It is challenging to get access to datasets related to the physical performance of soccer players. The teams consider such information highly confidential, especially if it covers in-game performance. Hence, most analysis and evaluation of the players' performance do not contain much information on the physical aspect of the game. We propose a novel method to solve this issue by deriving individual and team movements in soccer. We use event-based datasets allowing us to analyze the movement profiles of potentially tens of thousands of players. By analyzing the similarity of players based on their movements we find that C. Ronaldo and Ruben Castro were extremely similar despite having two orders of magnitude in their market values, 29 players are more similar to Ronaldo than the most similar counterpart of Messi based on the consistency and uniqueness of their trajectories, and that teams use an abundance of unique attacking schemes, 8909 unique attacks were launched in the 2012/13 season of the Spanish league. Our study reveals novel, actionable insights for the soccer industry at an unprecedented scale.