Can Prediction Markets Deliver Sharp Prices When Most Contracts See No Volume and Bots Dominate the Action?

Key Takeaways

• Record June Volume: Kalshi and Polymarket generated more than $50 billion in notional trading volume, with Kalshi alone at roughly $33 billion and 65% market share.
• Thin Markets Prevail: Roughly 70% of Polymarket closed contracts from 2021 through May generated less than $10,000 in trading volume, while more than 45,000 markets recorded no trading at all.
• Bot Dominance: Automated trading accounted for more than 80% of volume in markets under $10,000, per University of San Diego research.
• Regulatory Clash: The CFTC ordered Kalshi to honor Michigan trades despite a state court directive to unwind them, citing risks to market certainty and impartial access.

How can prediction markets deliver reliable price discovery when the majority of contracts sit empty and automated systems drive most of the activity in those thin venues?

The numbers from June tell two stories at once. Kalshi and Polymarket posted their biggest month on record with more than $50 billion in notional trading volume. Kalshi captured roughly $33 billion of that total. That performance pushed its market share to about 65%, up from 57% in May. Annualized, the pace points to an industry on track for more than $500 billion a year. Sports contracts make up roughly half of all activity and more than 85% of Kalshi volume.

Yet the distribution is lopsided. A CNBC analysis of Polymarket closed contracts from 2021 through May showed roughly 70% generated less than $10,000 in reported trading volume. Fewer than 10% reached between $100,000 and $1 million. More than 45,000 markets, nearly 5% of the total, recorded no trading at all. Kalshi showed a similar pattern in its on-chain data. As first reported by Gaming Today, headline volume hides an uneven market.

Record World Cup Volume Concentrated in Marquee Events

The biggest markets, elections, championship games and breaking news, continue to pull in millions or billions. These contracts create fast-moving prices that operators and traders watch closely. Macquarie pointed to infrastructure deals reinforcing that momentum. DraftKings launched its own exchange, DKeX, built on the platform acquired from Railbird Technologies. Polymarket partnered with Liga MX using Genius Sports data. Kalshi is reportedly exploring a funding round that would value the company at nearly $40 billion.

Away from those high-profile contracts, platforms run thousands of smaller markets that appeal to narrow audiences. This creates a tradeoff. Greater variety attracts specialized traders but spreads activity too thin. Sportsbooks have managed similar dynamics for years. When liquidity clusters in a handful of marquee lines, the long tail becomes noise rather than signal.

Bot Dominance Fills the Gap in Sub-$10,000 Markets

Automated trading is common where human participation is scarce. University of San Diego business professor Joshua Della Vedova classified accounts as bots if they made more than 50 trades a day or 1,000 overall. His research found bots accounted for more than 80% of volume in markets under $10,000. Bots proved profitable across market sizes, netting about $1.2 million in shallow markets and roughly $35.1 million in markets above $10 million in volume from November 2022 to February 2026. Della Vedova noted bots still favor larger markets because they offer more trading opportunities.

From the supplier side, this pattern matches what I have seen in data infrastructure builds. Low-volume venues invite automation because humans avoid the wider spreads and capital inefficiency. Atlanta-based trader Logan Sudeith, a former financial risk analyst, favors higher-volume, short-term markets because they are more capital-efficient. Contracts lasting a week or less, often tied to breaking political news, were among the most likely to top $1 million in volume.

Liquidity Mechanics Drive Wider Spreads and Price Swings

Liquidity shapes market behavior. More participants generally produce tighter spreads and easier entry and exit. Economics professor Constantin Bürgi at University College Dublin explained that thinly traded markets see wider price swings because a single trade can move prices more than in heavily traded contracts. Dartmouth economics professor Eric Zitzewitz added that thinner markets carry wider gaps between buy and sell prices, making them costlier for casual traders.

Researchers differ on whether low volume undermines the core promise of aggregating views into accurate forecasts. Evercore ISI strategists, reviewing five years of closed Kalshi and Polymarket contracts, found higher-volume markets tend to produce more reliable probabilities. Only 8% of markets ever reached $1 million in volume. Yale finance professor Theis Ingerslev Jensen argues accuracy hinges more on who is trading than on how much money is involved. Rutgers statistics professor Harry Crane cautioned that the lack of liquidity on its own does not discredit a market signal.

This is where the coverage underemphasizes the operator lens. Kalshi and Polymarket can post record aggregate volume while thousands of contracts remain ghost towns. Sportsbooks integrating these signals for hedging or product features face the practical risk that bot-driven thin markets distort the very probabilities they seek to import. DraftKings DKeX enters this environment with a built-in user base that could concentrate liquidity faster than standalone platforms. The question is whether that concentration simply replicates the same long-tail emptiness in a different wrapper.

CFTC Intervention Highlights Federal-State Friction

The growth unfolds against shifting legal ground. According to reporting by Gambling Insider, the CFTC ordered Kalshi to honor certain Michigan trades despite a state court directive to cancel and refund them. On July 12, Kalshi submitted an emergency rule filing that would have liquidated positions to comply with a June 29 temporary restraining order from the Ingham Circuit Court. The CFTC stayed that rule and directed the exchange to fulfill the trades in accordance with normal practices.

CFTC Chairman Michael Selig stated, “A state cannot force a DCM to violate its obligations, and federal law does not permit a DCM to discriminate against a state’s residents.” He added, “Canceling trades that have already been executed is an unprecedented step that risks a cascading effect on the entire marketplace and undermines the certainty in contracting that is a necessary component of a functioning market.” Kalshi Head of Enforcement Robert DeNault wrote on X, “We are disappointed by this decision and believe it is unfair to Kalshi. We already acted and unwound the trades, as the Michigan court order required us to do.” He added, “We are being put in an impossible position, looking to follow state court orders that may contradict our federal regulatory obligations.”

@ChairmanSelig observed that “Prediction markets are one of the most exciting innovations in financial markets. Yet for too long, the @CFTC has failed to provide guidance for these markets being used by millions of Americans. This ends today.”

The Michigan dispute, including an Aug. 12 geofencing deadline, underscores how regulatory uncertainty can compound liquidity challenges. Traders may hesitate to participate if executed positions risk later unwinding.

Where Liquidity Must Improve for Price Discovery to Scale

The combined coverage from Gaming Today and Gambling Insider surfaces the volume boom and the regulatory clash yet spends less time on the practical mechanics operators need to monitor. Bot profitability in shallow markets is real, but sustained human participation in the long tail remains the missing ingredient for trustworthy signals across thousands of contracts. DraftKings DKeX has an opportunity to test whether an established sportsbook audience changes the concentration pattern.

World Cup-driven momentum offers a forcing function. With sports making up half the activity, the next several months will show whether liquidity spreads beyond the marquee events or remains bottled up. Operators integrating these markets should track bot share, spread width and revision frequency in real time. The data is there. The discipline is in using it to separate signal from automated noise.