Solana Alpha Wallets (2026): 952K Candidates, 400 Real Winners
How we identify 952,643 Solana alpha-wallet candidates and the bot-confidence + sample-size filters that narrow the list to ~400 real winners.
MadeOnSol Team·· 11 min read
How we identify 952,643 Solana alpha-wallet candidates and the bot-confidence + sample-size filters that narrow the list to ~400 real winners.
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A Solana alpha wallet is an address that consistently buys profitable tokens before they become popular. On MadeOnSol we maintain a continuously refreshed dataset of 952,643 alpha-wallet candidates drawn from on-chain DEX trades — every wallet that has bought a token early enough to potentially be considered "smart money." This article explains exactly how that number is built, what separates real alpha from statistical noise, and how you can apply the same filters to find traders worth following.
The dataset powers the Solana Wallet Scanner, the KOL Tracker, and the alpha-flag endpoints in our public API. Every number below comes from a live materialized view (mv_alpha_wallets) and is refreshed every hour.
A Solana alpha wallet has three measurable properties:
That third property is where most "alpha wallet" lists fall apart. Anyone can grep for wallets with a 100 percent win rate. The trick is excluding wallets whose 100 percent comes from being a bot that exits the moment it gets a fill — a strategy that prints money on paper but offers no copyable signal.
The base population comes from every wallet that has placed a buy order on a DEX-traded Solana token in the last 90 days. We pull this directly from validator gRPC streams (no third-party APIs), parse swap instructions across Raydium, Meteora, Orca, PumpSwap, and a handful of smaller venues, and join the buyer wallet against the trade timeline.
Each wallet is then scored on six dimensions:
| Dimension | What it measures |
|---|---|
tokens_traded | Total distinct tokens the wallet has touched |
wins / losses | Closed positions classified by realized PnL sign |
win_rate | wins / (wins + losses) |
net_pnl_sol | Cumulative realized PnL in SOL |
roi | Net PnL divided by total SOL invested |
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import { MadeOnSol } from "madeonsol";
const client = new MadeOnSol({ apiKey: "msk_your_key" });
// Real-time KOL trades
const { trades } = await client.kol.feed({ limit: 10, action: "buy" });
// KOL convergence signals
const { tokens } = await client.kol.coordination({ min_kols: 3 });Building a product on Solana data?
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Open the KOL Trackeravg_rank | Average position in the buy-order timeline of each token |
bundle_rate | Share of trades that landed in the same Jito bundle as the swap that created the pool |
The full scoring logic was rolled out in migration 124 (May 2026). It runs on every new trade event via pg_notify and the view is rebuilt hourly.
Roughly seventy percent of every "alpha wallet" list circulating on Twitter is bots. We classify each wallet into one of four bot_confidence buckets using a combination of bundle frequency, buy-size standard deviation, and tokens-per-hour velocity:
| bot_confidence | Wallets | Share | Avg win rate | Avg tokens traded |
|---|---|---|---|---|
low | 861,888 | 90.5% | 23.9% | 1.2 |
high | 69,387 | 7.3% | 33.0% | 10.9 |
medium | 20,099 | 2.1% | 24.7% | 9.4 |
none | 1,269 | 0.1% | 24.0% | 9.5 |
A critical caveat about that 861,888 number: low bot confidence does not mean "confirmed human." It means "no bot signal detected." Three of the bot signals — tokens-per-hour velocity, buy-size standard deviation, and bundle frequency — require multiple trades to compute. A wallet that placed a single trade and never came back has no behavioral surface for the classifier to flag, so it defaults to low by absence of evidence. The avg_tokens column tells the story: low-confidence wallets average 1.2 tokens traded — the bucket is almost entirely single-trade wallets that the classifier simply could not evaluate.
The interesting columns are the last two. High-bot-confidence wallets have a higher average win rate (33.0 percent) and trade ten times more tokens than low-confidence wallets. Bots are mechanically more profitable than the median trader because their edge comes from infrastructure (Jito tips, MEV positioning) that retail traders cannot copy. Following a bot does not make you a bot; it makes you a bot's exit liquidity.
The wallets worth following live in the low-bot-confidence bucket plus a meaningful trade history. The classifier alone is not enough — you have to combine it with a sample-size floor.
Twenty percent of our dataset shows a win rate of seventy percent or higher. That number sounds incredible until you look at sample size:
| Win rate bucket | Wallets | Share |
|---|---|---|
| 70%+ | 198,272 | 20.8% |
| 60-70% | 3,730 | 0.4% |
| 50-60% | 16,437 | 1.7% |
| 40-50% | 2,921 | 0.3% |
| Under 40% | 731,283 | 76.8% |
The 198K "winners" are almost entirely wallets that traded one or two tokens, got lucky on both, and never came back. They are not alpha. They are statistical noise.
The cleanest filter for real alpha is:
bot_confidence = 'low' (human-shaped trade pattern)tokens_traded >= 30 (large enough sample to be meaningful)win_rate >= 0.6 (positive expectancy on a meaningful sample)Applied to the live dataset that filter returns roughly four hundred wallets. That is the actual alpha population on Solana right now — a hundredth of one percent of the broader candidate pool. Worth following. The other 952,000-and-change are the data you need to throw out to see them.
