Bayes Theorem - Web3 Games

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This diagram models the user flow and interactions within a Web3 game, focusing on the demographics of players and their engagements, specifically revolving around Non-Fungible Tokens (NFTs). It uses Bayesian statistics to estimate the likelihood of a player being a "Fun Seeker" given they have sold an NFT. The diagram categorizes players into two main groups: "Fun Seekers" and "Crypto Enthusiasts," both of which can potentially sell NFTs. Through automatic gate distribution and targeted resources flow, it dynamically simulates the distribution of new players into these categories, along with the transition of some players into NFT sellers within each category. 

As the system iterates, various probabilities are recalculated to reflect the changing landscape of the game's player base. These calculations include the prior probability of a player being a "Fun Seeker," the likelihood of a "Fun Seeker" selling an NFT, the overall probability of observing an NFT sale, and the posterior odds of a player being a "Fun Seeker" post observing an NFT sale. By inputting real game data and running this simulation over multiple steps, the model provides valuable insights into the composition and behavior of the game's community, assisting in strategic decision-making regarding game design, marketing, and community engagement strategies.