We've seen Google's PageRank algorithm applied to cancer outcome prediction and used to determine molecular shapes and chemical reactions. Now, PageRank is being used to reveal soccer teams' strategies.
MIT's technology review points to a paper from Javier Lopez Pena at University College London and Hugo Touchette at Queen Mary University of London, analyzing soccer strategy, and using PageRank in the process.
The abstract for the study says:
We showcase in this paper the use of some tools from network theory to describe the strategy of football teams. Using passing data made available by FIFA during the 2010 World Cup, we construct for each team a weighted and directed network in which nodes correspond to players and arrows to passes. The resulting network or graph provides a direct visual inspection of a team's strategy, from which we can identify play pattern, determine hot-spots on the play and localize potential weaknesses. Using different centrality measures, we can also determine the relative importance of each player in the game, the `popularity' of a player, and the effect of removing players from the game.
PageRank is used to measure player popularity, to predict who is most likely to get the ball. The paper looks at the Netherlands and Spain. Here are the passing networks for each team, as diagrammed in the paper:
Here's the main section discussing pagerank in the paper:
The paper has caught the attention of Google's Matt Cutts, who tweeted a link to the MIT article:
Someone applied PageRank-like analysis to European soccer teams' passing: http://t.co/U7yfFJVn
You can read the entire paper here (pdf).