Over the past few months, I went through a pretty painful, mostly-manual process of reviewing long-form videos from popular crypto analysts, influencers, and commentators.

For each creator, I logged things like:

• Every actual prediction they made (price targets, time horizons, cycle calls, macro takes, etc.)
• Whether those predictions actually came true

This started as a personal research project because I got tired of hearing huge claims with zero accountability. I’m still refining the process and slowly building some internal tools to make the manual steps a bit faster, but even early on, some patterns are already surprisingly clear.

Early findings:

• A surprising number of creators are basically coin-flip accuracy (around 50%)
• A small group consistently hit 65–75%, especially on macro or cycle timing
• Some influencers miss 70% of their calls but speak with extreme confidence
• A few of the “worst performers” are actually the most charismatic/entertaining
• Many creators quietly ignore their misses and only highlight their wins

Why I’m doing this:

Crypto YouTube is massive, but it’s not structured data.
There’s no accountability.
No consistency.
No memory.

I wanted to see whether treating YouTube predictions like analyst forecasts — and actually tracking the outcomes — could reveal anything useful.

Ultimate goal (still early):

Build a structured dataset of crypto analyst predictions so I can start exploring bigger questions like:

• Is there any predictive power when you aggregate sentiment across many creators?
• Could a multi-dimensional sentiment model (e.g., 3D sentiment across topics/creators/time) reveal early signals?
• Do certain analysts perform better or worse in high-emotion markets?
• Who should we pay attention to, and who is consistently unreliable?

If anyone’s curious, feel free to ask or suggest creators. I’ve mostly focused on BTC-related analysts so far.