
2026 Women’s US Open Winner (Tennis)
Core Summary
According to the latest prediction market data for the query “2026 Women’s US Open Winner (Tennis)”, traders have formed a strong consensus.
Currently, Aryna Sabalenka is dominating the market with an overwhelming 25.5% chance of winning. Iga Swiatek follows in second place at 13%, while Elena Rybakina sits in third with 11.4%. The betting volume for this specific market has already reached $2.7M, reflecting intense industry interest.
Breakdown of Competitive Tiers
To better assess where each potential outcome stands, the market can be segmented into three distinct trading tiers based on implied probability and contract pricing:
🥇 Tier 1: The Dominant Leader
- Aryna Sabalenka (25.5%): Currently commanding the highest probability, Aryna Sabalenka is heavily favored by the order book. Traders looking to back this outcome face a “Buy Yes” contract price of 26¢, signaling a high degree of market conviction. This contract alone has generated $5.4K in volume.
🥈 Tier 2: The Primary Challengers
- Iga Swiatek (13%): Positioned as the most viable alternative, Iga Swiatek maintains a 13% chance of resolving true. Its “Buy Yes” shares currently trade at 13¢.
- Elena Rybakina (11.4%): Sitting in third place with a 11.4% probability, the market shows measured skepticism toward Elena Rybakina, treating it as an outside wildcard unless momentum shifts.
🥉 Tier 3: The Long-Tail Options (Combining for ~50.2%)
Beyond the top three choices, a wide field of macro variables and long-shot outcomes are being tracked. While their individual probabilities hover low, they represent crucial hedges for speculative traders:
- Alternative Options: This includes Coco Gauff (5.7%), Mirra Andreeva (4.7%), and Amanda Anisimova (4.4%).
- Speculative Volume: Despite low statistical likelihood, certain long-tail contracts like Elina Svitolina are still attracting notable interest.
Comprehensive Order Book & Pricing Dashboard
The table below outlines the full breakdown of contract prices, probabilities, and market depth for all listed outcomes in this prediction pool:
| Rank | Predicted Outcome | Win Probability | Trading Volume | Buy Yes (Cost) | Buy No (Cost) |
|---|---|---|---|---|---|
| 1 | Aryna Sabalenka | 25.5% | $5.4K | 26¢ | 75¢ |
| 2 | Iga Swiatek | 13.0% | $5.3K | 13¢ | 87¢ |
| 3 | Elena Rybakina | 11.3% | $67.0K | 11¢ | 89¢ |
| 4 | Coco Gauff | 5.7% | $10.9K | 6¢ | 94¢ |
| 5 | Mirra Andreeva | 4.7% | $18.1K | 5¢ | 95¢ |
| 6 | Amanda Anisimova | 4.3% | $51.2K | 4¢ | 96¢ |
| 7 | Elina Svitolina | 2.9% | $3.4K | 3¢ | 97¢ |
| 8 | Jessica Pegula | 2.3% | $80.7K | 2¢ | 98¢ |
| 9 | Diana Shnaider | 1.8% | $24.5K | 2¢ | 98¢ |
| 10 | Madison Keys | 1.7% | $2.9K | 2¢ | 98¢ |
| 11 | Karolina Muchova | 1.7% | $3.4K | 2¢ | 98¢ |
| 12 | Naomi Osaka | 1.6% | $2.5K | 2¢ | 98¢ |
| 13 | Victoria Mboko | 1.3% | $3.3K | 1¢ | 99¢ |
| 14 | Qinwen Zheng | 0.9% | $220.1K | 1¢ | 99¢ |
| 15 | Emma Navarro | 0.9% | $17.7K | 1¢ | 99¢ |
| 16 | Marie Bouzkova | 0.9% | $24.1K | 1¢ | 99¢ |
| 17 | Anastasia Potapova | 0.9% | $416.2K | 1¢ | 99¢ |
| 18 | Alexandra Eala | 0.9% | $245.6K | 1¢ | 99¢ |
| 19 | Linda Noskova | 0.8% | $4.0K | 1¢ | 99¢ |
| 20 | Jelena Ostapenko | 0.8% | $3.1K | 1¢ | 99¢ |
| 21 | Clara Tauson | 0.7% | $2.2K | 1¢ | 99¢ |
| 22 | Belinda Bencic | 0.7% | $40.3K | 1¢ | 99¢ |
| 23 | Elise Mertens | 0.6% | $20.1K | 1¢ | 99¢ |
| 24 | Barbora Krejcikova | 0.5% | $520.8K | 1¢ | 99¢ |
| 25 | Jasmine Paolini | 0.5% | $4.0K | 1¢ | 100¢ |
| 26 | Ashlyn Krueger | 0.4% | $20.0K | 0¢ | 100¢ |
| 27 | Marketa Vondrousova | 0.4% | $2.3K | 0¢ | 100¢ |
| 28 | Emma Raducanu | 0.4% | $41.5K | 0¢ | 100¢ |
| 29 | Tereza Valentova | 0.4% | $542.6K | 0¢ | 100¢ |
| 30 | Donna Vekic | 0.4% | $109.1K | 0¢ | 100¢ |
| 31 | Ekaterina Alexandrova | 0.4% | $9.3K | 0¢ | 100¢ |
| 32 | Daria Kasatkina | 0.4% | $4.4K | 0¢ | 100¢ |
| 33 | Liudmila Samsonova | 0.4% | $14.2K | 0¢ | 100¢ |
| 34 | Dayana Yastremska | 0.3% | $3.4K | 0¢ | 100¢ |
| 35 | Paula Badosa | 0.3% | $8.2K | 0¢ | 100¢ |
| 36 | Maya Joint | 0.3% | $31.8K | 0¢ | 100¢ |
| 37 | Beatriz Haddad Maia | 0.3% | $24.9K | 0¢ | 100¢ |
| 38 | Sofia Kenin | 0.2% | $2.2K | 0¢ | 100¢ |
| 39 | Katie Boulter | 0.2% | $50.3K | 0¢ | 100¢ |
| 40 | Xiyu Wang | 0.1% | $20.1K | 0¢ | 100¢ |
Result Rules
The 2026 U.S. Open tennis tournament is scheduled for August 23 - September 13, 2026.
