How Developers of The Play
to Earn Game Found Out How Much They Would Earn
In this article, we will tell you about the economic analysis for the developers of the Escape from Zeya game. We managed to calculate the model that could bring in $600 thousand if there are a lot of transactions and traffic.

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About the task

The aim was to combine the Play to Earn genre with economic mechanics to reach break-even point and then make the project profitable. We asked the developers to provide us with information about:
  • game mechanics;
  • business goals for growth rate;
  • user base structure;
  • the amount of investments needed at the first stage.
Obviously, the developers never thought about the last three points.

One of the tasks was to find vulnerabilities in the game mechanic when NFTs are issued or merged. To do that, we needed:
  • to find KPIs;
  • to calculate optimized KPI values;
  • to identify the connections between KPIs and how they influence each other;
  • to find a breakeven point, taking into account the coverage of costs at the initial stage of the project.

What we've done

We simulated user behavior based on the game architecture. We took key elements of the project as indicators, so the model was based on:
  • Transactions. They directly reflect demand and fill the budget. This element shows total cash flows. Transactions are regulated by marketing and in-game mechanics.

  • Average price. It reflects the average cost of all NFTs in the game and is related to transactions. The average price is regulated by token emission and in-game mechanics.

  • Burning rate. It reflects the decrease in the number of NFTs during the game and is regulated by token emission and in-game mechanics.

  • Secondary market share. It's related to the burning rate of NFTs and regulated by in-game mechanics.

  • Commission. We took 10% of all secondary market transactions as a constant

Developer's income depends on profit from commissions at the secondary market and NFTs sales on the primary market.
We have formed three scenarios to find out the viability of the game economy. Static data appeared in the first one. After that we noticed that it's impossible to keep the indicators the same during the project and added dynamic ranges to the second scenario. In the third, we separately ran the indicators that deviate from the baseline values, and analyzed where it all led to.

Scenario №1. The ideal option

In the first simulation, we took the rising and falling rates of transactions up to 3,000 per day.
The initial data:
  • average NFTs price: from $5 to $23;
  • burning rate: from 5 to 30%;
  • secondary market share: from 10 to 50%;
  • duration: 150 days.
This model showed that we will achieve the peak number of transactions in the midsts of the project life, on the 75th day, due to gradual involvement of players and encouraging them to take action. However, we found some problems. If the number of burned NFTs isn't regulated, NFTs will be uncontrollably washed out from the platform.

The project becomes profitable in 4-6 months if the secondary market share is static and the commission amount is 10%.

Players receive a part of the profit for participating in tournaments. We took into account static payout percentage and 20% of the income between tournaments in this simulation. Players would receive less with each subsequent event because of the decrease of transaction number after the 75th day. It might have a negative effect on their expectations.

Scenario №2. The realistic one

In this simulation, we considered concise metrics and the fact that it's impossible to keep the key indicators the same during the whole game life. Also, we added dynamic ranges and corrected metrics:
  • average NFTs price: from $7 to $14;
  • burning rate: from 15 to 26%;
  • secondary market share: from 25 to 45%;
  • duration: 90 days
In this model, the first three elements didn't show an upward or downward trend and remained in the same range. At the end, we received a smoothly growing schedule of transactions which meant an ever-increasing rate of return.

Scenario №3. What if…

We've analyzed how the elements influence each other and found out what will happen if we deviate from the baseline.

If we can't achieve growth of transaction number, the project will still work and show income.
The reason is that each payout is basically a share of profit.

If we take the average cost of a transaction into a range of $1 to $5, the game
will still show income.

If the burning rate appears to be low, from 5 to 15%, the simulation shows that players will tend
to sell NFTs and leave the project. In this case, the game would become unprofitable.

If the burning rate is high, we can see higher profit. However, it will be difficult to stimulate players
to do so.

How much will the game earn?

Considering all the models, we can make a conclusion that the perfect player behavior is not to sell NFTs but to constantly buy new ones to burn them and level up. In this case, the indicators should be:

  • average NFTs price: from $7 to $14;

  • burning rate: from 15 to 26%;

  • secondary market share: from 25 to 45%;

  • average player payout bank: from $8000 to $10000.

It's important to remember that these indicators influence each other. If you change one of them, the skewness will inevitably happen to one side or the other. It's hard to keep metrics static in reality. So, if we stick to the necessary number of transactions of 100 per day, we will receive profit of $400 to $600 thousand in 150 days.

In this case, NFT cost will be $50 000 for the game.


Based on the above, we've come up with the following recommendations.

  • Reduce the number of levels needed to reach top. In other cases, the initial NFT cost would be low.
  • Increase marketing importance to get more transactions.
  • Think of the in-game method to regulate the number of NFTs.
  • The average price of NFTs should be at least $7.
  • The percentage of secondary sales should be no higher than 45%.

What else?

There are two threats to the Play to Earn genre.

The first one is running at a loss. The game is based on NFT, so it is related to projects which allow users to make money. Players can "pull" all investments out of the game. The project won't grow without investments from the players.

The second one is reputation. If investors don't enjoy the game process, the image of the development studio will suffer. Thereafter, it will be more difficult for developers to raise finances for the next project.

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