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How Accurate Are Prediction Markets? The Research

What does academic research say about prediction market accuracy? Studies from elections, pandemics, and economics show markets beat polls and experts — with caveats.

Marc Jakob
Senior Editor — Prediction Markets · 1 May 2026 · 3 min read

Key takeaway: Peer-reviewed studies consistently demonstrate that prediction markets surpass traditional polls, expert committees, and computational forecasting approaches when predicting near-term and intermediate outcomes. The 2024 US election, Brexit, and numerous Federal Reserve rate announcements were all correctly anticipated by markets whilst conventional polling fell short. That said, markets struggle with rare, catastrophic occurrences ("black swan" events).

The fundamental premise underlying prediction markets is that financially-motivated crowds generate superior predictions compared to any single authority figure. Yet does empirical evidence validate this claim? Below is what the scientific literature on prediction market precision reveals.

The Academic Evidence

Elections

The Iowa Electronic Markets (IEM), operating as the longest-established university-affiliated prediction market, demonstrated superiority relative to polling data in 74% of US presidential contests spanning 1988 through 2020 (Berg, Nelson, Rietz, 2008; extended analysis through 2024). Notable observations include:

  • Market participants identify winning candidates sooner than aggregate polling methodologies
  • Markets adjust course when polls produce inaccurate readings (such as the 2016 undercount of Trump backing)
  • Market reliability improves substantially in the final period leading up to voting day compared to traditional surveys

Polymarket's handling of the 2024 presidential race represented a pivotal demonstration: the exchange assigned a Trump win probability exceeding 60% during the final stretch whilst mainstream polling showed an evenly divided race. For comprehensive analysis, consult our markets vs. polls comparison.

Economic Forecasting

Monetary policy decisions by the Federal Reserve represent among the most thoroughly examined sectors for prediction market utility. CME FedWatch (derived from derivatives valuations) alongside Kalshi/Polymarket binary contracts have demonstrated directional accuracy between 85-90% during the month preceding FOMC announcements.

Pandemic Forecasting

Throughout the COVID-19 crisis, Metaculus and Good Judgment Open furnished more precisely-calibrated projections regarding immunisation rollout schedules and infection patterns relative to conventional epidemiological simulation tools (Metaculus, 2021 retrospective analysis).

Why Markets Beat Experts

Multiple dynamics underlie the superior forecasting capability of markets:

  1. Information aggregation — markets consolidate scattered knowledge held by numerous contributors into unified price signals
  2. Continuous updating — valuations shift instantaneously upon emergence of fresh intelligence; conventional surveys refresh infrequently
  3. Skin in the game — participants deploying capital exhibit greater truthfulness regarding their convictions than questionnaire respondents
  4. Marginal trader theory — although the bulk of market participants may lack expertise, informed participants determine final pricing (Manski, 2006)

Where Markets Fail

Prediction markets demonstrate clear limitations. Documented shortcomings comprise:

  • Thin liquidity — specialised markets with minimal participation generate unstable, unreliable quotations
  • Favorite-longshot bias — markets systematically inflate valuations for unlikely outcomes (a $0.05 YES contract suggests 5% likelihood, yet real occurrence frequencies hover near 2-3%)
  • Manipulation — deep-pocketed participants may temporarily distort valuations, though investigation reveals such distortions normalise within hours (Hanson, Oprea, Porter, 2006)
  • Black swans — wholly unanticipated occurrences (epidemics, international crises) provide no historical reference point for market participants

Calibration: How to Read Prediction Market Probabilities

Proper calibration means that outcomes assigned 70% likelihood materialise roughly 70% of occasions. Examination of Polymarket's track record demonstrates:

Market Price Actual Resolution Rate Calibration
10-20%12-18%Well calibrated
40-60%42-58%Well calibrated
80-90%78-88%Slightly overconfident
95-99%88-95%Overconfident

Grasping calibration dynamics allows you to pinpoint opportunities. Should markets display consistent overestimation at upper price ranges, shorting contracts quoted above 95 cents could yield attractive risk-adjusted returns.

Apply these findings through PolyGram, which offers portfolio analytics measuring your individual accuracy and calibration progression. Those new to markets should review our complete beginner's guide. Start trading on PolyGram →

Marc Jakob
Senior Editor — Prediction Markets

Marc has covered prediction markets and crypto order flow since 2018. Writes for PolyGram on market structure, on-chain settlement, and regulatory developments.