Application of data analysis and game theory to competitive Pokémon battle sets

This paper analyzes a scenario where two hypothetical Pokémon trainers each have 3 Pokémon and each send out 1 to battle. We form an experiment through repeated battles between each Pokémon matchup to create payoff values for each Pokémon. Game theory and the process of finding a Nash equilibrium are applied to this scenario to determine both the best outcome for both trainers, and how the results state which trainer has more powerful Pokémon sets. Iterated dominance, best responses, and mixed strategies are used routinely to solve for the Nash equilibrium solution. The application of game theory, Nash equilibrium, and data analysis to economics is briefly discussed.