Investor Due Diligence in the Age of Wash Trading and Double-Counting in Crypto Prediction Platforms

The rise of crypto-based prediction markets has captivated investors and technologists alike, promising a new frontier for aggregating collective intelligence about future events. Platforms like Polymarket, Gnosis, and Augur have attracted billions in trading volume, with some, like Polymarket, achieving valuations exceeding $9 billion according to a 2025 report. However, beneath the surface of this growth lies a critical challenge: data integrity. Recent studies and industry critiques reveal that wash trading and double-counting practices have distorted key metrics, undermining the reliability of these markets. For investors, this raises urgent questions: How can one distinguish genuine market activity from artificial noise? What due diligence is required to navigate these risks while capitalizing on the sector's potential?

The Scale of the Problem: Wash Trading and Double-Counting

Wash trading-where users rapidly buy and sell the same contracts among colluding accounts-has become a systemic issue in crypto prediction markets. A 2025 Columbia University study found that 25% of Polymarket's trading volume over three years was artificially inflated, with peaks reaching 60% of weekly volume in December 2024 according to research. Sports and election markets were particularly vulnerable, with some weeks showing over 90% of trades flagged as inauthentic according to a study. The study attributes this to Polymarket's pseudonymous, fee-free structure, which allows users to create multiple wallets and engage in self-dealing without financial friction according to industry analysis.

Compounding this issue is double-counting, a technical flaw in how on-chain data is aggregated. Paradigm researcher Storm Slivkoff highlighted that Polymarket's smart contracts emit redundant "OrderFilled" events for each trade, leading dashboards to inflate volume by nearly 100% according to a technical analysis. For example, a $4.13 trade is recorded as $8.26 in volume when both maker and taker events are summed according to on-chain data. While not intentional manipulation, this error has distorted market perceptions, particularly in a sector where volume is a proxy for liquidity and legitimacy according to market analysis.

Platform-Specific Risks and Mitigations

The risks vary across platforms. Polymarket, despite its growth, remains the most exposed due to its decentralized, pseudonymous design and lack of KYC/AML safeguards according to industry research. In contrast, Kalshi, a regulated competitor backed by the CFTC, has implemented market surveillance systems and identity verification, reducing the feasibility of wash trading according to financial reports. By October 2025, Kalshi's sports betting volume ($1.1 billion) had already outpaced Polymarket's ($350 million), suggesting that regulatory compliance may offer a competitive edge according to market analysis.

Gnosis and Augur, pioneers in decentralized prediction markets, faced similar challenges in their early years. High Ethereum gas fees and complex user interfaces limited liquidity, but Layer 2 solutions (e.g., Polygon, Base) have since reduced costs and improved accessibility according to platform reports. However, these platforms still rely on stake-based reporting systems to mitigate double-counting, which, while effective, require active participation from token holders to ensure accurate outcomes according to community discussions.

Investor Due Diligence: Navigating the Noise

For investors, the key to navigating these risks lies in rigorous due diligence. Here are three critical steps:

1. Scrutinize Platform Structure:
   Platforms with transaction fees, identity verification, and regulatory oversight (e.g., Kalshi) are less susceptible to manipulation. Conversely, fee-free, pseudonymous platforms (e.g., Polymarket) require deeper scrutiny of on-chain data and wallet activity according to a 2025 study.

2. Analyze Volume with Caution:
   Given the prevalence of double-counting, investors should focus on one-sided volume metrics (e.g., taker or maker volume) rather than total notional volume according to market analysis. Tools like Dune Analytics or on-chain explorers can help dissect transaction patterns and identify anomalies.

3. Assess Incentive Alignment:
   Platforms incentivizing genuine participation (e.g., token airdrops tied to long-term engagement) are less likely to attract speculative wash trading. Conversely, short-term incentives (e.g., airdrops based on trading volume) may encourage artificial activity according to economic research.

Opportunities Amid the Risks

Despite these challenges, prediction markets represent a compelling opportunity. The sector's total trading volume reached $27.9 billion in 2025, driven by demand for real-time insights on elections, sports, and macroeconomic trends according to market data. For investors willing to navigate the data integrity hurdles, platforms with robust governance, transparent metrics, and regulatory alignment (e.g., Kalshi) offer a path to capitalize on this growth while minimizing exposure to manipulation.

Conclusion

The crypto prediction market sector is at a crossroads. While wash trading and double-counting have eroded trust in key metrics, they also highlight the need for innovation in governance and transparency. For investors, the path forward requires a blend of technical rigor and strategic patience. By prioritizing platforms with structural safeguards and adopting a critical lens toward volume metrics, investors can position themselves to benefit from the sector's long-term potential without falling victim to its current pitfalls.