I ran this analysis using Convexly, a calibration-tracking tool I'm working on. The Brier scoring math in the post is the same math that runs in the product. Disclosure out of the way.
What I did: pulled trade data for the top 100 Polymarket profit wallets from the public API, resolved 3,651 unique positions, and computed per-wallet Brier scores. Then tested the correlation between calibration and profit using Spearman rank correlation (not Pearson, because the profit distribution is fat-tailed, Hill alpha ~1.6).
The headline finding: Spearman r = +0.608 between Brier score and realized profit. Worse calibration predicts bigger profits. The correlation gets stronger when you drop the top 10 by profit (+0.72), so it isn't outlier-driven. The worst-calibrated whales earn 4.66x the median profit of the better-calibrated whales.
The leaderboard is a concentration ranking. Median single-event concentration: 69.8%. Twenty of the top 100 made their biggest money on the 2024 election.
After separating the four wallets Chainalysis publicly attributed to "Theo" (the French trader who commissioned private YouGov polls), 8 wallets remain in a narrow cluster on the popular-vote markets in a 3-week window around election day. Chainalysis did not link BetTom42 or alexmulti to Theo.
Full 47-column CSV is downloadable from the post. Happy to answer methodology questions.
