
2026 Women's Wimbledon Winner
Core Summary
According to the latest prediction market data for the query “2026 Women's Wimbledon Winner”, traders have formed a strong consensus.
Currently, Aryna Sabalenka is dominating the market with an overwhelming 22.5% chance of winning. Elena Rybakina follows in second place at 18%, while Mirra Andreeva sits in third with 9.3%. The betting volume for this specific market has already reached $7.7M, 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 (22.5%): 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 23¢, signaling a high degree of market conviction. This contract alone has generated $18.9K in volume.
🥈 Tier 2: The Primary Challengers
- Elena Rybakina (18%): Positioned as the most viable alternative, Elena Rybakina maintains a 18% chance of resolving true. Its “Buy Yes” shares currently trade at 18¢.
- Mirra Andreeva (9.3%): Sitting in third place with a 9.3% probability, the market shows measured skepticism toward Mirra Andreeva, treating it as an outside wildcard unless momentum shifts.
🥉 Tier 3: The Long-Tail Options (Combining for ~50.3%)
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 Iga Świątek (9%), Amanda Anisimova (5.8%), and Coco Gauff (4.6%).
- Speculative Volume: Despite low statistical likelihood, certain long-tail contracts like Jessica Pegula 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 | 22.5% | $18.9K | 23¢ | 78¢ |
| 2 | Elena Rybakina | 18.0% | $26.3K | 18¢ | 82¢ |
| 3 | Mirra Andreeva | 9.3% | $792.5K | 9¢ | 91¢ |
| 4 | Iga Świątek | 9.0% | $272.7K | 9¢ | 91¢ |
| 5 | Amanda Anisimova | 5.8% | $1.0M | 6¢ | 94¢ |
| 6 | Coco Gauff | 4.5% | $116.8K | 5¢ | 95¢ |
| 7 | Jessica Pegula | 3.0% | $258.6K | 3¢ | 97¢ |
| 8 | Elina Svitolina | 2.8% | $18.6K | 3¢ | 97¢ |
| 9 | Emma Raducanu | 1.9% | $245.4K | 2¢ | 98¢ |
| 10 | Marta Kostyuk | 1.9% | $41.4K | 2¢ | 98¢ |
| 11 | Karolína Muchová | 1.7% | $166.4K | 2¢ | 98¢ |
| 12 | Barbora Krejčíková | 1.6% | $45.1K | 2¢ | 98¢ |
| 13 | Diana Shnaider | 1.2% | $43.7K | 1¢ | 99¢ |
| 14 | Markéta Vondroušová | 1.1% | $14.9K | 1¢ | 99¢ |
| 15 | Madison Keys | 1.1% | $149.4K | 1¢ | 99¢ |
| 16 | Linda Nosková | 0.9% | $67.4K | 1¢ | 99¢ |
| 17 | Belinda Bencic | 0.8% | $40.0K | 1¢ | 99¢ |
| 18 | Naomi Osaka | 0.8% | $13.6K | 1¢ | 99¢ |
| 19 | Donna Vekić | 0.8% | $33.5K | 1¢ | 99¢ |
| 20 | Qinwen Zheng | 0.7% | $25.0K | 1¢ | 99¢ |
| 21 | Anna Kalinskaya | 0.7% | $52.9K | 1¢ | 99¢ |
| 22 | Jasmine Paolini | 0.4% | $248.3K | 0¢ | 100¢ |
| 23 | Liudmila Samsonova | 0.4% | $100.2K | 0¢ | 100¢ |
| 24 | Emma Navarro | 0.4% | $27.0K | 0¢ | 100¢ |
| 25 | Clara Tauson | 0.4% | $447.3K | 0¢ | 100¢ |
| 26 | Jelena Ostapenko | 0.4% | $901.2K | 0¢ | 100¢ |
| 27 | Ekaterina Alexandrova | 0.4% | $48.7K | 0¢ | 100¢ |
| 28 | Tatjana Maria | 0.4% | $14.3K | 0¢ | 100¢ |
| 29 | Dayana Yastremska | 0.4% | $8.2K | 0¢ | 100¢ |
| 30 | Elise Mertens | 0.4% | $38.5K | 0¢ | 100¢ |
| 31 | Ons Jabeur | 0.3% | $145.7K | 0¢ | 100¢ |
| 32 | Leylah Fernandez | 0.3% | $11.6K | 0¢ | 100¢ |
| 33 | Xinyu Wang | 0.3% | $29.0K | 0¢ | 100¢ |
| 34 | Anastasia Pavlyuchenkova | 0.3% | $43.8K | 0¢ | 100¢ |
| 35 | Yulia Putintseva | 0.3% | $30.4K | 0¢ | 100¢ |
| 36 | Marie Bouzková | 0.3% | $38.8K | 0¢ | 100¢ |
| 37 | Ashlyn Krueger | 0.2% | $735.1K | 0¢ | 100¢ |
| 38 | Paula Badosa | 0.1% | $88.8K | 0¢ | 100¢ |
| 39 | Maya Joint | 0.1% | $317.2K | 0¢ | 100¢ |
| 40 | Olga Danilović | 0.1% | $8.5K | 0¢ | 100¢ |
| 41 | McCartney Kessler | 0.1% | $11.4K | 0¢ | 100¢ |
| 42 | Solana Sierra | 0.1% | $56.9K | 0¢ | 100¢ |
| 43 | Sonay Kartal | 0.1% | $48.9K | 0¢ | 100¢ |
| 44 | Beatriz Haddad Maia | 0.1% | $33.7K | 0¢ | 100¢ |
| 45 | Laura Siegemund | 0.1% | $9.0K | 0¢ | 100¢ |
| 46 | Maria Sakkari | 0.1% | $10.9K | 0¢ | 100¢ |
Result Rules
Wimbledon 2026 is scheduled for June 29 - July 12, 2026.
