How to audit our track record yourself

You asked how to verify a crypto service's results. The honest answer is that a claim is almost never verifiable, but a method often is. Anyone can post a screenshot of a token that went up. What you actually want to inspect is the machinery behind the number: when the entry was fixed, how the outcome was measured, and whether the calls that failed are still sitting in the total. This article lays out the method behind our figures, points you at the pages where the underlying material lives, and shows you how to check a single call yourself.

What verification actually means for a track record

Four questions separate a checkable record from marketing copy.

When was the entry fixed? A starting point only means something if it was recorded before the outcome was known. If entry can be chosen after the fact, every number becomes decoration.

Who recorded it, and how? Self-reported data is still self-reported. That does not make it useless, but it means you should be checking whether the recording rule is stated plainly and applied consistently.

What is the denominator? The bottom of the fraction matters more than the top. A handful of spectacular outcomes means nothing if thousands of attempts have quietly gone missing.

Is the losing side still in the totals? Look specifically for how many calls went nowhere. A record that only reports its best results is not a record; it is a highlight reel.

Any service that will not answer those four questions in writing is asking you to trust a feeling.

The method behind our numbers

Every figure we publish is forward-measured from our own logged calls. "Forward-measured" means the clock only starts at the moment of the call and runs in one direction from there. Market capitalisation, or market cap, is the token's price multiplied by its circulating supply — a rough measure of how much money the whole float is worth at that instant.

• Entry is the market cap of the token at the moment we logged the call. Not the low of the week, not a dip that arrived later, not a price we wish we had caught.
• Peak is measured only after that moment. We are not scanning the token's whole history for its best day; we take the highest market cap reached after the call was recorded.
• Losers stay in. Tokens that went flat or fell are not removed from the denominator. There is no pruning of calls that aged badly.

Two limitations follow directly from that design, and you should hold them in mind whenever you read a number of ours. First, the peak is a hindsight maximum. Reaching it in practice means selling into strength, and most people do not. Second, "doubled" describes a token's peak, not a trader's bank balance. The two are not the same thing.

Checking a single call

This is the part you can do without trusting us at all. Open the receipts page, which lists calls alongside what happened afterwards. Pick a call with a visible timestamp and work through it in order:

• Note the entry market cap as it was logged at that moment.
• Look at what the token did after the timestamp, and at what it did not do.
• Compare the peak with where the token sits now, which is often a very different picture.
• Confirm that the call shows up in the aggregate counts, rather than existing only as an isolated anecdote.

Do that for a handful of calls, and deliberately include one that went badly. A small sample cannot tell you whether a method works. It can tell you whether the description of the method matches the data, which is the only question a small sample is qualified to answer.

What the outcome data says

As of 2026-09-15, we had logged 36,182 Solana calls. Of those, 7,710 — 21.3% — reached at least double their entry market cap at some point after the call. 6.4% reached five times, 2.6% reached ten times, and 0.3% reached fifty times. Meanwhile 18,973 calls, or 52.4%, went flat or down.

Read those together, not separately. A little over a fifth reaching double is the impressive-sounding line. The line that keeps you honest is the other one: more than half went nowhere.

On Robinhood Chain, the picture splits by token category. Of 8,150 meme tokens, 5.6% doubled. Of 3,989 unclassified tokens, 5.0% doubled. Of 868 stock-paired tokens, 16.0% doubled. Of 639 utility tokens, 27.5% doubled. Category is doing a lot of work here, and so is sample size — a few hundred tokens can swing a long way on a handful of outcomes. The buckets are also our own classification decisions, which is a judgment, not a measurement.

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