Information Leakage at Population Scale: An Evaluation of the Polymarket Insider-Relevant Subpopulation, 2020-2026
Maksym Nechepurenko

TL;DR
This study evaluates the scope and effectiveness of the ILS-dl framework on Polymarket markets from 2020 to 2026, revealing significant limitations in its applicability and the need for methodological improvements.
Contribution
It extends the ILS-dl framework to a large-scale evaluation, uncovering its narrower effective domain and highlighting key obstacles related to resolution semantics.
Findings
Only 0.7% of markets yield computable ILS-dl values
A hazard-decay baseline correction alters the interpretation of results
Detection of informed flow requires methodological refinement
Abstract
We carry the deadline-resolved Information Leakage Score (ILS-dl) framework of Nechepurenko (2026a, 2026b) from a single-case proof of concept to a population-scale evaluation across 12,708 Polymarket markets, October 2020 to April 2026. We frame the paper as a scope-discovery study: scaling reveals that the framework's effective domain is materially narrower than initial framing suggested, and the principal obstacle is not score computation but resolution semantics. We report four findings. First, only 88 of 12,708 candidate markets (0.7%) yield computable ILS-dl values; only 1 of 32 markets in the ForesightFlow Insider Cases (FFIC) inventory is in scope, and 14 of 32 FFIC markets are flagged unclassifiable due to genuine resolution-criterion ambiguity. Second, only 12 of the 88 computed markets (13.6%) satisfy anchor-sensitivity, and an independent-second-pass T_event validation…
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