UNCOMMON•GOODS
Minting statistics about the first and only hard-coded Rune

What is the Global Average?

Imagine...

... you want to find out how many mints per block could be created on average – in different scenarios: minimal, moderate, or maximal. For this, we first use the long-term average, which we calculate from from the historical data.

Lets say the average is 1,360 net mints per block – thats our starting point.

Now we consider: What happens if network activity significantly decreases or skyrockets? To represent this, we apply some adjustments to this average:

• Minimal: If the network is very quiet, we only take half the average as a guideline (around 680 instead of 1,360 mints per block).
• Moderate: Here we assume normal activity, so we stick to the average of 1,360 mints per block.
• Maximal: In the case of extremely high load, we assume twice the average, i.e., 2,720 mints per block.

Depending on whether the mintage is minimum, moderate or maximum, the total supply of UNCOMMON•GOODS can vary significantly, which in turn affects the value of the individual tokens. Assuming a market capitalization of 3 billion (which is a realistic estimate), the price per token can be calculated by dividing the total number of tokens minted by 3 billion. The result is that a minimum mintage leads to a higher price per token, while a maximum mintage has the opposite effect.

How does the calculation work?

To make this work, we proceed in two simple steps:

1. Calculate the average:

We look at historical data, e.g., how many units were created (minted) or burned. Then we calculate the net average per block by dividing the difference between created and burned units by the number of blocks in the considered period:

avgNetMintedPerBlock = (totalMinted - totalBurned) / blockDifference;

2. Derive scenarios:

Based on this average, we derive three scenarios:

• Minimal: avgNetMintedPerBlock * 0.5 (half activity).
• Moderate: avgNetMintedPerBlock * 1.0 (no change).
• Maximal: avgNetMintedPerBlock * 2.0 (double activity).

What do you get in the end?

The result is a small, clear dataset that provides you with the estimated net mints per block for each scenario. Perfect for quickly getting an overview of how network activity might develop – without hours of analysis.

In the end, its not an exact science, but rather a pragmatic heuristic. But for many applications, its more than enough to get a sense of possible developments!