What actually happens to most tokens after launch

The question was direct: what percentage of new tokens actually go up? Not "can go up," not "have the potential to" — do. The honest answer requires a denominator, and almost nobody publishing crypto commentary has one. We do, because we log every call we make and then measure what happened afterwards. So here is the distribution, with the caveats attached, and then an explanation of why the distribution matters more than any single result.

What these numbers actually measure

Before the figures mean anything, you need to know what was counted.

A market cap is the token's price multiplied by its circulating supply — the total value the market is currently putting on the thing. When we log a token, we record its market cap at that moment. That is the entry level.

Everything below is forward-measured: the peak is taken only from price action after the moment we logged the token. A token that had already run before we looked at it does not get credit for that run. This matters because it removes the most common trick in crypto marketing — pointing at a chart and starting the story wherever it looks best.

Tokens that went nowhere are in the totals. They are not filtered out, and the worst outcomes are not quietly dropped.

The data covers 36,147 logged calls on Solana, as of 2026-09-15.

The Solana distribution

Of those 36,147 logged calls, 21.3 percent doubled — meaning the market cap reached twice the entry level at some point after we logged it.

That is the headline number, and it is worth sitting with. Roughly one in five. Which means roughly four in five did not double.

The rest of the distribution:

• 6.4 percent reached five times the entry market cap.
• 2.6 percent reached ten times.
• 0.3 percent reached fifty times.

52.4 percent were flat or down — the peak after logging was at or below the level we logged them at. The remaining tokens sat somewhere in between: above where we logged them, but short of a double.

Notice the shape. Each step up gets dramatically thinner. Doubling is uncommon. A ten-fold is rare. A fifty-fold is a rounding error in the total. If your mental model of a new token launch is "this either doubles or dies," the real distribution is more lopsided than that in both directions: a large bloc goes nowhere, a smaller bloc grinds up modestly, and a thin tail does something dramatic.

The same shape on Robinhood Chain

We log Robinhood Chain tokens separately, and we group them by how they presented themselves at the time we logged them. The category labels are ours and they reflect what the token claimed to be, not what it turned out to be.

• Meme tokens: 8,150 logged, 5.6 percent doubled.
• Unclassified tokens: 3,880 logged, 4.9 percent doubled.
• Tokens paired to a stock: 868 logged, 16.0 percent doubled.
• Utility tokens: 639 logged, 27.5 percent doubled.

Two things are worth pulling out here.

First, the doubling rates are lower across the board than the Solana figure. That is not a statement that one chain is better. The windows are different, the launch conditions are different, and the mix of what gets logged is different. It is a statement that a base rate belongs to a specific population and a specific period, and you should be suspicious of anyone who moves one number between contexts.

Second, look at the sample sizes. The utility category shows the highest doubling percentage and has only 639 tokens behind it. A few dozen outcomes moving one way or the other would visibly shift that figure. The meme category has 8,150 tokens behind its 5.6 percent, so it is far more stable. A high percentage built on a small sample is not a finding — it is a number waiting to change.

Why you need a baseline at all

Here is the part that transfers to any token, on any chain, whether or not you ever use our tools.

A single result, on its own, tells you nothing. If someone shows you a call that doubled, you have learned one data point and no context. You cannot tell whether that outcome reflects anything repeatable or whether it is the ordinary noise of a process where roughly one in five tokens doubles anyway.

A base rate is what turns a result into information. Knowing that 21.3 percent of logged Solana calls doubled does not tell you which ones will. It tells you what an unremarkable outcome looks like, which is the only way to recognise a remarkable one. It also reframes the losses: if you approach launches assuming the typical path is a double, then a token that goes flat feels like bad luck. If you know that 52.4 percent of logged calls went flat or down, that outcome reads as ordinary instead of anomalous.

This is why we publish the flat ones and the dead ones alongside the outliers. A record with only the winners is not a record — it is a highlight reel, and it makes every outcome look equally achievable.

What this does not tell you

A peak is not a profit. Every figure above measures the highest market cap after logging. Getting that outcome requires selling at that high. We do not measure whether a seller could have exited there at size — thin liquidity can make a price real on a chart and unusable in practice.

This is our log, not the chain. 36,147 calls are tokens we chose to log. They are not a random sample of everything launched on Solana. Whatever criteria put a token into our log shapes the distribution you just read.

The categories are self-reported. "Utility" is what a project claimed. Some of those will turn out to be memes with a longer whitepaper.

No number here predicts the next token. These are backward looks at a fixed window ending 2026-09-15.

What to do next

Two places to go. The research page lays out the outcome data behind these figures, including the parts that look bad. The receipts page shows every call we logged and what it did next, so you can check our work rather than take our word for it.

Read the base rate first. Then read the individual results with it in hand. That order is the whole point.