MLB Prediction Market Traders
MLB prediction markets benefit from the sport's deep statistical tradition — sabermetrics, pitch tracking, and advanced batting metrics provide quantitative traders with rich data for modeling game outcomes. With 162 regular-season games per team, MLB offers the highest volume of tradable events in North American sports. Platforms like Polymarket, Kalshi, and Probable Markets each offer baseball contracts throughout the season. This page ranks the top 20 MLB traders by category P&L.
Top MLB Traders
Ranked by category-specific P&L within mlb markets.
Frequently Asked Questions
Who are the best MLB prediction market traders?
The top MLB traders are ranked on this page by category P&L. Successful MLB traders often leverage sabermetric models that incorporate starting pitcher matchups, bullpen rest, park factors, and platoon splits to identify mispriced games.
Why is MLB good for prediction market trading?
MLB's 162-game season provides the highest sample size of any major sport, allowing statistical models to converge on accurate probabilities more quickly. The dominance of starting pitching in game outcomes also makes individual games more predictable when pitcher matchup data is properly incorporated.
What MLB data matters most for prediction markets?
Starting pitcher quality (FIP, xFIP, SIERA), bullpen availability, park factors, weather conditions, and lineup construction are the most impactful variables. Late lineup changes and bullpen usage from the previous series can create edge opportunities.
How liquid are MLB prediction markets?
Regular season MLB markets have moderate liquidity, with playoff and World Series markets seeing significantly higher volume. Marquee matchups and rivalry games tend to attract more trading activity than mid-week series between small-market teams.
Can sabermetrics give an edge in baseball prediction markets?
Yes. Traders who build models incorporating advanced metrics like Stuff+ for pitchers, Barrel% for hitters, and sprint speed for baserunning often identify mispriced markets, especially early in the season when sample sizes are small and public perception lags statistical reality.
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