This market will resolve to the player that wins the 2026 Wimbledon Women’s Singles Tournament.
If at any point it becomes impossible for a listed player to win the 2026 Wimbledon Women’s Singles Tournament per the rules of the tournament, the corresponding market will resolve to “No”.
If the 2026 Wimbledon Women’s Singles Tournament is cancelled, postponed after August 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 Wimbledon (https://www.wimbledon.com/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 Jasmine Paolini as the premium value opportunity on the board. While the market only assigns it a 0.4% trading probability, our AI’s Fair Value assessment sits at 51.9% — yielding an impressive +51.4% EV Gap.
- Under-the-Radar Dark Horses Other notable discrepancies include Xinyu Wang (EV Gap: +50.8%) and Donna Vekić (EV Gap: +50.7%). 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 | 22.5% | 46.3% | +23.8% |
| Elena Rybakina | 18.0% | 29.8% | +11.8% |
| Mirra Andreeva | 9.3% | 35.4% | +26.1% |
| Iga Świątek | 9.0% | 45.1% | +36.1% |
| Amanda Anisimova | 5.8% | 35.7% | +29.9% |
| Coco Gauff | 4.5% | 34.5% | +29.9% |
| Jessica Pegula | 3.0% | 31.7% | +28.7% |
| Elina Svitolina | 2.8% | 35.8% | +33.0% |
| Emma Raducanu | 1.9% | 41.3% | +39.4% |
| Marta Kostyuk | 1.9% | 40.5% | +38.6% |
| Karolína Muchová | 1.7% | 35.8% | +34.2% |
| Barbora Krejčíková | 1.6% | 40.3% | +38.7% |
| Diana Shnaider | 1.2% | 51.8% | +50.6% |
| Markéta Vondroušová | 1.1% | 36.7% | +35.6% |
| Madison Keys | 1.1% | 35.6% | +34.6% |
| Linda Nosková | 0.9% | 39.3% | +38.4% |
| Belinda Bencic | 0.8% | 27.6% | +26.8% |
| Naomi Osaka | 0.8% | 36.8% | +36.0% |
| Donna Vekić | 0.8% | 51.4% | +50.7% |
| Qinwen Zheng | 0.7% | 33.0% | +32.4% |
| Anna Kalinskaya | 0.7% | 38.2% | +37.6% |
| Jasmine PaoliniBest EV | 0.4% | 51.9% | +51.4% |
| Liudmila Samsonova | 0.4% | 39.7% | +39.2% |
| Emma Navarro | 0.4% | 37.6% | +37.2% |
| Clara Tauson | 0.4% | 45.9% | +45.4% |
| Jelena Ostapenko | 0.4% | 41.8% | +41.4% |
| Ekaterina Alexandrova | 0.4% | 44.1% | +43.8% |
| Tatjana Maria | 0.4% | 39.2% | +38.8% |
| Dayana Yastremska | 0.4% | 49.5% | +49.1% |
| Elise Mertens | 0.4% | 33.9% | +33.6% |
| Ons Jabeur | 0.3% | 49.6% | +49.3% |
| Leylah Fernandez | 0.3% | 36.3% | +36.1% |
| Xinyu Wang | 0.3% | 51.0% | +50.8% |
| Anastasia Pavlyuchenkova | 0.3% | 38.3% | +38.0% |
| Yulia Putintseva | 0.3% | 49.5% | +49.3% |
| Marie Bouzková | 0.3% | 39.8% | +39.5% |
| Ashlyn Krueger | 0.2% | 38.6% | +38.4% |
| Paula Badosa | 0.1% | 33.3% | +33.1% |
| Maya Joint | 0.1% | 38.1% | +38.0% |
| Olga Danilović | 0.1% | 38.6% | +38.4% |
| McCartney Kessler | 0.1% | 46.5% | +46.3% |
| Solana Sierra | 0.1% | 48.1% | +47.9% |
| Sonay Kartal | 0.1% | 38.3% | +38.2% |
| Beatriz Haddad Maia | 0.1% | 37.4% | +37.2% |
| Laura Siegemund | 0.1% | 50.5% | +50.4% |
| Maria Sakkari | 0.1% | 39.7% | +39.5% |
Trade Activities
Here is the trade activities for this event.
Jun 30, 2026
- 07:55 AM——$0.00
Sold 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:55 AM——$0.00
Bought 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:55 AM——$0.00
Sold 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:55 AM——$0.00
Bought 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AM——$0.00
Sold 3037.76 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AMNOnorthdrawer$0.00
Sold 0.74 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AM——$0.00
Bought 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AM——$0.00
Sold 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AM——$0.00
Bought 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AM——$0.00
Sold 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:54 AM——$0.00
Bought 3038.5 Yes for Will Dayana Yastremska be the 2026 Women’s Wimbledon Winner? at 0
- 07:51 AM——$67.84
Sold 67.84 No for Will Jasmine Paolini be the 2026 Women’s Wimbledon Winner? at 1
Whales Wallets That Are Betting on This Event
Frequently Asked Questions
What is the current market consensus on "2026 Women's Wimbledon Winner"?
As of the latest update, Aryna Sabalenka leads the field as the frontrunner with a 22.5% win probability, followed by Elena Rybakina at 18% and Mirra Andreeva at 9.3%. Total trading volume for this pool has reached $7.7M, 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 Jasmine Paolini as the most significant mispricing. While the market trades it at a 0.4% implied probability, our AI calculates a Fair Value of 51.9% — an Expected Value gap of +51.4%, 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. Xinyu Wang holds a positive EV Gap of +50.8%, and Donna Vekić shows +50.7%. These contracts are discounted by live order books despite stronger quantitative backing.
