Platform comparison
| Platform | YES odds | NO odds | Fee | KYC | Settlement | |
|---|---|---|---|---|---|---|
Polymarket (via Champions League Prediction) Pick polygram.ink (preferred broker) |
25% | 75% | 0% (USDC on-chain) | No-KYC up to $1,500 | USDC, auto via UMA oracle | See live odds → |
Polymarket (direct) polymarket.com |
25% | 75% | 0% | Geo-blocked in US/UK/EU | USDC, on-chain | See live odds → |
Kalshi kalshi.com |
— | — | Up to 7% per trade | US-only, KYC required | USD | See live odds → |
Betfair Exchange betfair.com |
— | — | 2-5% commission | Full KYC from first trade | GBP / EUR | See live odds → |
Manifold Markets manifold.markets |
— | — | Play-money (mana) | None — play-money | Mana (no cash-out) | See live odds → |
Outcome probabilities
Current market-implied probability for each outcome, from the live order book.
| Outcome | Probability |
|---|---|
| Aryna Sabalenka | 25% |
| Iga Swiatek | 10% |
| Elena Rybakina | 9% |
| Coco Gauff | 8% |
| Mirra Andreeva | 6% |
| Naomi Osaka | 6% |
| Amanda Anisimova | 4% |
| Jessica Pegula | 4% |
| Linda Noskova | 4% |
| Karolina Muchova | 3% |
| Madison Keys | 2% |
| Elina Svitolina | 2% |
| Alexandra Eala | 2% |
| Qinwen Zheng | 1% |
| Barbora Krejcikova | 1% |
| Victoria Mboko | 1% |
| Emma Navarro | 1% |
| Belinda Bencic | 1% |
| Jasmine Paolini | 1% |
| Paula Badosa | 1% |
| Diana Shnaider | 1% |
| Marie Bouzkova | 1% |
| Elise Mertens | 1% |
| Marketa Vondrousova | 0% |
| Clara Tauson | 0% |
| Emma Raducanu | 0% |
| Maya Joint | 0% |
| Ekaterina Alexandrova | 0% |
| Jelena Ostapenko | 0% |
| Daria Kasatkina | 0% |
| Tereza Valentova | 0% |
| Anastasia Potapova | 0% |
| Donna Vekic | 0% |
| Dayana Yastremska | 0% |
| Liudmila Samsonova | 0% |
| Xiyu Wang | 0% |
| Ashlyn Krueger | 0% |
| Beatriz Haddad Maia | 0% |
| Sofia Kenin | 0% |
| Katie Boulter | 0% |
| Other | 0% |
| Player A | 0% |
| Player B | 0% |
| Player C | 0% |
| Player D | 0% |
| Player E | 0% |
| Player F | 0% |
| Player G | 0% |
| Player H | 0% |
| Player I | 0% |
| Player J | 0% |
| Player K | 0% |
| Player L | 0% |
| Player M | 0% |
| Player N | 0% |
| Player O | 0% |
| Player P | 0% |
| Player Q | 0% |
| Player R | 0% |
| Player S | 0% |
| Player T | 0% |
| Player U | 0% |
| Player V | 0% |
| Player W | 0% |
| Player X | 0% |
| Player Y | 0% |
| Player Z | 0% |
Market context
The 2026 US Open women’s singles runs from 23 August to 13 September, and the market is effectively asking whether the current leader can convert that status into a second straight New York title. Aryna Sabalenka is priced as the frontrunner at 25%, ahead of Iga Swiatek at 10%, Coco Gauff at 8.5% and Elena Rybakina at 9.2%, which is a typical spread for a Grand Slam held on a surface where a small group of elite hard-court players usually dominate the market.[2]
A 25% read on the leader is strong, but it still leaves a broad field of plausible winners, and that matters because women’s majors have produced repeat champions and surprise runs in equal measure. Sabalenka’s position is consistent with book pricing that has her as the outright favourite, while recent market snapshots also show her around the low-to-mid 20s in implied probability, suggesting the consensus has been stable rather than drifting sharply.[1][3][5] In practical terms, a quarter-chance implies the market is respecting her top-end level without treating her as close to a lock, which is usually what you see when there is no dominant injury-free runaway favourite.
The main catalysts from here are entry lists, seeding, withdrawal news and any fitness updates from the top four or five names. Sabalenka, Swiatek, Gauff, Rybakina and Mirra Andreeva have all been priced as live contenders in external books and prediction markets, so any late-summer slump, scheduling change or physical issue could move the board quickly.[1][2][3] Traders should also watch the lead-in hard-court events in North America, because results there often reset expectations before Flushing Meadows and can sharpen or weaken the case for the market leader.
Methodology
Football-specific comparison page for 2026 Women’s US Open Winner (Tennis). Polymarket's live quote (Polygon order book) plus platform attributes for the three reference venues. Sports markets reward liquidity — Polymarket and Betfair are materially deeper than Kalshi (US-focused) or Manifold (play-money).
Resolution & payout
Sports markets typically settle on official final-whistle plus league confirmation. Polymarket uses UMA Optimistic Oracle with a source URL per contract — usually official league data feeds or ESPN/Soccerway. Two-hour dispute window, then smart-contract payout in USDC.
FAQ
- Are prediction markets better than sports betting?
- Prediction markets tend toward tighter odds than bookmakers because they use peer-to-peer exchange rather than bookmaker margin. On major matches, Polymarket quotes typically sit 2-5% closer to the true probability model than bet365 or DraftKings.
- Can I bet on individual matches?
- Yes, Polymarket lists every major Premier League / Champions League / World Cup match as its own market. Liquidity varies — top matches like El Clásico or a semi-final often have six-figure pools, lower-league games closer to three-figure.
- What are live sports odds on Polymarket?
- Some top-tier matches stay open during play — you can trade the half-time probability in the 70th minute. Polymarket mid-prices update second-by-second; any frontend mirroring the order book shows the same movement.
- Which sports markets are available?
- Football (soccer) dominates — Champions League, World Cup, Premier League, La Liga, Bundesliga — followed by NFL, NBA, tennis Grand Slams, Formula 1, boxing/MMA. Resolution via official league source confirmation.
- What's the difference between match odds and outright odds?
- Match odds cover a single game ("Bayern beats BVB"). Outright odds are long-term aggregates ("Bayern wins the league"). Outright markets have deeper liquidity; match markets have faster resolution.
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