Unchained Podcast: How to Trade Prediction Markets Without an Opinion on the Event (Ep. 979)

Host: Laura Shin
Guest: Marcus Thielen (CEO, 10X Research)
Date: December 13, 2025

Episode Overview

This episode delves into the rapidly growing world of crypto-based prediction markets. Laura Shin and guest Marcus Thielen analyze the surge in popularity and volume of platforms like Polymarket and Kalshi, the competitive landscape as new entrants (e.g., Gemini, Robinhood) appear, and the complex but lucrative strategies for trading prediction markets—even without having a strong opinion on the actual event being bet on. Marcus explains a variety of risk-managed, analytical approaches, highlighting how sophisticated traders can structure arbitrage opportunities, harvest spreads, and utilize probability imbalances—all while remaining agnostic to the underlying event.

Key Discussion Points & Insights

1. Current State and Growth of Prediction Markets

• Market Traction & User Growth

  • Both Polymarket and Kalshi are experiencing skyrocketing volumes (≈$1B/week), with users increasing from ~70K to 250K weekly (04:21).
  • "It's almost like as when Bitcoin started to decline... that's when really the volumes and the activity started to increase." — Marcus Thielen [04:37]
  • Comparisons to more mainstream platforms (e.g., Robinhood, Coinbase) show a notable rise in attention.

• Regulatory and Competitive Backdrop

  • Kalshi and Polymarket's intense competition, escalating with Polymarket’s US entry.
  • New entrants: Gemini (via "Gemini titan"), Robinhood (with Susquehanna), and Limitless.
  • Regulatory approvals (e.g., Gemini’s US license) fueling further competition.

• Market Composition

  • 90% of current prediction market volume is sports betting; crypto or macro bets remain niche but are growing.

2. Why Prediction Markets Are Different from Crypto Markets

• Structure & Fundamentals

  • Prediction markets are "exotic option trading strategies... about understanding the probability and being fast with the news.” — Marcus Thielen [08:39]
  • Trades are typically binary event contracts (“yes/no”), versus the open-ended narrative-driven trading in crypto assets.
  • Market structure often mirrors traditional limit order books; "impatient" takers vs. patient market makers.

• Liquidity and Market Making

  • Both markets require sophisticated liquidity provisioning, but there are essential differences in execution, sizing, and risk dynamics.

3. Assessing the Leading Players: Polymarket vs. Kalshi

• Core Differences

  • Polymarket: Crypto-native, faster onboarding (non-US onboarding takes <2 mins; US has a huge waitlist), easy crypto funding. (12:49)
  • Kalshi: US focus, heavier regulatory processes, potentially better revenue model via fees.

• Volume & Valuations

  • At the time of recording: Polymarket leads in monthly visitors (~19M vs. Kalshi's 5M) [17:31].
  • Valuations are comparable ($12B vs. $11B), but market share fluctuates—sports seasons and US entry play a role.

• Market Structure

  • Both use limit order books. Fluidity, fees, and regulatory approaches affect user experience but differences are narrowing.

4. Token Launches and Incentivization

• Polymarket’s Forthcoming Airdrop

  • Polymarket will launch a POLY token via an airdrop, “already confirmed by the CEO and head of growth,” seen as a strategy to cement user loyalty and boost engagement (23:58).
  • "Everybody who holds the token will suddenly become... a marketing person for the protocol." — Marcus Thielen [25:40]
  • Historical examples (e.g., BNB, OKX, Whitebit tokens) shown to underpin growth and user buy-in.

• Other Platforms’ Token Prospects

  • Thielen doubts Kalshi will issue a token, as being "crypto-native" is key to token utility and success.

5. Trading Prediction Markets: Risks and Frameworks

• Event Contract Structure

  • Predictive contracts are more akin to "barrier options" with definitive end dates—accuracy and timing are both crucial (33:50).

• Risk Profiles

  • Probability-based pricing means the risk is different (and often more finite) than with perpetual crypto holdings.
  • “You need to get the timing right.” Missed deadlines = zero payout, even if event occurs shortly after expiry.

