Analysis of gameplay data is crucial for evaluating design decisions and refining a game experience. However, identifying player strategies and finding areas of confusion is difficult because a designer may not know what queries to ask or what patterns to look for in the data. To make this task easier, we present Playtracer, a method for visually analyzing play traces that is independent of a specific game's structure. Playtracer applies multidimensional scaling to cluster players and game states, providing a detailed visual representation of the paths the players take through a game. We evaluate our method by analyzing an educational puzzle game and highlighting common hypotheses, pitfalls, confusing elements, and anomalies. Our results suggest that Playtracer can be an effective tool for game analysis and improvement.