This market will resolve to the player that wins the 2026 U.S. Open Women’s Singles Tournament.
If at any point it becomes impossible for a listed player to win the 2026 U.S. Open Women’s Singles Tournament per the rules of the tournament, the corresponding market will resolve to “No”.
If the 2026 U.S. Open Women’s Singles Tournament is cancelled, postponed after October 31, 2026, or there is otherwise no winner declared within that timeframe, this market will resolve to “Other”.
The primary resolution source will be official information from the U.S. Open (https://www.usopen.org/index.html); however, a consensus of credible reporting may also be used.
AI Valuation Analysis: Finding Market Mispricings & EV Gaps
While human consensus and speculative volume shape the broader prediction market, our quantitative algorithms offer a data-driven counter-perspective. By analyzing fundamental signals, underlying trends and historical distributions, our AI Valuation model calculates an independent “Fair Value” probability for each outcome.
Comparing this Fair Value against the current Trade Value uncovers major disparities — known as the Expected Value (EV) Gap. Contracts with a positive EV Gap represent statistically underpriced outcomes, whereas a negative EV Gap flags a potential market overreaction.
Top AI Alpha & Mispriced Arbitrage Opportunities
Based on the latest data model run, several key contracts stand out with significant deviations:
- The Best Value Play (Highest EV) Our model identifies Madison Keys as the premium value opportunity on the board. While the market only assigns it a 1.7% trading probability, our AI’s Fair Value assessment sits at 45.3% — yielding an impressive +43.6% EV Gap.
- Under-the-Radar Dark Horses Other notable discrepancies include Katie Boulter (EV Gap: +42.5%) and Diana Shnaider (EV Gap: +41.9%). These long-tail opportunities are heavily discounted by the live order books despite stronger statistical backing from our predictive model.
| Market | Trade Value | Fair Value | EV Gap |
|---|---|---|---|
| Aryna Sabalenka | 25.5% | 39.1% | +13.7% |
| Iga Swiatek | 13.0% | 40.5% | +27.5% |
| Elena Rybakina | 11.3% | 41.6% | +30.3% |
| Coco Gauff | 5.7% | 43.0% | +37.3% |
| Mirra Andreeva | 4.7% | 44.4% | +39.7% |
| Amanda Anisimova | 4.3% | 37.3% | +32.9% |
| Elina Svitolina | 2.9% | 34.6% | +31.7% |
| Jessica Pegula | 2.3% | 38.5% | +36.2% |
| Diana Shnaider | 1.8% | 43.6% | +41.9% |
| Madison KeysBest EV | 1.7% | 45.3% | +43.6% |
| Karolina Muchova | 1.7% | 39.1% | +37.5% |
| Naomi Osaka | 1.6% | 34.8% | +33.2% |
| Victoria Mboko | 1.3% | 40.5% | +39.3% |
| Qinwen Zheng | 0.9% | 39.3% | +38.4% |
| Emma Navarro | 0.9% | 40.9% | +40.0% |
| Marie Bouzkova | 0.9% | 37.5% | +36.6% |
| Anastasia Potapova | 0.9% | 40.1% | +39.2% |
| Alexandra Eala | 0.9% | 39.9% | +39.0% |
| Linda Noskova | 0.8% | 36.7% | +36.0% |
| Jelena Ostapenko | 0.8% | 33.2% | +32.4% |
| Clara Tauson | 0.7% | 40.3% | +39.6% |
| Belinda Bencic | 0.7% | 39.3% | +38.6% |
| Elise Mertens | 0.6% | 37.3% | +36.7% |
| Barbora Krejcikova | 0.5% | 37.0% | +36.4% |
| Jasmine Paolini | 0.5% | 37.6% | +37.1% |
| Ashlyn Krueger | 0.4% | 38.3% | +37.9% |
| Marketa Vondrousova | 0.4% | 37.4% | +37.0% |
| Emma Raducanu | 0.4% | 38.7% | +38.3% |
| Tereza Valentova | 0.4% | 38.4% | +38.0% |
| Donna Vekic | 0.4% | 38.8% | +38.4% |
| Ekaterina Alexandrova | 0.4% | 36.1% | +35.8% |
| Daria Kasatkina | 0.4% | 34.2% | +33.9% |
| Liudmila Samsonova | 0.4% | 38.7% | +38.3% |
| Dayana Yastremska | 0.3% | 37.1% | +36.8% |
| Paula Badosa | 0.3% | 40.0% | +39.7% |
| Maya Joint | 0.3% | 37.7% | +37.5% |
| Beatriz Haddad Maia | 0.3% | 41.1% | +40.8% |
| Sofia Kenin | 0.2% | 37.2% | +37.0% |
| Katie Boulter | 0.2% | 42.7% | +42.5% |
| Xiyu Wang | 0.1% | 41.7% | +41.6% |
Trade Activities
Here is the trade activities for this event.
