Web3 games can leverage SxT to easily join large off-chain game telemetry with on-chain transparent ownership data in one request, then send that answer back on-chain. For example, calculating shot accuracy, distance traveled, or assists from telemetry joined with NFTs/owner used in each match, then sending those updated stats back on-chain for leaderboards or play-to-earn rewards.

Data Context

Before jumping into gaming use cases for Space and Time (SxT), let's set context on what kind of data games typically operate on. Setting aside internal enterprise data and broadly speaking, Web3 Games typically have two types of data:

  • On-Chain Data: game data that publicly records value-transfer data, or published game-state data. Examples include game character ownership, in-game currency, and leaderboard states.
  • Off-Chain Telemetry: internal game data that is transactional or telemetry in nature. Examples include in-game movement logs, accuracy percentage, and non-value transfer transactional changes to characters.

Traditional or Web2 games will have all this data as well, however, instead of "On-Chain Data" they'll store those elements in centralized, internal systems, meaning they must broker all transactions directly—or more commonly, disallow transfer of ownership entirely, giving rise to secondary/black markets.

Specific Gaming Use Cases

SxT can of course satisfy all the 'standard' use cases in gaming, from serving in-game data in real time (being a transactional database) as well as complex analytic use cases (being an analytic data warehouse).

However, there are also a few unique and particularly valuable use cases that would be of particular interest to Web3 gaming companies.

On-Chain Leaderboards, by NFT (item or character)

Consider a Web3 soccer game where each player’s team is composed of NFT characters, and players get a new NFT minted for their team for every 10 games that they win. The on-chain leaderboard may show the winner of each game and the number of games each player has won. SxT, however, enables more extensive insights (like a specific character’s playing evolution) to be stored on-chain too. In this example, once the winning team of a game is determined, a smart contract can query and roll up an expanse of game telemetry in SxT (like a player’s most played character, that character’s shots-on-goal, the accuracy percentage, etc.) to be loaded on-chain.

Sophisticated Play-to-Earn Logic

Consider now a play-to-earn FPS game, where users earn tokens and power-ups for winning a multiplayer round. The logic is simple by necessity, employing a “winner takes all” approach— which leads to an earning imbalance, as only the players with the most kills earn and power up. To diversify the reward distribution, more sophisticated logic can create prorated earning schemes based on in-game activity relative to all other players. This model allows—for example—players with the highest shot-accuracy to also be rewarded and evens out the playing field, so to speak, as more games are played. Though this level of acuity can’t be achieved with the current data constraints of Web3 gaming, the ability of SxT to easily join on-chain ownership data and off-chain telemetry makes it possible.

What’s Next