Interactive video games often use vision-based systems or wearables to track player movements. Vision-based systems are privacy-invasive, and wearables require frequent recalibration and recharging. Frequently-Modulated Continuous-Wave (FMCW) radars have been proposed as an alternative tracking solution addressing these problems. Working in the millimeter-wave (mmWave) range, they capture scenes as point clusters, ensuring privacy without attaching sensors to the user. Previous research has shown their applicability in rehabilitation, gait recognition, and smart home appliances. This study focuses on integrating an mmWave sensing device with an interactive version of the Breakout video game. We propose a general framework with three main modules - generating points, clustering them, and reconstructing the player's movements as in-game commands. Our system enhances an already existing Kalman filter-based tracking algorithm. Online experiments were conducted to compare the proposed system to the baseline algorithm. The proposed system decreases the standard deviation on the estimated target location by 33% against motionless targets, while maintaining the baseline accuracy when tested on moving targets. Furthermore, it allows a higher game refresh rate, thus smoothing in-game movements. These results demonstrate the potential of FMCW radars in enhancing interactive video game experiences.