According to data from July 2025 to mid-March 2026, 🔴 the median return rate for market players is predicted to be negative 8%, while traditional sports betting is only negative 5%.
Small players (transactions under $100) suffer losses up to negative 26.8% in the prediction markets, only those who trade over $500,000 a year can barely make a positive 2.6%. Ordinary users playing across two platforms can make a small profit of 1% in sports betting, but lose 6% in the prediction markets.
On Polymarket, 84% of traders end up losing money, with only a few making significant profits. Kalshi platform analyzed over 72 million transactions, totaling $18.2 billion, and found that ordinary users (takers) who directly place orders lose an average of 1.12% per transaction, while professional market makers (makers) who provide liquidity earn 1.12%.
Normally, traditional sports betting bookmakers would limit or kick out sharp players who consistently win money, with the risk mainly borne by the bookmakers themselves, and the odds faced by ordinary players are generally adjusted, making it relatively fair. The prediction market is completely different, it is open to everyone, professional traders and market makers can stay indefinitely without any restrictions. This creates a clear "harvesting" mechanism: most ordinary users like to directly click "buy", immediately consuming someone else's quote (using up liquidity), while smart market makers place limit orders, slowly providing liquidity and steadily earning the spread. This wealth transfer between market orders and limit orders is particularly evident in Kalshi data—out of 99 different price ranges, ordinary users lose in 80 ranges, while market makers exactly earn.
🔗 Besides the betting transaction structure, the behavior of players also accelerates losses
Prediction market users particularly love buying "YES" contracts, especially those low-probability, long-odds options, thinking "what if it hits big", this optimistic sentiment often leads to overpriced rates. Kalshi data shows that YES long-odds contracts ranging from 1 cent to 10 cents account for 41% to 47% of the volume, far exceeding the proportion of market makers.
Sports and entertainment events are the most likely to make people impulsive, accounting for 72% of Kalshi's total transaction volume, where ordinary users lose even more (2.23 percentage points), while financial events have a much smaller gap due to more rational behavior.
🔴 Additionally, the average bet in the prediction market is $185, compared to only $55 in sports betting, with larger amounts per bet, decisions made impulsively lead to faster money loss.
🔗 But despite losing more, users continue to flock in
Because the prediction market feels like both an investment and a game, with instant feedback and a variety of fresh events, it has a strong sense of excitement. Many people see it as a place to test their judgment, and feel "skilled" after winning occasionally, continuing to increase their bets.
🔴 The platform also has more young people (average age 31, compared to 35 in sports betting), who are more likely to be attracted by the 24-hour, anytime betting mode, treating small money as entertainment expenses.
➡️ Overall, the mechanism, player behavior, and gameplay of the prediction market together form a more efficient "harvesting system" than traditional sports betting.
Sports betting, because it is dominated by bookmakers and has a restricted mode, can better control risks and slow down the losses of ordinary players. This mechanism allows the prediction market to harvest user value more directly and efficiently. The data shows that most people lose faster, yet they continue to participate due to the excitement.
Therefore, if sports betting operators integrate the prediction market mechanism, they are likely to significantly increase profits, such as DraftKings launching the independent product DraftKings Predictions, FanDuel collaborating with CME Group to launch FanDuel Predicts, and Betr reaching a multi-year cooperation with Polymarket in 2026 to embed prediction contracts directly into its super app, covering sports, politics, and cultural events.
These integrations allow sports betting to continue growing in regulatory gray areas or emerging markets, and also enhance overall user lifetime value (LTV) through cross-selling and extending user dwell time.
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