Tracking Bull Run History Without Losing Your Mind
I spent three years trying to build a proper framework for tracking crypto bull runs. I started by copying what everyone else did — screenshots, hand-drawn charts, a Excel spreadsheet that grew to 47 tabs. It was useless. The problem wasn't data collection. It was knowing what signals actually mattered versus what was just noise. Here is how I actually do it now. The process takes me about 20 minutes per cycle check, usually on Sunday mornings.
Why Most People Misread Bull Run History
The biggest mistake I see is treating every rally as a repeat of the last one. 2017 looks nothing like 2021, which looks nothing like 2024. The macro conditions are different. Regulatory environments shift. Institutional participation changes the entire shape of price action. When I first started analyzing Bull Run History, I kept expecting the same top patterns. I was wrong every time. The second mistake is focusing only on Bitcoin. Altcoin season timing is not predictable from BTC dominance alone. You need to watch Ethereum relative strength, stablecoin supply growth, and exchange reserve movements simultaneously. These three give you a much clearer picture than price charts alone. I had a specific problem back in early 2023 that taught me this. I was tracking the recovery rally and kept getting squeezed on entry points because I was only watching BTC/USD. I missed that ETH was already showing accumulation patterns on the weekly while everyone was distracted by Bitcoin hitting new highs against the dollar. The workaround was simple but I wish I had done it from the start — I started tracking BTC/ETH ratio as a separate signal line. When that ratio started compressing during sideways periods, it told me altcoins were about to move before the price action caught up. That pattern has held up across every cycle since.
What You Actually Need to Track
Forget fancy dashboards. You need maybe five data points maximum. Everything else is decoration. Bitcoin halving cycle timing. This is the baseline. Each cycle spans roughly four years from one halving to the next. The pre-halving phase, the post-halving consolidation, the parabolic run, and the distribution. Knowing where you are in this timeline matters more than any indicator. Global M2 money supply growth. This is the real fuel behind bull markets. When central banks are printing, risk assets go up. When they are tightening, they come down. Check the Fed balance sheet, the ECB balance sheet, the PBOC data. You do not need real-time precision. Monthly or quarterly is fine. This tells you whether liquidity is expanding or contracting on a global scale.
Get the Full Details
Exchange net flows. Coins moving off exchanges into cold storage signals accumulation. Coins moving onto exchanges signals selling pressure. This data is publicly available through Glassnode, CryptoQuant, and similar services. I check this once a week. Big moves in the wrong direction warn me before price reacts. Stablecoin market cap growth. When stablecoin supply expands rapidly, fresh capital is entering the ecosystem. This usually precedes price moves by two to six weeks. A shrinking stablecoin supply means money is exiting. This is one of the most reliable leading indicators and it is completely overlooked by retail traders. Fear and Greed Index alongside funding rates. Extreme greed with positive funding rates across major exchanges usually marks a local top. Extreme fear with negative or near-zero funding often marks a bottom. This combination filters out false signals that either metric produces alone.
How to Build a Simple Tracking System
I use a single Google Sheet with four tabs. One tab has the halving dates and cycle phases with notes. One tab tracks the five data points above on a weekly basis. One tab logs my observations and entries. The last tab is just a raw chart of Bitcoin price with halving markers overlaid. The whole thing takes about 10 minutes to update each week. If you are spending more than 30 minutes on this, you are overcomplicating it. I also keep a running text file where I jot down what I am seeing in plain language. "BTC consolidating between 61k and 68k. ETH showing relative strength. Stablecoin supply flat for three weeks." These notes look meaningless in isolation. Six months later, when you read them together, patterns emerge that no indicator would show you.
Bull Run History as a Tool, Not a Crystal Ball
The honest truth is that this system does not predict tops or bottoms. It tells you the probability landscape. Sometimes the data says one thing and the market does another anyway. That happened in 2022 when all the accumulation signals were flashing green and then Terra collapsed. No model predicted that. No amount of Bull Run History analysis would have helped with a black swan event like that. The system works best when you use it to manage position size and risk rather than to time perfect entries. If the data suggests you are in a late-cycle phase, you reduce exposure regardless of how good the pumps feel. If it suggests early accumulation, you build positions slowly over weeks rather than going all in at once. The downside of this approach is that it requires discipline. You will see candles going up and feel FOMO. The data might say wait. You have to actually wait. I failed this test myself in mid-2021. The signals were muted but I bought anyway because the price was moving. I made money but I should have made three times as much by sticking to the process. That is the real cost of ignoring your own framework — not losing money, leaving money on the table.
If you want a resource to pull the data from, CryptoQuant and Glassnode both offer free tiers that cover exchange flows and stablecoin supply. The Bitcoin halving schedule is just a Wikipedia page. Everything else is yours to track manually or with a script if you know Python. I have been doing this since 2020. The system has not changed much. What changed is my ability to ignore the noise and follow the five signals instead of chasing every new indicator someone sells on Twitter. That is the actual takeaway here. Less data. Better focus. Same results cycle after cycle.
