The Risk Takers Podcast

They walk through starting an automated API trading project, from a simple balance print to CSV-driven orders and trade tapes. They explore finding liquid wide markets, building alerts and opportunity scores, and metrics to rank attractive markets. They also debate platform fees, legal risks to prediction markets, and where VC money should flow.

A deep dive into mention markets and live trading tactics. Stories about building announcer databases and pricing speeches. How coding, bots, and AI speed cross-exchange arbitrage. Practical talk on live mispricing, RFQs, and exploiting correlated award and political markets.

They dig into the emotional reality of long losing stretches and how they change decision making. There is a deep debate about showing RFQ user IDs and how that shifts market behavior. Legal and industry news, market profiling tactics, automation impacts, and practical trading adjustments round out the conversation.

A nerdy deep dive on which sports stats actually predict outcomes and how to separate signal from noise. A LoL example shows why raw counts can mislead and when to use proxies and standardized inputs. A detailed look at a controversial Kalshi Iran leadership market, settlement rules, and the problems with last-traded-price resolutions. Brief industry news, trading mechanics, and ethical concerns around death and war markets.

A clear walkthrough of how to build a basic sports betting model, from napkin math to full distributions. They compare ground-up and hybrid approaches and explain when linear regression is enough. Feature engineering, gathering niche data, backtesting and spotting residual biases are covered. The show also reacts to recent industry news and answers practical modeling and time-management questions.

Eric (Egzee), a college junior and top prediction-market trader who built automated scraping and market-making systems for Kalshi. He describes building live bots, automating RFQ combos, and running a large solo market-making operation while managing latency, sizing bugs, and exploiters. He also covers balancing school with a major internship decision and scaling a high-frequency trading setup.

They relive high‑volume Super Bowl prop trading and the quirky spread vs moneyline distortions that hit their wagers. They dig into the Cardi B market, its contradictory rules, and messy resolution processes. They debate how prediction markets invite insider information, the risks of poor rulemaking, and whether culture markets are toxic compared with sports markets.

Mike (Mr. PeanutBettor) — an actuary-turned-sports bettor and prominent gambling Twitter originator. He discusses trading at Deck Prism and how that shaped live and pregame strategies. Conversations cover small-data decision-making, building NBA prop models in Excel, prediction markets, scaling origination, and practical tool workflows.

A heated debate over selling versus betting sharp projection data and how to protect intellectual property. Strategies for monetizing projections: B2B feeds, profit sharing, and prediction‑market trading. Industry moves: exchanges, regulatory shifts, and sportsbook tech splits. Practical tips on deploying models live, AI uses in betting ops, and building partnerships and teams.

In this engaging chat, Adam, known as TheBeagleBets, shares his journey from college dropout to professional gambler, mastering the art of heads-up Sit & Gos and NBA betting. He reveals the emotional ups and downs of a betting career and how balancing family life with gambling can be achieved. Adam discusses the transition to live sports betting, the intricacies of building simulation models, and the challenges of competing in today's market. He also emphasizes the importance of humility and networking in maintaining longevity in the industry.