While many RPG video games stimulate players’ critical thinking, their efforts can lead to wasted hours and poor outcomes. JMP/Pro Multivariate data mining was applied in the game “Empire: Four Kingdoms” to optimize rank/resource outcomes. 2 main objectives are: (1) recruit a powerful army to conquer more land & defend against enemy attacks, (2) produce new resources (Food, Wood, Stone) for building a mighty fortress. There are 40+ types of troop units available to build an army. Each troop unit has 7 attributes. To optimize the troop recruiting process, Multivariate Correlations are used to identify affinity patterns. Correlation analysis suggests splitting troop units into 3 categories (Attack, Defense, Speed/Looting). Defense capability is more important than Attack and Speed/Looting. There is one battle constraint – limited troop units/types per battle – which limits the linear optimization model; Hierarchical clustering  is used to resolve this by accurately identifying clusters. Principle Component Analysis (PCA) is used to verify dimensional reduction and determine the appropriate number of clusters with a Scree Plot. The model created is validated in actual game battles within 95% prediction interval. This statistical approach enhances troop recruiting and accurately predicts battle results