To make this concrete, here are the top five wallets that pass the filter, sorted by net SOL profit. All numbers are realized PnL on closed positions only; open positions are excluded so we are not pricing in vaporware.
| Wallet | Win rate | Tokens | Bot conf. | Net PnL (SOL) | ROI |
|---|---|---|---|---|---|
5ATd…NWd | 78.1% | 37 | low | 271.9 | 70.51 |
EYzA…p2t9 | 61.8% | 35 | low | 13.3 | 0.03 |
kcVz…Mxf | 60.6% | 33 | low | 10.4 | 0.43 |
DrWN…daT | 64.9% | 37 | low | 7.5 | 0.16 |
DkL5…4m4 | 62.5% | 32 | low | 6.8 | 0.19 |
The gap between the top wallet and the second is enormous — the top wallet's 70.5x ROI is genuinely outlier behavior on the kind of size that rules out a bot. The other four are textbook "good human trader" profiles: high tens of trades, mid-sixties win rate, modest positive ROI.
There are three ways to query the alpha-wallet dataset:
1. On-site lookup. Paste any Solana address into the Wallet Scanner and you get the wallet's alpha-flag status, bot-confidence bucket, win rate, ROI, and biggest miss back in one card.
2. KOL Tracker. The KOL Tracker is a curated subset of the alpha population — wallets we have additionally verified via X handle, performance auditing, and manual review. There are 1,058 of them, with 544 actively trading in the last thirty days. Important: the curated KOL list and the broader alpha dataset are disjoint — a wallet is either curated (KOL) or algorithmically scored (alpha), never both. See how the 1,069-wallet KOL roster is manually curated for the human-review side of that split.
3. API. The /v1/wallet/{address} endpoint returns the same fields the on-site scanner uses. The /v1/alpha/* endpoints expose filtered slices of the dataset — top by ROI, top by net PnL, fastest movers — for bots and dashboards that want to query continuously.
Most wallet-rank dashboards (Cielo, Birdeye, GMGN) rely on aggregated DEX trade data with looser filters. They tend to over-count single-trade wallets and under-count win-rate-on-bot-confidence interactions, which is why our top-five list looks different from theirs. Specifically:
The MadeOnSol dataset is the only public Solana wallet-rank dataset that runs all four of those filters together. If you see a wallet ranked as alpha on our site, you can be reasonably confident it is not a bot, not a one-trade fluke, and not a position-still-open mirage.
There are 952,643 candidates in the broader alpha dataset, but only about four hundred meet the stricter "low bot confidence, thirty-plus tokens, sixty-plus percent win rate" filter that defines real alpha. Most public "alpha wallet" lists overstate the number by a hundred to a thousand times because they do not filter out low-sample wins or bot trades.
Across all 952K candidates the average win rate is twenty-four percent. Filtering to low-bot-confidence wallets with at least thirty closed trades raises the average to roughly sixty-two percent. The median real-alpha wallet wins about three out of five trades on a sample large enough to mean something.
We score every wallet on three bot signals: how often its trades land in the same Jito bundle as the pool-creation transaction (bundle_rate), how uniform its buy sizes are (buy_size_stddev), and how many tokens per hour it interacts with (tokens-per-hour). A wallet that bundles frequently, buys identical sizes, and touches more than ten new tokens per hour is classified as high bot confidence and excluded from the alpha population. Wallets with too few trades to compute these signals fall into the low bucket by default — that bucket alone is not a positive human classification, which is why the alpha filter also requires a minimum thirty-token trade history.
There are two ways. For live access, the full dataset is exposed via the public API — the /v1/alpha/top endpoint returns paginated wallet records with all scored fields, and the PRO and ULTRA tiers unlock the unfiltered firehose. For a one-time bulk download, the complete scored-wallet population (~1.25M wallets, one row each with realized PnL, win rate, ROI and bot-confidence) ships as an identity-scrubbed CSV — the Solana Smart-Money dataset, with a free 5,000-row sample to inspect the schema before you buy.
The KOL Tracker is a curated subset — 1,058 manually verified wallets with public X handles. The alpha dataset is the algorithmic counterpart — 952,643 wallets scored from on-chain behavior with no manual verification. The two lists are disjoint by design: a KOL wallet appears in kol_trades, an alpha wallet appears in mv_alpha_wallets, and the same address never appears in both.
The materialized view rebuilds once an hour. Real-time trade events flow into the underlying tables continuously via gRPC streams from validator nodes, so the data behind each refresh is at most sixty minutes stale.
Of the 952,643 wallets that have bought a token on Solana in the last ninety days, roughly four hundred meet the standard of a real alpha wallet: enough trades to mean something, win rate above sixty percent, and a trade pattern consistent with a human making real decisions. The other 952,000-and-change are noise, bots, and one-trade winners.
The MadeOnSol scoring pipeline gives you the four hundred, not the 952K. Paste a wallet into the Wallet Scanner to check any address against it — or, if you want the whole scored population to run your own filters offline, download the full Smart-Money dataset as a CSV.