Avi Arora on Oddpool, Institutional Traders & Prediction Market Data | Prediction Market Movers
On this edition of Prediction Market Movers, Chris Gerlacher sits down with Avi Arora, co-founder of Oddpool, to discuss how institutional traders are approaching prediction markets and what infrastructure is still missing for large-scale adoption.
The conversation covers Kalshi, Polymarket, historical tick-level data, market-making, liquidity, institutional flow, prediction market analytics, and how Oddpool is building data tools for traders and hedge funds.
Avi explains how he became interested in prediction markets through mention markets, statistical trading strategies, low-latency broadcast signals, and speech-to-text analysis. The episode also dives into how prediction market data can be used for backtesting, quantitative trading, AI forecasting models, and market pricing across platforms.
The discussion also explores Y Combinator, startup founder dynamics, fundraising, prediction market regulation, and how companies like Kalshi helped push the industry forward.
Avi shares insights into building Oddpool, collecting normalized market data across venues, and why the prediction market data layer could become one of the most valuable segments of the industry over the next several years.
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00:00 - Intro
1:30 - His start in Prediction Markets
5:15 - Starting Oddpool
6:15 - What is missing in prediction markets?
9:15 - Which contracts should be targeted?
11:20 - Getting into Y Combinator and founder dynamics
14:20 - The benefit of Y Combinator
16:30 - On industry interruptions
20:30 - What does a mature industry look like?
22:30 - Hedging on political events
24:00 - Under appreciated data in prediction markets
27:20 - Next steps for Oddpool
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