ITF Bali: Sam Ryan Ziegann vs Thanaphat Boosarawongse

Platform comparison

Market context

Sam Ryan Ziegann and Thanaphat Boosarawongse are due to meet in an ITF Men’s Bali match, and in prediction-market terms a **YES** share pays out if the named player advances, while a **NO** share pays out if he does not. A crowd-implied probability of **0% YES** means the market is pricing the named outcome as effectively impossible, but on a match market that can also reflect very little trading activity rather than firm evidence about the players’ chances.

Publicly available form pages for Sam Ryan Ziegann show limited match history and broadly middling returns, with one results page listing a win rate just under 50% and another showing similar percentages across recent sample sets.[1][2] That kind of thin statistical footprint is common at lower-tier ITF level, where players often have small, uneven datasets and results can move quickly with late withdrawals, qualifiers, or changes in draw order. For a new reader, the main lesson is that a zero-priced outcome in a small tennis market often says as much about liquidity and information gaps as it does about on-court probability.[1][2]

The key catalysts are straightforward: whether the match is actually played on the scheduled Bali card, whether either player withdraws before first serve, and whether the fixture is moved or postponed beyond the market’s seven-day settlement window. Because the market resolves to 50-50 if the match is not played, ends level, or is delayed too long without a winner, traders usually watch tournament order-of-play updates, draw changes, and any last-minute retirement notices. In a lower-level event like an ITF stop in Bali, those scheduling and availability updates can matter more than pre-match rankings or public odds.

Sources: 1 · 2

Methodology

We track ITF Bali: Sam Ryan Ziegann vs Thanaphat Boosarawongse across the five venues with material prediction-market liquidity. The probability shown is the live Polymarket mid; the comparison rows summarise how each venue treats the underlying contract — fees, KYC thresholds, settlement currency, deposit options. The highlighted row marks the cheapest route into Polymarket's order book.

Resolution & payout

At resolution the UMA oracle takes over: a proposer posts the outcome with a bond, any token holder can dispute within two hours. Without dispute the result is accepted and the smart contract distributes USDC instantly.

On Kalshi (CFTC-regulated) resolution runs through their in-house clearing engine in USD. Betfair Exchange settles after match end in the account's local currency. Manifold pays no cash — only its in-platform "mana" currency.

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 Prediction Market UK. Kalshi charges up to 7% per trade; Betfair Exchange takes 2-5% commission on net winnings.

Is this market available outside the US?

Polymarket itself is geo-blocked in the US/UK/EU. Always check the legal status of prediction markets in your jurisdiction before trading.

How does resolution work?

Through the UMA Optimistic Oracle on Polygon: a proposer submits the outcome, a two-hour challenge window opens, and USDC payouts settle automatically once the result is final.

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.

How fast are USDC deposits?

Polygon credits deposits after 12 confirmations — usually under 30 seconds. Withdrawals follow the same path and land back in your wallet within minutes.