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What is realized entry edge?

How much more often a wallet's entries resolved true than the price it paid implied, on the probability scale, read with a bootstrap 95 percent interval. The point estimate alone is never the answer.

The answer first

Every prediction-market entry is an implied probability: pay 40 cents on a binary market and you are acting as if the event is at least 40 percent likely. Realized entry edge asks, across a wallet's resolved record, how much more often its entries resolved true than the prices it paid implied. The unit is probability points: +5.0pp means entries resolved true five points more often than the paid prices implied. Convexly reads the statistic with a bias-corrected and accelerated (BCa) bootstrap 95 percent interval, never a point estimate on its own, because at realistic sample sizes the point estimate is mostly noise.

Worked example: the bigger number is the weaker read

Two real rows from the frozen 2026-06-09 scan of our own published top-50 cohort (full table at /research/top50-skill-scan):

  • Wallet 0xaaaf7f: realized entry edge +12.2pp across 32 resolved positions, 95 percent interval [-0.7, +23.7]. The interval includes zero, so the record is not separable from chance despite the large point estimate.
  • Wallet 0xc2fb28: realized entry edge +5.6pp across 137 resolved positions, 95 percent interval [+1.2, +9.5]. Less than half the point estimate, but the interval clears zero: the stronger read, though as one uncorrected test of 35 it is consistent with chance at the cohort level, it is not in the FDR-corrected cleared set, and its net PnL on the board is negative.

That inversion is the whole lesson. A +12.2pp point estimate on 32 positions tells you less than a +5.6pp estimate on 137, because the interval width scales with sample size. Anyone quoting a wallet's edge without its interval and its denominator in the same breath is quoting noise.

The four-state verdict it feeds

On the analyzer, the skill badge, and the cohort scans, realized entry edge feeds a deterministic four-state read, evaluated top-down with demotions first:

  • Flagged: a single event drives at least 60 percent of the net result, so the figure cannot be separated from one outcome. This overrides any point estimate.
  • Insufficient: fewer than 30 resolved positions, or no usable interval. Too thin to tell an edge from chance either way.
  • Not separable from chance: the BCa interval includes zero. Not a claim of no skill; a claim that the record cannot establish one at this sample size.
  • Skilled: renders only when all gates pass and the BCa lower bound is strictly above zero. Retrospective and in-sample; a past read is not a forecast.

The frozen definitions live in the lexicon, and the interval construction is documented on the methodology page.

What realized entry edge does NOT do

It does not measure dollar PnL, which on a fat-tailed market is dominated by a few large positions. It does not forecast future trades. And a single positive interval does not survive being one test among many: that is the job of the false-discovery-rate correction, which is applied whenever a whole cohort is screened at once.

Read a wallet's edge

Paste any Polymarket wallet address at the analyzer to get its realized entry edge, the BCa 95 percent interval, the resolved-position count, and the four-state read. Free, no signup, public on-chain data only.

Convexly publishes new methodology research roughly every 6-8 weeks plus the /learn series on a rolling cadence. Get the next paper in your inbox when it ships:

Frequently asked

What is realized entry edge?
How much more often a wallet's entries resolved true than the price it paid implied, on the probability scale. If a wallet consistently buys at an implied 40 percent and those positions resolve true 45 percent of the time, its realized entry edge is about +5 probability points. Convexly reads the statistic with a bias-corrected and accelerated (BCa) bootstrap 95 percent interval, never as a bare point estimate.
Why does the confidence interval matter more than the point estimate?
Because at realistic sample sizes the point estimate is noise-dominated. In Convexly's frozen 2026-06-09 top-50 scan, one wallet showed +12.2 probability points of edge across 32 resolved positions but its interval [-0.7, +23.7] includes zero, so the record is not separable from chance. Another showed a smaller +5.6 points across 137 positions with an interval [+1.2, +9.5] that clears zero. The bigger number was the weaker read.
When does a wallet read as skilled?
Only when all three gates pass: at least 30 resolved positions, no concentration flag (no single event driving 60 percent or more of the net result), and a BCa 95 percent lower bound strictly above zero. Demotions win: a flattering point estimate alone never reaches the skilled state. Even then the read is retrospective and in-sample, and it is not a forecast.
Is realized entry edge the same as PnL?
No. PnL is the dollar outcome, which on a fat-tailed market is dominated by a few large positions and by luck at these sample sizes. Realized entry edge asks a narrower, more testable question: did the entries beat the prices paid, on average, across the resolved record? A wallet can have positive PnL with no readable edge, and the reverse: the one positive-interval wallet in the 2026-06-09 scan has negative net PnL on the board.
Where can I see a wallet's realized entry edge?
Paste the address at /tools/polymarket-wallet-analyzer. The free analyzer returns the realized entry edge in probability points, the BCa 95 percent interval, the resolved-position count, and the four-state read (skilled, not separable from chance, insufficient, or flagged). Public on-chain data only.

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