In the past ten years, neural networks have made a significant impact on machine learning by enabling computers to make decisions previously difficult for them to accomplish. This predominantly began as recognizing photographic content, and is now being applied in a variety of contexts. Recently, there have been significant achievements for neural networks that select best moves to play in games. DeepMind's AlphaGo defeated 18-time Go world champion Lee Sedol in 2016, and since then neural networks have been given serious consideration in this field. This study analyzes which games are best suited to a neural network solution, and how to design a game specific neural network to successfully select best moves.