Canadian Open: Sebastian Baez vs Mattia Bellucci

Platform comparison

Market context

Sebastian Baez and Mattia Bellucci were scheduled to meet in the Canadian Open men’s draw in Montreal, and the market’s 100% YES pricing implies the contract is treating Baez as a near-certain advance unless the fixture is abandoned or converted into a 50-50 void. For a programmatic trader, that means the main task is not price discovery but event-state monitoring: track whether the match is officially played, whether a winner is recorded, and whether any postponement pushes settlement into the market’s tie clause.

Comparable pre-match pricing from external tennis books and model feeds was much more balanced, with several outlets putting Baez roughly in the low- to mid-50s and Bellucci close behind rather than priced as a lock.[4][8][11][13] That gap matters because prediction-market probabilities can move from genuine match expectancy to operational certainty when the contract is already close to resolution; in other words, a 100% print often reflects either the market already resolving to a known outcome or a stale order book after the underlying event has effectively passed.

The catalysts to watch are tournament scheduling updates, official match completion, and any withdrawal, walkover, suspension, or rescheduling notices from the Canadian Open draw or live scoring feeds. FanDuel and live-score listings show this as a Montreal ATP fixture, while multiple data pages still carry the pairing and odds, so a bot should verify the actual court status before acting on the headline probability.[1][2][3][10] If your workflow uses conditional orders, the key dependency is the settlement rule: a match not played at all, or delayed beyond seven days without a winner, resolves to 50-50, so automation should check both the result feed and any postponement timestamp before assuming finality.

Sources: 1 · 2 · 3 · 4 · 5

Methodology

Methodologically we separate two layers: the live probability (Polymarket mid-price) and the platform attributes (fee, KYC, settlement currency, payment rails). That keeps the comparison honest — a single canonical probability across the row, with the venue-by-venue trade-offs spelt out in the columns next to it.

Resolution & payout

Settlement runs on-chain. Polymarket's contract logic separates YES and NO shares as conditional tokens; at resolution the winning share lifts to $1.00 and the losing one to $0. The outcome input comes from the UMA Optimistic Oracle, which secures against bad resolution with a bond + dispute window.

Once finalised, the smart contract pays USDC to the holders' wallets within minutes — no withdrawal fees beyond Polygon network gas. Kalshi settles in USD via CFTC clearance, Betfair in account currency net of commission, Manifold in play-money mana with no cash-out.

FAQ

Where can I trade this market with the lowest fees?

Polymarket is geo-blocked in the US/UK/EU. The easiest 0%-fee broker into the same order book is Kalshi Fees. Kalshi charges up to 7% per trade; Betfair Exchange takes 2-5% commission on net winnings.

What's the difference between YES and NO shares?

A YES share pays $1.00 if the event happens, $0 otherwise. A NO share pays $1.00 if the event doesn't happen. The market price between 0¢ and 100¢ is the implied probability.

What does Polymarket cost to trade?

Polymarket itself charges 0% — the only cost is the Polygon network fee, typically under $0.01 per transaction. Off-chain venues like Kalshi or Betfair charge 2-7% commission.

Do I need to KYC for this market?

On Polymarket directly, no — it's wallet-based. Intermediary brokers like Kalshi Fees trigger KYC only above $1,500 of lifetime trading volume; under that you trade pseudonymously with a single wallet address.

How reliable are the quoted odds?

The YES/NO percentages are the live mid-prices of the Polymarket order book. On deep markets they move every few seconds; on thinner ones you'll see short plateaus.