A common evaluation function for playing Chinese Checkers with two or more players has been the single-agent distance across the board. This is an abstraction of a perfect heuristic, because it ignores the interactions between the players in the game. Previous work has studied these heuristics for smaller versions of the game, including 6-piece data for a board with 49 locations and 81 locations which have 13.98 million and 324.5 million combinations respectively. The single-agent solution to the full game of Chinese Checkers has 81 locations and 10 pieces per player. This results in 1.88 trillion possible positions and is stored using 500GB of disk space. In this paper we report results from a preliminary study on how to best use the data to improve the play of a Chinese Checkers program.