Enhancing On-Chain Data Analytics
A special post from a TBL Pro member.
Dear Readers,
At TBL, we try to be teachers and students. At times, we teach about monetary plumbing or the fundamentals behind bitcoin. During others, we lean on experts. Today, we share a post written by a fellow TBL Pro that believed we had our Short-Term Holder/Long-Term Holder analysis in last week’s Mean Median Mode, well, somewhat incorrect. In an attempt to learn from our mistakes and go deeper down the on-chain rabbit hole that fascinates so many of us, we invited Johan to deliver his entire analysis so that we can all benefit. Here it is!
Introduction
I’m not an expert in any way, shape, or form—I’m simply a student of markets, always eager to learn. It’s an honor to write this piece on behalf of The Bitcoin Layer. I’ve learned a great deal from Nik and Joe at TBL, but when it comes to on-chain Bitcoin data, my go-to source is their regular guest and on-chain wizard, James Check. Be sure to explore his research, as it’s thought-provoking, genuinely innovative, and very detailed. Today’s analysis leans on Check’s expertise but is my attempt to add value to the TBL readership.
First Principles
Before we dive into the mechanics of Short-Term Holders versus Long-Term Holders, let’s start from first principles. Analyzing on-chain Bitcoin data can be valuable when interpreted correctly. At its core, on-chain data comes from Bitcoin’s ledger, where transactions are validated and timestamped by miners into the timechain and shared among all nodes. This verification process ensures ownership is accurately recorded, preventing double-spending. By examining these transactions, one can extract meaningful patterns and insights into user behavior.
When analyzing on-chain data, it’s important to understand that the data is always retrospective—reflecting events that could be very recent or as far back as ten years. The data itself does not predict future events; it is merely a continuously updated record of the shared ledger: tick tock, next block.
Any predictive value found in on-chain analysis comes from understanding human behavior. When analysts use on-chain data to forecast prices or anticipate outcomes, they are essentially betting on patterns of human behavior repeating themselves under similar conditions—not on the data itself inherently predicting future outcomes.
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Supply versus Demand
Another aspect of analyzing on-chain data is understanding that one primarily examines the supply side of the price equation. The Bitcoin ledger contains all UTXOs (Unspent Transaction Outputs), collectively representing Bitcoin’s total circulating supply. Embedded within Bitcoin’s protocol is an eloquent, groundbreaking, and beautifully crafted line of code that strictly limits supply inflation, ensuring issuance never exceeds the pre-defined rate set for each epoch. The fully diluted supply is famously capped at practically 21,000,000 BTC (the exact amount is an infinitesimal fraction of less than 21 million). This number remains fixed, regardless of whether users lose access to their private keys. The total supply of Bitcoin will continuously be represented by an ever-changing set of UTXOs distributed across an unknown number of addresses throughout the ledger, constantly evolving for as long as Bitcoin exists.
In contrast, the demand side is unknown—and as you might guess, price formation requires both supply and demand.
Demand is not programmed into Bitcoin’s protocol. There is no code ensuring that demand will exceed supply. There is no guaranteed outcome. “Number go up” is simply not programmed into Bitcoin—period.
However, what is programmed are Bitcoin’s core properties and incentives. These fundamental properties arguably position Bitcoin as the best proxy for money currently available: it’s durable, divisible, portable, verifiable, fungible, saleable, and—critically—scarce. The built-in incentives reward miners for validating and timestamping transactions.
Bitcoin’s protocol also uniquely emphasizes accessibility and pseudonymity. Anyone can use the Bitcoin network, provided they follow the rules of the protocol. It is permissionless and does not require Know-Your-Customer (KYC) compliance. As a result, when analyzing on-chain data, it remains unknown exactly who controls the private keys associated with Bitcoin addresses.
The combination of these programmed properties, characteristics, and incentives creates inherent demand—but that demand fluctuates based on human behavior. This variability is precisely why The Bitcoin Layer developed the TBL Liquidity Index. With its high correlation to both the S&P 500 and Bitcoin’s price, the TBL Liquidity Index could offer insights into expected demand conditions for risk-bearing assets.
To drive this point home clearly: Bitcoin’s supply is fixed, while demand is not. Demand is ultimately driven by human behavior. On-chain data predominantly addresses the supply side of the equation.
The rite of passage
One of the most iconic rites of passage that historically separated boys from men was the Spartan Agoge. The Agoge was specifically designed to instill discipline, endurance, loyalty, and martial prowess. Occasionally, I’m reminded of this analogy when people speak about “diamond hands” in relation to holding Bitcoin. Just as Spartan warriors endured grueling trials, Bitcoin holders must withstand the harsh reality of a crypto winter—where scammers get rekt, businesses collapse, and speculators face liquidation. This challenging period is precisely when your conviction is tested, discipline is crucial, and generational wealth is forged.
A crypto winter is an event that transforms ordinary people (“normies”) who own Bitcoin into committed “Bitcoiners.” Mistakes are made, lessons are learned, and adaptations follow. By the end of a crypto winter, a normie has either sold their Bitcoin or has fully transitioned into a Bitcoiner.
Emerging from this trial, the Bitcoiners—armed with newly forged diamond hands—enter a fresh epoch marked by what is known as “the halving,” where Bitcoin’s block subsidy is programmatically reduced by half. This moment feels reminiscent of the iconic scene from 300, when King Leonidas asks his Spartan warriors what their profession is.
The reason I’m painting this vivid picture will become clearer as we delve into the differences between Long-Term Holders and Short-Term Holders.
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