Both try to forecast the future. Here's how they actually work — and when each is more useful.
How the two methods differ on the fundamentals.
Polls
Ask people what they will do
Prediction Markets
Ask people to bet on outcomes
Polls
~1,000–1,500 likely voters
Prediction Markets
Thousands of traders worldwide
Polls
Free to answer
Prediction Markets
Real money at stake
Polls
Days to weeks
Prediction Markets
Real-time (seconds)
Polls
Margin of error ±3%
Prediction Markets
Implied probability (price)
Polls
Media outlets, campaigns
Prediction Markets
The traders themselves
Polls
Social desirability pressure
Prediction Markets
Lose real money if wrong
Polling relies on random sampling of the electorate, likely voter screens, weighting to match demographics, and reporting a margin of error. Methods have improved after the high-profile misses in 2016 and 2020, but structural challenges remain.
What the research shows. Wolfers & Zitzewitz (2004, Journal of Economic Perspectives) found prediction market forecasts are “typically fairly accurate” and outperform most moderately sophisticated benchmarks. Rothschild (2009, Public Opinion Quarterly) showed debiased prediction market forecasts outperformed debiased polls for US Presidential and Senate races, particularly early in the cycle. Neither method is perfect — both exhibit systematic biases that can be partially corrected.
National polls underestimated certain voter groups, leading to systematic swing-state errors. Methodology improvements are ongoing, but the challenges haven't fully resolved.
Low-volume markets for down-ballot or niche races may have very few active traders, which reduces reliability and makes prices easier to move.
Polls can miss enthusiasm gaps and non-response bias. Markets can be gamed by large players and reflect trader demographics, not voter demographics.
