Game designers have to deal with the complex task of monitoring the emotional state of players in games. There are different elements with the game, which effect the player's emotional status. Since the game play experience occurs almost unconsciously, traditional methods such as think aloud may disrupt the playing experience, thus skewing the results obtained. Other methods include fitting cables and electrodes to the player to monitor biological information. Although such devices can offer significant accurate results, they are not commonly found and may cause discomfort while playing games. Because of this, we propose a webcam-based heart rate monitoring method that can be used to predict the player's emotional state. We first analyzed the change in heart rate with respect to the players emotional state. This allowed us to find a correlation between emotional states, such as frustration, fun, challenge, and boredom. The second objective was to create a webcam-based method to monitor the heart rate. This was performed by extracting the RGB channels from the face region and then retrieving the underlying components using a dimensionality-reduction method. The results obtained from the webcam-based method were far from perfect, but this was expected, since we were performing the tests under realistic conditions. The last objective was to predict the player's emotional state using the heart rate obtained from the webcam-based method. The accuracy of the prediction was up to 76 %, which exceeded our initial aim. This system will be implemented in Unity 3D to make its integration and adoption easier.