Proof of contributed stats

Proof of gaming

The POG that is adopted by most of the P2E ecosystems today is a method of obtaining a token profit as much as the players play the game. For example, if only one user plays the game, the player can obtain tokens corresponding to 1 time of play. In a glimpse, this system seems very fair as a method adopted by most games and has a characteristic that as there are more users entering the game, more game tokens are created. In a lot of games, in an attempt to prevent a devaluation of tokens generated in such a way, introduced a burn model that can use tokens of partial contents, but it was not a significant model in the long- term. To solve such a problem, the ORBLER team has introduced the concept of the Proof of Contributed Stats (POCS).

Proof of Work (PoW) Block issued in Time Unit

In the PoW mainnet chain, the blocks are allocated according to the amount of PoW stakes for a certain period or specific work unit. The number of MSP tokens issued per one block of game data is restricted and the allocation method of MSP tokens will be based on POCS contributions.

Proof of Contributed stats

Inspired by PoW, we have designed a more advanced reward system, Proof of contributed stats, POCS. All players receive a record through the gameplay. They can acquire a better record according to their performance. A player who has acquired a better record will be provided with a better reward.
The game record of players will be grouped in a unit of one minute to form a single block. The MSP is allocated by the weighted value of contribution from the applicable block.
For example, 5 users played the game for one minute and each player had cleared the stages up to 40 stages, 30 stages, 20 stages, 5 stages, and 5 stages. Respectively, the allocation ratio of MSP tokens will be divided into 40%, 30%, 20%, 5%, and 5%.
The above description is only an example and the actual allocation ratio follows the calculation from more complex formulas.
When a user plays the same game as other users and forms similar data, a user with a better achievement will be provided with more reward from the weighted value. The play data of users who have participated in the game will be analyzed to be made public transparently, and rewards will be provided based on this.