ForesightFlow: Real-Time Detection of Informed Trading in Decentralized Prediction Markets

Decentralized prediction markets such as Polymarket aggregate dispersed beliefs into continuously updated price signals, but their on-chain transparency and pseudonymous participation also make them an unusually fertile environment for informed trading on material non-public information. Recent empirical work has documented hundreds of millions of dollars in anomalous profits on Polymarket between 2024 and 2026; existing detection approaches are almost exclusively post-hoc and offer no actionable signal during the window when informed flow is actually moving prices.

We propose ForesightFlow, a real-time detection framework that combines classical microstructure measures of informed trading — adapted to the discrete, bounded structure of binary outcome markets — with on-chain wallet features unique to decentralized platforms. We introduce the Information Leakage Score (ILS), a label generator that quantifies how much of a market's terminal information move was priced in before the corresponding public news event, and show that ILS admits a clean interpretation in terms of the Murphy decomposition of the Brier score. As an empirical anchor we release the ForesightFlow Insider Cases (FFIC) inventory, a curated validation set mapping eight publicly documented insider episodes to concrete Polymarket market identifiers. The historical-backfill stage of the data pipeline is operational, indexing 911,237 markets (865,725 resolved) and 17.9 million trades across 10,410 markets above the $50K volume cutoff at which subgraph trade history becomes reliably available.

A pilot empirical study tightens the methodology in three ways: a resolution-anchored proxy for T_news does not separate event-resolved markets from a matched control population; high ILS on high-consensus markets reflects a formula edge effect; and the proxy-based ILS distribution is not robust to anchor choice. We specify three operational scope conditions for ILS — restriction to event-resolved markets with substantive uncertainty at T_open, recovery of article-derived T_news, and a robustness check across multiple anchor offsets. An attempt to scale to the full FFIC inventory revealed that documented insider cases are systematically deadline-resolved ("Will event X occur by date Y?"), falling outside the original ILS scope. We extend the score to a deadline-ILS variant anchored to the underlying event timestamp and apply the extension to the 2026 U.S.–Iran conflict cluster. On the cleanest applicable case, the deadline-ILS shifts from −0.331 at the resolution-anchored proxy to +0.113 at the article-derived event timestamp, demonstrating that the extension distinguishes signal from proxy artefact. System code, the FFIC inventory, and a full resolution-typology classification of the 911,237-market corpus are released at https://github.com/ForesightFlow.