We describe the winning strategy of the inaugural Lemonade Stand Game (LSG) Tournament. The LSG is a repeated symmetric 3?player constant?sum finite horizon game, in which a player chooses a location for their lemonade stand on an island with the aim of being as far as possible from its opponents. To receive a high utility in this game, our strategy, EA\^ 2 , attempts to find a suitable partner with which to coordinate and exploit the third player. To do this, we classify the behaviour of our opponents using the history of joint interactions in order to identify the best player to coordinate with and how this coordination should be established. This approach is designed to be adaptive to various types of opponents such that coordination is almost always achieved, which yields consistently high utilities to our agent, as evidenced by the Tournament results and our subsequent experimental analysis. Our strategy models behaviours of its opponents, rather than situations of the game (e.g. game theoretic equilibrium or off equilibrium paths), which makes EA\^ 2 easy to generalize to many other games.