Oddpool
Oddpool is a YC Spring 2026 (P26) company. Based in San Francisco, CA, USA. Team of 2.
About Oddpool
Summary
Oddpool builds a unified data and connectivity layer for prediction markets, serving quant funds, prop trading firms, and macro research desks. It aggregates, normalizes, and streams order book data, trade history, and live probabilities across fragmented venues like Kalshi and Polymarket into a single API. The product replaces the manual work of piecing together clean, backtestable data from multiple incompatible exchanges.
Business model
Free tier up to 1,000 requests per month, then $30/month (Pro) and $100/month (Premium), with a separate institutional tier.
Go-to-market
Individual quants and developers start self-serve with an API key and no sales call; institutional desks, including market makers and hedge funds, are onboarded through a direct sales process via a booked call.
From the Y Combinator listing
Institutional infrastructure for prediction markets
Oddpool is a platform that helps quant funds and trading desks harness the power of prediction markets. We make it easy to access, search, and analyze every venue from one place. Avi and Ritesh have been roommates since freshman year at Georgia Tech. Avi has a Master's in ML and saved Microsoft $6M/year by building a more accurate model on half the hardware. Ritesh has a Master's in Distributed Systems and made buy-side trading systems at Bloomberg 40% faster. We started trading prediction markets ourselves but couldn't backtest our strategies because the tooling for this emerging asset class didn't exist. The deeper we went, the more we saw that fragmentation between prediction markets and lack of clean data was going to be a big problem. We launched a prosumer tier and grew to several thousand dollars in MRR within months. Now we're bringing it to institutions, building tooling with the rigor and depth serious desks demand. They're the fastest growing asset class in finance, and CFTC applications for new exchanges keep climbing. Each new venue makes the market bigger, the fragmentation worse, and the unified data layer more valuable. It doesn't exist yet. We're building it.
Facts
- B2B / B2B -> Engineering, Product and Design
- San Francisco, CA, USA
- 2
- Active
- Early
Founders (2)
- Ritesh Malpani
Score every batch against your own thesis
GPAgent's sourcing agent reads every company in a batch, scores each one against your fund's thesis in a private workspace, and lines up the founders worth meeting before Demo Day. You decide who to contact. Your scores, notes, and pipeline never appear on these pages.
How Accelerator intelligence works