How on-chain sportsbooks actually settle bets

"Non-custodial" tells you funds aren't held by a company. It doesn't tell you how a bet actually gets matched, priced and paid out. That part varies a lot between platforms, and understanding the mechanics helps explain things like why liquidity depth differs so much between two platforms that are both, technically, decentralized. Here are the three models you'll run into most often.

1. Peer-to-peer order books

This is the closest on-chain analog to a traditional betting exchange like Betfair. Bettors post orders to back or lay a specific outcome at a specific price, and a matching engine — sometimes fully on-chain, sometimes off-chain for speed with on-chain settlement — pairs opposing orders together. SX Bet and BetDEX both use variants of this model: on BetDEX, matching happens through the open-source Monaco Protocol, with funds escrowed and settled on-chain rather than held by the platform.

The practical upside is pricing that reflects real supply and demand between users rather than a house-set line. The tradeoff is liquidity: if there aren't enough opposing orders at your price on a given market, you either wait, accept a worse price, or split your bet across multiple smaller fills. This is exactly why order-book platforms tend to have deeper liquidity on major markets (top-tier football, NBA) and thinner books on niche sports.

2. Automated market makers (AMMs)

Borrowed directly from decentralized token exchanges like Uniswap, this model replaces a matching engine with a liquidity pool and a pricing formula. Instead of waiting for another bettor to take the other side of your wager, you're trading against a pool that automatically adjusts odds based on how much has already been staked on each outcome. Overtime Markets uses this approach across Optimism, Arbitrum and Base.

The advantage is that you can always get a bet matched instantly — there's no waiting for a counterparty, because the pool is always the counterparty. The tradeoff is that heavy one-sided betting on a popular outcome can move the pool's implied odds significantly, the same way a large token swap moves price on a DEX. Well-designed AMM sportsbooks manage this with pool depth and exposure limits, but it's a structurally different risk profile than an order book.

3. Peer-to-pool models

A close cousin of the AMM approach, peer-to-pool platforms let users deposit into a shared liquidity pool that collectively underwrites the sportsbook's payouts, earning a share of the book's net results in return. Divvy.bet's "House Pool" is a small-scale example of this design on Solana — bettors wager against the pool directly, and pool depositors take on the book's aggregate risk and reward.

This model effectively turns bettors on the other side into the house, distributed across everyone who deposited into the pool. It's a genuinely different risk-sharing structure than either of the other two models, and worth understanding if you're evaluating a platform that offers this kind of liquidity-provider role alongside its sportsbook.

4. Prediction markets (a related but distinct category)

Polymarket doesn't fit neatly into "sportsbook" at all — it's a prediction market trading YES/NO shares on outcomes through an on-chain central limit order book, with prices representing implied probability rather than fixed odds. Settlement depends on real-world outcome resolution rather than a live scoreboard feed. It's worth knowing this distinction exists, since prediction-market mechanics (share pricing, resolution sources, potential for disputed outcomes) differ meaningfully from traditional fixed-odds betting.

Why this matters for you as a bettor

None of these models is objectively "more decentralized" than another — they're all non-custodial in the sense that funds settle via smart contract rather than a company's ledger. But they behave differently in practice: order books reward patience and liquidity-aware bet sizing, AMMs guarantee instant matching at the cost of pool-driven price impact, and peer-to-pool models put you on the other side of a shared risk pool rather than an individual counterparty. Knowing which one you're using explains a lot about why the same bet can feel very different from platform to platform.