
2026 Women’s US Open Winner (Tennis)
核心摘要
根據「2026 Women’s US Open Winner (Tennis)」的最新預測市場資料,交易者已形成強烈共識。
目前,Aryna Sabalenka 以壓倒性的 25.5% 獲勝機率主導市場;Iga Swiatek 以 13% 位居第二,Elena Rybakina 以 11.4% 排名第三。該市場的下注量已達 $2.7M,反映出市場的高度關注。
競爭梯隊拆解
為了更好地評估各潛在結果的位置,可依據隱含機率與合約定價將市場劃分為三個明顯的交易梯隊:
🥇 第一梯隊:絕對領跑者
- Aryna Sabalenka (25.5%):Aryna Sabalenka 目前擁有最高機率,深受訂單簿青睞。看好該結果的交易者面對的「Buy Yes」合約價為 26¢,顯示出市場的高度確信。僅該合約就已產生 $5.4K 的成交量。
🥈 第二梯隊:主要挑戰者
- Iga Swiatek (13%):作為最可行的替代選項,Iga Swiatek 保持著 13% 的成真機率,其「Buy Yes」份額目前成交價為 13¢。
- Elena Rybakina (11.4%):以 11.4% 的機率位列第三,市場對 Elena Rybakina 持謹慎懷疑態度,除非勢頭轉變,否則視其為外圍黑馬。
🥉 第三梯隊:長尾選項(合計約 50.2%)
在前三名之外,還有大量宏觀變數與冷門結果被持續追蹤。儘管單個機率偏低,但它們是投機交易者的重要對沖:
- 替代選項:包括 Coco Gauff (5.7%)、Mirra Andreeva (4.7%),以及 Amanda Anisimova (4.4%)。
- 投機成交:儘管統計機率偏低,像 Elina Svitolina 這類長尾合約仍吸引著可觀的關注。
完整訂單簿與定價面板
下表列出了該預測池中所有結果的合約價格、機率與市場深度的完整拆解:
| 排名 | 預測結果 | 獲勝機率 | 成交量 | 買入 Yes(成本) | 買入 No(成本) |
|---|---|---|---|---|---|
| 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¢ |
裁決規則
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 估值分析:發現市場錯誤定價與 EV 差
人群共識與投機成交塑造了更宏觀的預測市場,而我們的量化演算法提供了資料驅動的反向視角。透過分析基本面訊號、底層趨勢與歷史分布,我們的 AI 估值模型為每個結果獨立測算出一個「公允價值」機率。
將該公允價值與當前交易價值對比,可揭示出重大背離——即期望值(EV)差。正 EV 差代表統計上被低估的結果,而負 EV 差則提示市場可能存在反應過度。
頂級 AI Alpha 與錯誤定價套利機會
根據最新一輪資料模型測算,以下幾個關鍵合約存在顯著偏離:
- 最佳價值標的(最高 EV):我們的模型將 Madison Keys 識別為盤面上最具價值的機會。市場僅給予其 1.7% 的交易機率,而我們 AI 的公允價值評估為 45.3%——形成可觀的 +43.6% EV 差。
- 被忽視的黑馬:其他值得注意的偏離包括 Katie Boulter(EV 差:+42.5%)以及 Diana Shnaider(EV 差:+41.9%)。儘管我們的預測模型給予更強的統計支撐,這些長尾機會仍被即時訂單簿大幅低估。
| 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% |
交易動態
以下是該事件的交易動態。
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
正在押注該事件的鯨魚錢包
常見問題
目前市場對「2026 Women’s US Open Winner (Tennis)」的共識是什麼?
截至最新更新,Aryna Sabalenka 以 25.5% 的獲勝機率領跑,其次是 Iga Swiatek(13%),以及 Elena Rybakina(11.4%)。該市場總成交量已達 $2.7M,顯示出充足的流動性與高交易參與度。
AI 公允價值與即時市場交易價值有何不同?
即時市場交易價值反映的是公眾情緒、訂單簿動能與投機資金。我們的 AI 公允價值則由量化模型獨立計算,剔除情緒炒作、專注底層數據。兩者出現顯著背離時即形成 EV 差,提示市場對某個結果可能存在錯誤定價。
目前哪個結果的期望值(EV)最高?
最新一輪測算顯示,Madison Keys 是最顯著的錯誤定價。市場對其隱含機率僅給到 1.7%,而我們的 AI 測算其公允價值為 45.3%——形成 +43.6% 的期望值差,是該市場中最具價值的標的。
長尾資料中是否藏有高價值的黑馬選項?
當然有。除了頭部結果之外,我們的模型在排名靠後的選項中發現了被低估的潛力。Katie Boulter 擁有 +42.5% 的正 EV 差,Diana Shnaider 則為 +41.9%。儘管量化層面更有支撐,這些合約仍被即時訂單簿低估。
