⭕️La_Crrypt💰₿ ✓

[text] Looking at one wallet is research. Looking at 100,000 wallets is analytics. Building labels others use is infrastructure. Think of a supermarket. 100,000 customers walk into your shop. Some only buy when there’s a discount. Some always buy premium products. Some buy every

[image] I analyzed 10,797 wallets across 155 migrated tokens on Pumpfun in last 30 days. I wasn’t looking for “smart money.” I was testing a different idea: Can wallet behavior be used to identify repeatable trading strategy ? Using a behavior-based labeling framework, I identified

[text] I have come to the realization that Web3 experience is geographical, personal, and contextual. Web3 works on a timing system, which makes it impossible for individuals to have the same experience. People don’t experience the same market, even when looking at the same chart.

[image] One thing I’ve learnt from crypto/on-chain is this: If you can track money movement, where it’s coming from, where it’s going, and where it finally lands, you’ll also land there too. The difference is, you got there earlier and with a better entry than 90% of people. And the

[image] The trench looks random until you start filtering behavior instead of narratives. Building datasets across market cap ranges is making one thing obvious: The best runners leave different on-chain signals before the chart explodes.

[text] One thing about crypto: You can do research and fail. You can do research and keep it a secret. You can bring a model that predicts and gives insights to 90% of Web2 companies and still watch it fail in Web3. I’ve had research ideas that looked brilliant at the start. By the

[image] A bag holder 🎒 I’m a representative 🧡💯

[image] Data in Web3 is only useful if it leads to better outcomes. These are a few alerts and their outcomes (2x–3x+). The goal isn’t to find every winner, but to reduce the chances of losing.

[image] My previous research reduced uncertainty and consistently found 2x–3x opportunities. But I wasn’t satisfied. I wanted to understand why some tokens stop at 2x while others become 5x, 10x, or much larger. So I went back to the data. Removed assumptions and refined my research.

[text] From my own on-chain analysis, one thing I’ve realized about “smart wallets” is that they’re only considered smart based on the platform labeling them. Different analysts and data scientists are behind each platform, and each team defines “smart” differently. For example, the

[image] One thing I discovered during my wallet research is that knowing a wallet is profitable doesn’t tell you why it’s profitable. Knowing a wallet made money doesn’t tell you how it made money. While researching profitable wallets, I kept running into the same problem. I’d find a