Data-Driven Difficulty Analysis

Data-Driven Difficulty Analysis

Simplify and optimize your stage difficulty balancing




For each stage in your game, helps you find the Optimum difficulty for your overall audience of players

Testing the difficulty of all the stages in a game can be very time consuming. You rely on feedback from your team, some testers… are they representative of your real players? And is your tuning optimum for your overall audience?

Our data-driven analysis and tuning uses statistical tools (like Gaussian Regression) to check, for each stage, if your difficulty is "optimum" for your overall audience of players.

Stop tuning blindfolded and losing precious time!

For each stage, you can check in the web-portal if your difficulty is optimum  for your global audience. will also check if the "easier" and "harder" values are optimum for the Real-Time Player Personalization.

The checked stages (feedback on the easier/default/harder values) are available for the Player Personalization feature, while the later stages (less players) are still explored for Difficulty Analysis.

If you update your game via the App Store or via a server, and the new version contains changes that could affect the difficulty, you indicate in the  portal which stages have been affected so the learning restarts only for those stages.

Use it during early-access, soft-launch, and for live game updates.