6. Marcus Thielen’s Trading Strategies — No Event Knowledge Needed

• Thielen has developed a suite of techniques to "trade probability, not events." Key strategies include [40:12–62:48]:

  a. Cross-Market Arbitrage

  • Exploit pricing differences for identical events across platforms (e.g., Polymarket vs. Kalshi) [40:41].
  • Requires accounting for fee and withdrawal friction, but low risk if executed carefully.

  b. Endgame Sweep / Late-Stage Arbitrage

  • Capture “obvious” mispricings late in contract life; e.g., betting against mathematically impossible outcomes for small but near-certain yield [43:33].
  • “The probability was really near zero. Mathematically it's impossible, but you can still pick up the 4% by fading this trade.” — Marcus Thielen [39:16]

  c. Time Decay Capture

  • Bet against high volatility-priced markets as expiration approaches, harvesting slow, reliable returns [44:56].

  d. Maker Spread Harvesting

  • More advanced: Provide liquidity and collect bid-ask spreads, especially during volatility spikes, akin to market making [45:53].

  e. Probability Compression Play

  • Identify and exploit over/underpriced probabilities, particularly after key news or market shifts (e.g., FOMC meetings, political decisions) [49:55].

  f. Avoiding Long Shots

  • Steer clear of low-probability, high-payout bets; statistic: “60% of all the money that is lost is really lost with these...long shot bets.” [52:12]
  • Focus instead on “lots of small wins”—higher probability, lower risk.

  g. Liquidity Imbalance/Follow Whale Flow

  • Track large or consistently successful traders ("whales") on-chain, essentially copy trading the sharpest players [55:01].
  • Easier on Polymarket (public wallet activity) than Kalshi.

  h. Price Sensitivity Screening

  • Compare implied probabilities/prices on Polymarket prediction contracts to institutional options (e.g., Deribit) and exploit retail euphoria or mispricing [57:14].

  i. Conditional Hedging

  • Use prediction markets to hedge real-world risks when traditional derivatives are unavailable or impractical [60:31].

  j. Event Calendar Positioning

  • Structure positions around known macro or political events (e.g., Fed meetings, elections), either directly or as part of cross-instrument arbitrage [61:33].

7. Professionalization, Gamification, and Future Outlook

• Growing involvement of professional traders and market makers, likened to the evolution of Bitcoin/crypto markets.
• “Professional traders... really seem to focus more on the higher probability trades that really [go] from...high probability to a guaranteed probability.” [52:48]
• The wisdom of the crowd is less important than the “wisdom within the crowd”—emphasizing the edge held by top performers [55:01, 63:38].
• Expectation: As platforms mature, arbitrage opportunities will narrow, but market sophistication (and competition) will rise.

Notable Quotes and Memorable Moments

• On Crowd Wisdom:
  "It's not the wisdom of the crowd, it's the wisdom within the crowd. Because within the crowd there will be some large players... who might have an edge in a certain category." — Marcus Thielen [55:05]

• On Arbitrage Opportunities:
  “If the odds are very different on one [platform], you potentially can hedge them out on another. These are like very low-risk...we rank them…from lowest risk to highest risk.” — Marcus Thielen [40:41]

• On Avoiding Long Shots:
  "60% of all the money that is lost is really lost with these, you know, long shot bets..." — Marcus Thielen [52:12]

• On Professionalization:
  "There's more and more professional traders looking at these markets and really pricing it from a probabilistic viewpoint." — Marcus Thielen [63:38]

Important Timestamps

• [04:21] – State of prediction market adoption and growth statistics
• [08:39] – Comparing prediction markets and crypto trading structures
• [12:49] – Polymarket vs. Kalshi: onboarding, liquidity, business models
• [17:31] – Latest volume/user data (Polymarket vs. Kalshi)
• [23:58] – Polymarket’s planned POLY token airdrop and its likely impact
• [33:50] – How prediction market risk differs from regular crypto trading
• [37:04] – Example trade: Harvesting 4% in a Polymarket ETF bet
• [40:41]–[62:48] – Deep strategy walkthrough: arbitrage, endgame, spreads, copy trading, and more
• [52:12] – The dangers of “long shots”
• [55:01] – “Follow whale flow” and tracking expert traders
• [63:38] – The growing role of pros and professionalization of markets

Overall Takeaways

• Prediction markets are becoming a major force in trading—both as entertainment and as professional, probability-based venues.
• Arbitrage and high-probability, analytics-driven trading are superior to betting on unknown outcomes or low-probability ‘lottery tickets’.
• Copy trading, price sensitivity screening, and endgame arbitrage are accessible, repeatable ways to reliably profit as the space grows.
• Polymarket and Kalshi are front-runners but the landscape is evolving rapidly, with token launches and regulatory shifts shaping the next wave of competition.

For new entrants, the episode is a treasure trove of practical strategies and industry insight—proof that in the modern prediction market, you can profit handsomely even without a strong opinion on the event itself, simply by trading statistical edges and structural inefficiencies.