Monitoring systems collect information from sensors distributed around a monitored plant to assess its health condition. These sensors are prone to be compromised by an attacker. Consequently, two clearly distinct agents exist, namely, a monitoring system and an attacker, both having opposite objectives regarding the accuracy of plant condition assessments. Under this context, a game between these two players arises. This paper considers the inclusion of game-theoretic formulations into resilient condition assessment monitoring (ReCAM) systems. In particular, proposed game calculations periodically identify best sensor networks to be used by the ReCAM system for sensor adaptation based on estimated attacks that an attacker may use. The resulting ReCAM system is then applied to a simplified power plant model and its performance is evaluated via simulations.