Prediction markets Overview

1. TLDR
• Allows users to trade “shares” on future events (sports, politics, culture, crypto) that pay $1 if the event happens and $0 if it doesn’t
• In theory, markets aggregate dispersed information into better forecasts; in practice the UX and distribution are shifting fast toward social, feed-native experiences
• Daily volumes are around ~$30M each on Polymarket ($1b valuation) and Kalshi (~$2B valuation) and a friendlier U.S. regulatory stance on this market
• Adheres to the "hypergamble/hyperfinancialisation" thesis and a growing social element --> every post has an attached market and “bets become statements” (identity + reputation), lowering intent/friction and broadening participation

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2. Project landscape
a) Markets
• @Polymarket: largest crypto-native venue on @Polygon whose markets resolve through UMA’s optimistic oracle
• @Kalshi: A CFTC-regulated, U.S.-accessible exchange --> contracts listed on a Designated Contract Market with event specifications
• @DriftProtocol B.E.T: DeFi native market on @solana

b) Terminals & bots building on top
• @fliprbot: social trading bot + terminal that started on X, goal to become a cross-venue aggregator
• @polycule_bot: @telegram-native bot for Polymarket with copy-trading
• @betmoardotfun: a Polymarket web terminal with breaking-news feeds, on-page trading, wallet/profiles analytics

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3. The risks (and why disputes happen)
• Unclear market rules: Recent example was the $14M “Zelenskyy suit” where the market showed how even widely reported “facts” (most outlets said he wore a suit) can still be argued both ways --> what is perceived fairness?
• Oracle design & governance trade-offs: On Polymarket, many markets ultimately rely on UMA token-holder votes. In the Venezuela election market, critics argue UMA voters overrode the event’s posted resolution rules (primary source of truth was the official results) and paid out based on a media-consensus standard instead --> i.e. conflicts if voters can also be traders
• Manipulation risk: can shift from “truth-seeking” to “tautology-seeking” --> incentives to push narratives rather than measure them

They were initially quite niche, but quickly moving into mainstream + socially distributed products.

The upside is faster, crowd-priced info; but the big downside is that wording, oracles, and incentives still has to be solved.

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*Notable project mentions
a) Prediction markets
• @Truemarketsorg
• @HedgehogMarket
• @noise_xyz
• @inertia_social
• @trylimitless
• @swaye_co
• @metaculus
• @narrativexyz
• @trepa_io
• @xodotmarket
• @ManifoldMarkets
• @BRKTgg
• @MyriadMarkets
• @PredictBase

b) Sports focused
• @azuroprotocol
• @Overtime_io
• @SX_Bet