanova | 34.9% | 5.3% | 1.5% | 0.1% | 0.0% | 0.0% | 0.0% | 26.3 | 0.7 |
| Elina Svitolina | 21.8% | 9.8% | 3.1% | 0.2% | 0.0% | 0.0% | 0.0% | 25.4 | -9.4 |
| Sofia Arvidsson | 32.5% | 2.8% | 1.2% | 0.4% | 0.1% | 0.0% | 0.0% | 24.7 | -8.4 |
| Sharon Fichman | 20.8% | 9.9% | 2.5% | 0.3% | 0.1% | 0.0% | 0.0% | 24.7 | -4.6 |
| Yvonne Meusburger | 27.2% | 6.9% | 1.4% | 0.3% | 0.0% | 0.0% | 0.0% | 24.5 | -2.1 |
| Nicole Gibbs | 28.5% | 5.2% | 1.4% | 0.3% | 0.1% | 0.0% | 0.0% | 24.4 | -6.9 |
| Annika Beck | 19.8% | 8.7% | 2.2% | 0.6% | 0.1% | 0.0% | 0.0% | 24.0 | -6.7 |
| Ying-Ying Duan | 15.7% | 7.6% | 3.1% | 0.9% | 0.2% | 0.0% | 0.0% | 24.0 | -12.0 |
| Galina Voskoboeva | 33.7% | 2.1% | 0.6% | 0.1% | 0.0% | 0.0% | 0.0% | 23.7 | -10.6 |
| Mariana Duque-Marino | 29.7% | 2.8% | 0.6% | 0.1% | 0.0% | 0.0% | 0.0% | 22.4 | 0.1 |
| Johanna Larsson | 18.4% | 8.0% | 1.7% | 0.3% | 0.0% | 0.0% | 0.0% | 22.1 | -6.0 |
| Bojana Jovanovski | 20.0% | 5.1% | 1.9% | 0.3% | 0.0% | 0.0% | 0.0% | 21.7 | -12.9 |
| Alexandra Dulgheru | 23.6% | 4.9% | 1.1% | 0.1% | 0.0% | 0.0% | 0.0% | 21.7 | -4.7 |
| Olga Puchkova | 25.3% | 5.2% | 0.3% | 0.1% | 0.0% | 0.0% | 0.0% | 21.6 | -3.5 |
| Anna Tatishvili | 18.9% | 6.7% | 1.8% | 0.1% | 0.0% | 0.0% | 0.0% | 21.5 | -10.4 |
| Mathilde Johansson | 25.1% | 3.5% | 0.8% | 0.1% | 0.0% | 0.0% | 0.0% | 21.3 | -1.1 |
| Timea Babos | 16.1% | 6.3% | 1.9% | 0.5% | 0.0% | 0.0% | 0.0% | 21.1 | -10.8 |
| Maria Sanchez | 24.4% | 2.8% | 0.9% | 0.2% | 0.0% | 0.0% | 0.0% | 20.9 | -4.6 |
| Chanel Simmonds | 23.6% | 2.8% | 0.7% | 0.1% | 0.0% | 0.0% | 0.0% | 20.3 | -0.7 |
| Heather Watson | 11.3% | 6.3% | 2.0% | 0.4% | 0.1% | 0.0% | 0.0% | 19.5 | -14.0 |
| Lara Arruabarrena-Vecino | 15.7% | 5.7% | 1.0% | 0.1% | 0.0% | 0.0% | 0.0% | 19.1 | -5.0 |
| Sachia Vickery | 20.5% | 2.9% | 0.4% | 0.1% | 0.0% | 0.0% | 0.0% | 18.9 | 0.5 |
| Vesna Dolonc | 21.3% | 0.5% | 0.1% | 0.0% | 0.0% | 0.0% | 0 | 17.8 | -2.6 |
| Misaki Doi | 13.9% | 2.4% | 0.6% | 0.1% | 0.0% | 0.0% | 0.0% | 16.7 | -8.0 |
| Lucie Hradecka | 10.5% | 3.9% | 0.9% | 0.2% | 0.0% | 0.0% | 0.0% | 16.6 | -8.5 |
| Mandy Minella | 11.7% | 3.1% | 0.6% | 0.0% | 0.0% | 0.0% | 0.0% | 16.0 | -4.3 |
| Patricia Mayr-Achleitner | 11.4% | 2.8% | 0.1% | 0.0% | 0.0% | 0.0% | 0.0% | 15.4 | -5.2 |
| Victoria Duval | 7.9% | 2.3% | 0.6% | 0.1% | 0.0% | 0.0% | 0.0% | 14.6 | -8.6 |
| Francesca Schiavone | 4.7% | 2.3% | 0.9% | 0.3% | 0.1% | 0.0% | 0.0% | 14.2 | -24.7 |
| Silvia Soler-Espinosa | 6.1% | 2.1% | 0.7% | 0.1% | 0.0% | 0.0% | 0.0% | 14.0 | -9.7 |
| Olga Govortsova | 5.2% | 1.7% | 0.8% | 0.1% | 0.0% | 0.0% | 0.0% | 13.6 | -16.0 |
| Dinah Pfizenmaier | 1.9% | 0.6% | 0.2% | 0.0% | 0.0% | 0.0% | 0 | 11.2 | -12.8 |
Contenders
Right up until the forecast numbers came out, I wasn’t looking forward to try and find a way to turn the usual “Serena 50%/Azarenka 30%/who cares 20%” prediction into something interesting. I should be more careful what I wish for because now I have to defend what’s probably the only forecast out there that has Azarenka as the slightest of slight favorites (albeit by an amount that’s smaller than the model’s margin of error).
