Adaptive difficulty calibration for skills-based activities in virtual environments

Abstract

Methods of the present disclosure may collect data when a user plays one or more different types of games when determinations are made as to whether the difficulty of a game should be changed. The collected data maybe evaluated to identify whether a user gaming performance level corresponds to an expected level of performance. When the user gaming performance level does not correspond to an expected level of performance, parameters that change the difficultly of the game may be changed automatically. Parameters that relate to movement speed, delay or hesitation, character strengths, numbers of competitors, or other metrics may be changed incrementally until a current user performance level corresponds to an expectation level of a particular user currently playing the game. At this time, the user expectation level may be changed, and the process may be repeated as skills of the user are developed over time.