BuidlGuidl
@buidlguidl
1/ 🧵 Let’s dive into Web3 prediction markets: - how they turn opinions into probabilities on-chain, - why they’re gaining traction, and - where AI could take them next.
2 replies
5 recasts
29 reactions
BuidlGuidl
@buidlguidl
2/ Prediction markets let you wager on future events, buy/sell outcome shares before resolution, and benefit from permissionless, on-chain settlement. Prices ↔ probabilities.
1 reply
0 recast
1 reaction
BuidlGuidl
@buidlguidl
3/ These markets date back to Wall Street election betting in 1884. On-chain, Polymarket users wagered over $3.3 billion in the 2024 U.S. presidential race alone.
1 reply
0 recast
0 reaction
BuidlGuidl
@buidlguidl
4/ Most are binary: two outcome tokens (“Yes” vs “No”), each pegged to a fixed payout (e.g. 1 USDC). Before resolution, 🎯 Price(Yes)+Price(No)=1 USDC.
1 reply
0 recast
0 reaction
BuidlGuidl
@buidlguidl
5/ Dynamic pricing emerges from supply/demand: buying “Yes” pushes its price up (higher implied probability), while “No” falls — and you can trade anytime.
1 reply
0 recast
0 reaction
BuidlGuidl
@buidlguidl
6/ Order books or AMMs are used for trade execution. Order books (used by Polymarket) are costly to run fully on-chain, so hybrid models - with off-chain matching and on-chain settlement - are now more common.
1 reply
0 recast
0 reaction
BuidlGuidl
@buidlguidl
7/ In AMM models, creators deposit collateral (e.g. 1 ETH) and mint equal outcome tokens (e.g. 100 Yes + 100 No at 0.01 ETH each). Prices shift with token supply.
1 reply
0 recast
0 reaction
BuidlGuidl
@buidlguidl
8/ Pricing rules range from simple linear functions to Logarithmic Market Scoring Rules (LMSR), offering smoother discovery as sentiment shifts — all within the fixed payout cap.
1 reply
0 recast
0 reaction
BuidlGuidl
@buidlguidl
9/ A key challenge is resolving off-chain events. Prediction markets rely on decentralized oracles (e.g. Optimistic Oracle) to report real-world outcomes on-chain.
1 reply
0 recast
0 reaction