How can that be possible, especially when trying to reconcile the ranking difference from that tracking graph?
The first thing to look at is the effects of the draw, and it provides some insight. Most people agree that Azarenka benefitted from the draw, but what happens when you actually try to quantify that gain? The draw-independent forecast had Serena with a 40 percent chance of winning and Azarenka with a 36 percent chance; that’s still a little closer than I might have thought, but not that far out of line with Sharapova out of the field.
The change in expected points from the draw do show Azarenka got the second-luckiest draw in the tournament, but that one number doesn’t do it justice for exactly when and where she got a good draw compared to Williams. Here’s a round-by-round comparison that shows how much better both Williams and Azarenka are expected to do with this draw compared to their average draws (click to enlarge):
The graph of an average draw for a player will bounce around the 0-axis with a mix of pluses and minuses for each round. Azarenka got a good draw in every single round, basically flipping a coin 7 times and getting 7 heads. And that spike in the semifinal round is what says the most: Azarenka facing a matchup with both Radwanska and Li was basically a 1-in-4 shot, so she got the best possible draw, since not only does she not face both, but Serena will almost have to play one of them in the semis.
Lower seeds to watch
- Simona Halep: She has been on an absolute tear since May, putting up gaudy scorelines, winning three tournaments, and beating Marion Bartoli so soundly she quit tennis forever (or at least that's the way I interpreted it). With her win in New Haven last week, the No. 21 seed now ranks fifth in AB hard-court ratings. Combine her recent success with the luckiest draw in the tournament, all the stars have aligned for her to become a slight favorite to reach the semifinals.
- Elena Vesnina: Her mini-section of eight is filled almost entirely with clay specialists, including 10-seed Roberta Vinci. She is a solid pick to get to the fourth round with a decent chance of upsetting Wozniacki.
Unseeded dark horses
- Andrea Petkovic: Her level of play since coming back from injury is worthy of being a seed, but the volume-based WTA rankings haven't caught up to her yet. She should be properly seeded by the time the Australian Open comes around.
- Shuai Peng: Her chances got heavily boosted by drawing sub-100 Yvonne Meusberger in the first round. It gets tougher after that, with a likely second-round match against Svetlana Kuznetsova, but her hard-court rating is high enough to put her in contention.
- Qualifier to watch: Mirjana Lucic-Baroni. She got the best draw out of all the unseeded players, getting a weaker American wild card in the first round and a slumping Nadia Petrova in the second.
Cheat Sheet for American Players (Non-Serena Division)
A quick and dirty guide to the American players in the field, and which dark horses to pick to make you look smarter than everyone else.
- Venus Williams: Drastically overrated by AB, which doesn't yet incorporate age-based decline, much less an autoimmune disorder that's began to affect Venus' play. She probably got the best draw of all the Americans though, so if there's a time to get invested for a storybook run, it's probably now.
- Sloane Stephens: Her trademark is performing her best at Slams, a concept on which I'm not sold at all. While everyone may be penciling in a fourth round rematch with Serena, getting past Jamie Hampton isn't exactly a given.
- Jamie Hampton: AB actually rates her higher than Sloane on hard courts. It's a shame they have to play each other and can't both make a deep run, but AB likes her to get to the fourth round more than Sloane.
- Madison Keys: Her wrist injury isn't helping things, and neither did an unlucky first-round match with Jelena Jankovic. She'll have her breakout run eventually, but it probably won't be this year with this draw.
- Varvara Lepchenko: She's had a solid-enough year to warrant a top-40 hard court rating, and got a pretty easy first-round matchup. Her second-rounder with Ana Ivanovic will be worth watching.
- Bethanie Mattek-Sands: The rare American player that performs best on clay courts. Even though she got a favorable draw, she'll be a better dark horse pick for the French Open.
- Mallory Burdette: I'm resigned to AB having been too optimistic about Burdette early on. Drawing a first-round seed probably means she won't have a great chance of validating her high rating this tournament.
- Coco Vandeweghe: She got the best draw of all the American qualifiers, getting another qualifier in round 1 and a clay specialist in round 2. A nice dark horse pick if you want the extra street cred that comes with taking a qualifier.
- Vania King: She would normally have a chance to be a great dark-horse pick with her quiet success on hard courts, but her draw didn't cooperate this year. That said, her path is pretty soft after a first-rounder with Kaia Kanepi, so if she can pull off the upset, she should get to the third round.
Favorite Bets
First-round bets:
- Vera Dushevina (+370) over Sabine Lisicki
- Grace Min (+160) over Karin Knapp
- Karolina Pliskova (+285) over Eugenie Bouchard
- Vania King (+180) over Kaia Kanepi
Futures:
- Victoria Azarenka to win outright (+290)
- Na Li to win outright (28-1)
- Elena Vesnina to win quarter (30-1)
Final Thoughts
It’s worth pausing and reflecting on what it means to not be a clear-cut favorite. If Sharapova had been in the field this year and had a semifinal matchup with Azarenka, the win probabilities probably would have been along the lines of Serena 37%, Azarenka 29%, Sharapova 19%. Because she’s not, the women’s field is top-heavy, and there’s not a lot of credible opposition to Serena and Azarenka.
Being a clear-cut favorite isn’t just a function of your skill level, it also depends heavily on the composition of the field. And in a field that tilts heavily towards the top two, Sharapova’s absence and a favorable draw make Azarenka less likely to lose than Serena. Serena remains just as dominant as she’s been all year, but she’s not a slam dunk to defend her 2012 U.S. Open title.
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