Jun 30, 2026
- 03:44 AMB4b41eAd279375742D6C2A1A2239Bdce56376411fD.$1.20
Bought 40 Yes for Will Jessica Pegula win the 2026 Women’s US Open? at 0.03
- 03:44 AMBEbenoitgagnon997$1.02
Bought 34 Yes for Will Jessica Pegula win the 2026 Women’s US Open? at 0.03
- 03:43 AMBEbenoitgagnon997$0.93
Bought 31 Yes for Will Amanda Anisimova win the 2026 Women’s US Open? at 0.03
- 03:35 AMBEbenoitgagnon997$0.93
Bought 92.52 Yes for Will Jasmine Paolini win the 2026 Women’s US Open? at 0.01
- 03:30 AMBEbenoitgagnon997$2.52
Bought 251.62 Yes for Will Diana Shnaider win the 2026 Women’s US Open? at 0.01
- 03:27 AMB4b41eAd279375742D6C2A1A2239Bdce56376411fD.$1.20
Bought 40 Yes for Will Jessica Pegula win the 2026 Women’s US Open? at 0.03
- 03:21 AMBEbenoitgagnon997$0.35
Bought 34.7 Yes for Will Belinda Bencic win the 2026 Women’s US Open? at 0.01
Jun 29, 2026
- 07:31 PM0X0x66E7ce01C6831B8A2503D09eDD6167152Ee68BcD-1771870353938$0.91
Bought 18.181817 Yes for Will Coco Gauff win the 2026 Women’s US Open? at 0.05
- 05:20 PMTWtwentys2$0.89
Sold 88.76 Yes for Will Emma Raducanu win the 2026 Women’s US Open? at 0.01
- 04:18 PM——$0.00
Bought 524.78 Yes for Will Marketa Vondrousova win the 2026 Women’s US Open? at 0
- 02:49 PMCHChristmasCracker$56.05
Sold 266.9 Yes for Will Aryna Sabalenka win the 2026 Women’s US Open? at 0.21
- 12:20 PM5252adsa$0.30
Sold 5 Yes for Will Mirra Andreeva win the 2026 Women’s US Open? at 0.06
Whales Wallets That Are Betting on This Event
Frequently Asked Questions
What is the current market consensus on "2026 Women’s US Open Winner (Tennis)"?
As of the latest update, Aryna Sabalenka leads the field as the frontrunner with a 25.5% win probability, followed by Iga Swiatek at 13% and Elena Rybakina at 11.4%. Total trading volume for this pool has reached $2.7M, indicating deep liquidity and high trader engagement.
How does the AI Fair Value differ from the live Market Trade Value?
The live Market Trade Value reflects public sentiment, order-book momentum and speculative capital. Our AI Fair Value is computed independently with quantitative models that strip out hype to focus on underlying data. When the two diverge, it creates an EV Gap, flagging where the market may be mispricing an outcome.
Which outcome represents the highest Expected Value (EV) right now?
Our latest run flags Madison Keys as the most significant mispricing. While the market trades it at a 1.7% implied probability, our AI calculates a Fair Value of 45.3% — an Expected Value gap of +43.6%, making it the premium value play in this pool.
Are there any high-value dark horse options hidden in the long-tail data?
Absolutely. Beyond the headline outcomes, our model highlights under-the-radar potential in lower-ranked options. Katie Boulter holds a positive EV Gap of +42.5%, and Diana Shnaider shows +41.9%. These contracts are discounted by live order books despite stronger quantitative backing.
