7 Myths About Prediction Markets That Need Debunking

by
Alisa Davidson

Printed: October 15, 2025 at 12:00 pm Up to date: October 13, 2025 at 9:59 am

by Ana

Edited and fact-checked:
October 15, 2025 at 12:00 pm

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Prediction markets are sometimes misunderstood—even derided—by critics who cling to outdated assumptions. 

In 2025, as these markets acquire traction in crypto, finance, and public coverage, many myths persist. 

Under are simply seven myths about prediction markets that deserve a re-examination.

“Prediction markets are simply playing”

That is maybe the most typical of all of the myths about prediction markets. Sure, prediction markets permit betting on outcomes, however the intent, incentives, and regulatory framing typically set them aside. 

Platforms like Kalshi within the U.S. function below federal regulation (by way of the CFTC) and supply occasion contracts as monetary devices, not pure video games of probability.

Statistically, prediction markets have outperformed public polls in a number of U.S. elections. Harry Crane’s research evaluating PredictIt and FiveThirtyEight discovered that markets have been persistently nearer to closing outcomes. Crane emphasised that polls seize “sentiment,” whereas markets search “accuracy and reality.”

So, the parable fails as a result of these markets are about greater than leisure—they’re instruments for forecasting threat, hedging uncertainty, and revealing aggregated perception backed by actual stakes.

“They’re straightforward to control”

Detractors warn that low-liquidity, insider trades, or coordinated manipulation can distort market costs. Whereas no system is ideal, many platforms construct in countermeasures: liquidity incentives, market-maker subsidies, stake weighting, and in regulated circumstances, oversight.

For instance, just some U.S. states allow contracts on sports activities occasions. Kalshi has confronted authorized pushback in states like Massachusetts and New Jersey, however in a number of courts the platform has defended contracts below federal oversight. These authorized rulings recommend confidence that the design and laws can mitigate manipulation.

Knowledgeable observers argue that true manipulation is more than likely solely when markets are skinny and localized. When liquidity, transparency, and regulatory compliance enhance, these dangers decline considerably.

“Solely political or sports activities followers use them — not helpful for finance or governance”

Probably the most widespread myths about prediction markets is that it doesn’t transfer past leisure. Actual-world governance, company planning, DAO choices, and threat administration are more and more woven into prediction markets’ use circumstances.

Kalshi affords markets on macroeconomic and regulatory outcomes, not simply elections or sports activities. Crypto platforms like Polymarket additionally host assorted occasion varieties, spanning finance, regulation, and international affairs. 

These permit establishments and decentralized communities to gauge chance of regulatory modifications or governance votes.

Researchers affirm that markets can produce forecasts which are “actionable for establishments,” particularly after they wish to anticipate taxes, regulation, or authorities coverage modifications. The information exhibits that such markets typically reply quicker and with extra nuance than conventional expert-derived forecasts.

“They produce black-box alerts — not explainable”

It’s typically believed that as a result of prediction markets mixture so many inputs, they turn out to be opaque. Quite the opposite, many markets are constructed on clear mechanisms: each commerce is public, worth actions are traceable, and guidelines of settlement are recognized upfront.

Polymarket, as an illustration, settles most markets based mostly on verifiable information sources, with dispute decision mechanisms clearly documented. Kalshi, being regulated, has to adjust to guidelines about disclosures and contract legal guidelines.

Harry Crane famous that prediction markets present the “weight of perception” in public kind, as a result of stakeholders should threat actual funds. That visibility creates accountability. 

Whereas markets don’t at all times reveal why somebody made a commerce, the collective end result is “seen in commerce quantity, costs, and shifts,” serving to customers to interpret sign energy.

“Prediction markets are unlawful or will at all times be banned”

Regulation issues, sure—however legality is way from uniform, and lots of prediction markets already function below clear regulatory constructions. For instance, Kalshi has managed to get rulings in favor of its sports activities and election-event contracts in some U.S. states, and courts have blocked sure state-imposed makes an attempt to deal with such contracts as unlawful playing in different jurisdictions.

The CEO of Kalshi has additionally argued that its contracts for sporting occasions shouldn’t be categorised as playing as a result of the enterprise doesn’t acquire from its gamers’ losses, which makes a notable distinction below U.S. legislation.

So, legality is just not a uniform prohibition—it will depend on jurisdiction, contract design, and regulatory standing. With the suitable licensing, compliance, and readability, prediction markets can and do function lawfully.

“Markets are nugatory when liquidity is low”

Low liquidity does make markets much less dependable—however once more, that doesn’t imply they “fail” universally. Many platforms use instruments to mitigate the issue: liquidity suppliers, incentive packages, AMMs (automated market makers), and cross-platform aggregation.

Proof means that markets with greater liquidity and fewer payment restrictions are typically extra correct. Crane noticed that Polymarket’s smaller payment construction and better liquidity positioned it forward of PredictIt in forecasting effectivity in current election cycles.

Even when liquidity is low, markets can nonetheless present directional or pattern alerts moderately than exact chance values. For a lot of customers (protocols, funds), that is sufficient to transfer choices.

“Prediction markets at all times out-perform specialists and fashions”

One of many extra harmful myths about prediction markets. Sure, markets are highly effective, however not infallible. They typically outperform polls or easy fashions in long-horizon political or regulatory forecasting, however in near-term or extremely complicated technical domains, skilled fashions can excel.

A examine evaluating PredictIt markets and printed fashions for U.S. battleground states within the 2020 election confirmed that markets carried out higher a number of months out, however because the election drew nearer, model-based polling and statistical fashions generally grew to become extra correct. The hybrid common typically beats every element alone.

Thus, a extra nuanced view: prediction markets are greatest utilized in mixture with fashions and skilled perception. They shine for long-horizon, macro, regulatory, or coverage questions, whereas skilled fashions would possibly assist with technical forecasting the place information and area data dominate.

The Actuality of Prediction Markets

Many myths about prediction markets are simply not true: they’re not purely playing, not inherently manipulable, not confined to politics or sports activities, nor eternally unlawful. 

When well-crafted and correctly regulated, they exhibit greater accuracy, transparency, probabilistic alerts, and real-time adaptability—all of which conventional forecast strategies discover laborious to match.

As regulation, design, and adoption enhance, prediction markets can go from being little curiosities in 2025 to being the important thing forecasting infrastructure, shaping insurance policies and governance and finance, and rather more.

Alisa, a devoted journalist on the MPost, focuses on cryptocurrency, zero-knowledge proofs, investments, and the expansive realm of Web3. With a eager eye for rising tendencies and applied sciences, she delivers complete protection to tell and have interaction readers within the ever-evolving panorama of digital finance.

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