How it works

Here is a quick summary of the method used to compute estimates. The algorithm uses a simplified model taking into account 3 factors:

Current weight of transactions in the mempool
Speed at which new weight is entering the mempool
Randomness in block production intervals

Unlike some other fee estimation algorithms, it doesn't look at the previous mined blocks at all. Instead, it looks at the factors that are going to drive the production of the next blocks: the mempool, the speed of increase of the mempool and the probability at which it is being drained.

Its goal is to give reasonable estimates given the presently known mempool dynamics, while avoiding overestimation.

Inputs

The mempool is categorized into "fee buckets". A bucket represents data about all transactions with a fee greater than or equal to some amount (in sat/vbyte).

Each bucket contains 2 numeric values:

For simplicity, transactions are not looked at individually. Focus is on the weight, like a fluid flowing from bucket to bucket.

Computations

For each target interval (30 mins, 1 hour, 2 hours etc...), we're trying to find the cheapest fee rate that is likely to become fully cleared (0 WU) with a given probability.

The probability is defined by the "confidence" setting on the website. Current values are:

Now let's simulate what's going to happen during each timespan lasting minutes:

The cheapest bucket whose final_weight is ≤ 0 is going to be the one selected as the estimate.

Small correction

Because the window used to sample the flow of transactions increases proportionally to each target interval, it sometimes gives incoherent results with estimates that decrease then increase as the window gets larger (if there was significant variations in the flow of transactions during this time).

Since this makes no sense (if a low fee gets you confirmed faster, then there is no need to increase the fee to target a longer window), so for each estimate we take the minimum value of all estimates at windows shorter or equal.


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