How are Staking Rewards and Network Rewards Rate calculated?

Staking rewards on Revolution Network are dynamic. This means both the rewards you earn and the 24-Hour Average Network Rewards displayed for a specific Reward Pool in Amped.bio can change over time.

The easiest way to think about staking is as a shared pool of network rewards.

As reward-generating network batches are processed, rewards are generated and distributed through participating nodes and Reward Pools to users staking REVO.

The amount you earn depends primarily on:

• How many network rewards are being generated

• How much of those rewards are available to fan stakers

• How much REVO is sharing those rewards

What does 24-Hour Average Network Rewards mean?

24-Hour Average Network Rewards represents the average Network Rewards Rate observed over the previous 24 hours.

It is designed to give you a more stable view of recent reward activity rather than showing a rate based on a single moment in time.

Because network activity changes, this percentage can move up or down over time. It should not be interpreted as a fixed or guaranteed return.

How is the Network Rewards Rate calculated?

At a high level:

Rewards available to fan stakers ÷ Total REVO staked by fan stakers

The Network Rewards Rate takes several factors into account, including:

• The number of reward-generating batches

• The average number of batches being processed

• The rewards generated by those batches

• The node's expected share of network rewards

• The percentage of rewards retained by the node

• The Reward Pool's share of node rewards

• Any percentage allocated to the Reward Pool creator

• The total amount of REVO staked by fans

Because these values can change, the Network Rewards Rate can change as well.

Why does the Network Rewards Rate change?

1. More or less REVO is being staked

Rewards available to fan stakers are shared among the REVO participating in a Reward Pool.

If more REVO enters the pool while the amount of available rewards remains unchanged, those rewards are shared across more staked REVO. This can reduce the Network Rewards Rate.

If REVO leaves the pool while available rewards remain unchanged, the remaining staked REVO represents a larger share of the rewards. This can increase the Network Rewards Rate.

2. Network batch activity change

Staking rewards are generated as reward-generating network batches are processed.

The number of batches processed over time is not constant. Batch activity can vary based on transaction volume, how transactions are bundled, and the overall efficiency of the network.

This directly affects reward generation:

More reward-generating batches → more rewards generated → potentially higher Network Rewards Rate

Fewer reward-generating batches → fewer rewards generated → potentially lower Network Rewards Rate

Importantly, fewer batches do not necessarily mean the network is performing less work.

As Revolution Network becomes more efficient, multiple transactions can be bundled into a single batch. This allows the network to process more activity with fewer batches.

That is good for network performance and scalability, but at the same transaction volume it can also result in fewer reward-generating batches and therefore a lower Network Rewards Rate.

As network usage grows and more transactions are submitted, reward-generating activity can increase again.

This is why the Network Rewards Rate can change even when your personal stake and the total amount staked in the Reward Pool have not changed.

3. The node's share of network rewards changes

Reward Pools receive rewards through participating staking nodes.

A node's expected share of network rewards can change depending on network conditions and the amount of stake associated with that node.

A larger share can increase the rewards available to its Reward Pools, while a smaller share can reduce them.

4. The Reward Pool's share changes

Each Reward Pool receives a portion of the rewards flowing through its associated node.

Changes in the amount of stake associated with a Reward Pool can affect its share of those rewards relative to other participating stake.

As a result, the amount available to fan stakers in a particular pool can change over time.

5. Node and Reward Pool creator percentages matter

A portion of network rewards may be allocated to the staking node or Reward Pool creator before the remaining rewards are distributed to fan stakers.

A higher node or creator allocation means a smaller percentage of the rewards is available to fan stakers.

How are my personal rewards determined?

Your personal rewards depend mainly on:

• How much REVO you have staked

• Your share of the total fan stake in the Reward Pool

• How many rewards are available to fan stakers

• How much reward-generating network activity occurs

• How long your REVO remains staked

For example, if your stake represents approximately 5% of the total fan stake in a Reward Pool, you would generally receive approximately 5% of the rewards distributed to fan stakers in that pool.

A simple way to think about it

Think of network rewards as a pie that is continually being created and shared.

More reward-generating network activity = potentially more pie.

More rewards available to fan stakers = potentially higher Network Rewards Rate.

More REVO sharing the same rewards = a smaller reward per staked REVO.

These factors can move in different directions at the same time.

For example, increased network activity could push the Network Rewards Rate higher, while a large increase in the amount of REVO being staked could push it lower.

The Network Rewards Rate is therefore best understood as a dynamic measure of current network reward conditions, not a fixed interest rate or guaranteed return.

Revolution Network is currently operating on testnet, where network performance, reward calculations, batching behavior, and other economic parameters are continually being tested and optimized in preparation for Mainnet.

For more detail on staking, including the issuance curve and tokenomics, see the Revolution Network Whitepaper.