Paradigm Latest Leak: Polymarket Trading Volume Inflated by 100%!

Top VC Paradigm’s latest research points out that mainstream data platforms are systematically double-counting trading volume for leading prediction market Polymarket. Researchers found that each Polymarket trade generates two types of OrderFilled events on-chain, but dashboards like DefiLlama and Blockworks sum both, causing the actual trading volume to be overestimated by 2x.

Is the $15 Billion Valuation Built on Inflated Data?

(Source: Storm)

In September this year, Intercontinental Exchange (ICE) invested in Polymarket at a $9 billion valuation, citing $25 billion in cumulative trading volume. Bloomberg reported in late October that the company was seeking a new funding round at a valuation of $12–15 billion. However, if these figures are found to actually be only half of what the public perceives, Polymarket’s leading position and impressive performance could come into question.

Investors typically use several core metrics to evaluate the value of prediction market platforms: total trading volume, daily active users, market depth, and fee income. Of these, trading volume is the most direct and easily comparable metric. When Polymarket showcases its $25 billion in cumulative trading volume, investors compare it to competitors like Kalshi, Augur, or traditional betting platforms. If this number is actually only $12.5 billion, Polymarket’s market dominance would be greatly diminished.

Even more serious is the collapse of the valuation model. Fintech and trading platforms are often valued using trading volume multiples, i.e., “valuation = annualized trading volume × some multiple.” If the trading volume data is cut in half, the reasonable valuation calculated with the same multiple also halves. This means the $15 billion fundraising target might need to be reduced to $7.5 billion—a scale of adjustment significant enough for investors to reconsider the entire deal.

Fee income is similarly affected. If Polymarket’s fee rate is 2% of trading volume, double-counting means actual income is also overestimated. Investors relying on inflated income projections may face significant performance gaps in the future. This data distortion not only affects current fundraising but could also prompt invested institutions to question valuations from previous rounds.

The Technical Double-Counting Mechanism Revealed by Paradigm

(Source: Storm)

Paradigm researcher Storm found that each Polymarket trade generates two types of OrderFilled events on-chain: one for the maker and another for the taker. However, these two records of the same transaction are “summed” by mainstream dashboards like DefiLlama, Blockworks, and Allium, resulting in trading volume being doubled.

(Source: Etherscan)

Storm gave a real-world example: a trader buys YES tokens for $4.13, but two OrderFilled records of $4.13 each appear on-chain, making the dashboard record $8.26. He stated this isn’t malicious wash trading, but a redundancy inherent in the prediction market’s data structure, easily misleading analysts to believe these are two independent trades.

Three Main Sources of Polymarket’s Double-Counting

Redundant Event Design: Each matched order generates dual OrderFilled events, separately recording the same trade from the maker and taker perspectives.

Analytical Tool Flaws: Platforms like DefiLlama use simple summing logic without recognizing the need to deduplicate related events.

Prediction Market Complexity: Trades involve complex forms such as swaps, splits, and merges, with interwoven data layers that make it difficult for generic blockchain explorers to identify relationships.

Storm emphasized that because Polymarket’s trading forms are far more complex than traditional DEXs, the interwoven data layers make it hard for regular blockchain explorers to identify relationships between events, increasing the risk of analyst miscalculation. This problem isn’t unique to Polymarket—the entire prediction market industry may face similar issues with statistical standards.

Industry Standards Debate and Paradigm’s Dual Motivation

(Source: Storm)

Paradigm’s official statement pointed out that mainstream data platforms generally overestimate Polymarket’s actual trading volume and recommended that prediction markets use “one-sided volume” as the standard, such as only counting taker-side trades. The statement specifically emphasized that the article is not about whether there was intentional exaggeration of trading volume, but to enable genuine comparison across platforms and to establish a consistent, transparent market statistics baseline.

However, Paradigm’s motivation is not entirely neutral. The VC is also an investor in Polymarket’s competitor Kalshi, so the motive behind publishing this research is self-evident. Kalshi is the first US-based, CFTC-approved compliant prediction market platform and has long sought to challenge Polymarket’s dominance among crypto-native users. By exposing Polymarket’s data issues, Paradigm is effectively cleaning up the competitive environment for its own portfolio company.

Storm stated that prediction markets are rapidly becoming a major category in financial markets, and as the industry matures, unified and objective data standards are increasingly necessary to prevent erroneous data from shaping the industry narrative. While this point is valid, the context of investor conflicts of interest inevitably raises questions about objectivity. Regardless, the research does reveal a real technical issue, though the identity of the whistleblower adds a layer of commercial competition to the event.

What data interpretations does this double-counting affect? Storm pointed out that this error inflates two core metrics: “notional volume” and “cashflow volume.” Notional volume is the primary reference for investors evaluating market size, while cashflow volume reflects the strength of actual capital flows. Both being overestimated by 2x means Polymarket’s market share, liquidity depth, and fee income projections may all need to be recalibrated.

For potential investors currently conducting due diligence, this is a major red flag. They need to re-examine all trading volume-based valuation models and require Polymarket to provide audited historical data using the one-sided volume standard. This data correction process could delay fundraising by several months or even cause some investors to walk away from negotiations. More broadly, the entire prediction market industry needs to establish a unified trading volume calculation standard, or cross-platform comparisons will always be distorted.

Dual Pressures of Competition and Regulatory Compliance

The timing of this data controversy is intriguing. Polymarket gained major attention this year for accurately predicting the US election outcome, with trading volume and user numbers surging. However, its unlicensed operations have always been a regulatory concern. In contrast, Paradigm-backed Kalshi holds CFTC-approved compliance, allowing it to legally operate a political prediction market in the US.

This research was published just as Polymarket is conducting a major fundraising round, making it hard not to suspect the possibility of competitive pressure. However, regardless of motive, the technical facts cannot be denied. Blockchain data is public and verifiable, and anyone can reproduce Storm’s analysis. For platforms like DefiLlama to maintain credibility, they must quickly correct their calculation methods and revise historical data.

For Polymarket, the best response is to proactively acknowledge the issue and provide corrected data. Taking a defensive stance or questioning Paradigm’s motives would only increase market doubts about its transparency. As an industry reliant on accurate data and user trust, any accusations of data manipulation or opacity could be fatal for prediction markets.