TL;DR
- Retail prediction market users face deeper median losses than sportsbook bettors.
- Professional traders profit from retail flow in prediction markets without restrictions.
- Younger users adopt prediction platforms while traditional sportsbook downloads decline.
Retail traders participating in prediction markets record deeper losses than users betting through traditional sportsbooks, according to new data examining performance since mid-2025. The findings highlight structural differences between both environments, where liquidity composition and counterparty sophistication shape outcomes for smaller accounts. Median returns for retail prediction market users sit near −8%, compared with roughly −5% for sportsbook bettors, indicating a harsher environment for inexperienced traders.
Research compiled by Citizens JMP draws on transaction-level analytics from Juice Reel and separates participants by trading volume. Larger accounts display positive returns, while nearly every smaller cohort posts losses.
Traders exceeding $500,000 in prediction market activity achieve a median return near +2.6%. By contrast, users operating with minimal capital experience steep declines, with accounts under $100 recording losses approaching −26.8%.
However, performance among sportsbook bettors also trends negative. No volume bracket generates consistent profits, yet declines appear less severe. High-volume sportsbook bettors above $500,000 show a median loss around −0.6%, while the smallest accounts fall near −29.3%.
Even with universal losses, prediction markets produce sharper disparities between professional participants and casual users. Consequently, capital concentration becomes a decisive factor shaping profitability.
Structural mechanics explain much of the divergence. Sportsbooks manage risk internally and frequently restrict or remove successful bettors. Such filtering limits exposure to highly informed participants. Prediction markets operate differently.
Platforms allow profitable traders to continue operating freely, which increases the presence of professionals, quantitative traders, and liquidity providers. Retail participants therefore face counterparties with deeper capital and stronger information advantages. As a result, losses accumulate faster for less experienced users.
Professional bettors participating in a recent call hosted by Citizens JMP described prediction markets as appealing precisely because retail flow provides liquidity. When uninformed traders place directional bets, sophisticated participants capture value on the opposite side. Such dynamics mirror financial markets where institutional actors often exploit pricing inefficiencies created by smaller investors.
Younger users gravitate toward prediction platforms
Despite weaker retail performance, prediction platforms attract younger demographics and strong download growth. Data referenced in the report shows about 24% of users on Kalshi fall under age 25, with a median age near 31.
By comparison, only about 7% of users on DraftKings and FanDuel belong to the same age bracket. Median user age on traditional sportsbooks sits closer to 35, indicating a generational gap in adoption.
Sensor Tower data cited in the research shows DraftKings and FanDuel downloads declining 18% and 13% year over year between September 2025 and February 2026. Over the same period, Kalshi recorded approximately 6.3 million downloads. Growth in younger users suggests prediction platforms capture attention early, potentially shaping future betting behavior.
Gaming executives downplay revenue risk for established sportsbooks. Leadership commentary compiled from earnings calls indicates limited direct impact. Executives argue prediction markets do not materially reduce existing customer activity.
Estimates compiled by Citizens JMP place potential revenue effects near 5%, suggesting moderate overlap between user bases. Consequently, prediction platforms appear less likely to pull established bettors away from sportsbooks.
Prediction markets generate excitement yet fail to function as reliable wealth-building tools for most individuals. Data across volume tiers shows consistent negative returns for smaller accounts. Professional traders and market makers absorb much of the value generated by uninformed order flow. Such structure parallels zero-sum trading environments where informed participants extract profits from less experienced traders.
Ultimately, performance metrics suggest caution. Median losses remain deeper in prediction markets, and only high-volume participants achieve consistent gains. At the same time, demographic trends show younger users gravitating toward prediction platforms, indicating sustained growth in adoption.
Retail traders entering prediction markets encounter sophisticated counterparties, tighter pricing, and thinner informational edges. As participation expands, understanding structural differences between sportsbooks and prediction markets becomes essential for evaluating risk.
