Last week, I mentionned the use of software for football or rugby analysis. I found an interesting paper about the very topic of sport analysis: "Detection of real-time patterns in sports interactions in football" (pdf file). The authors claims that instead of using frequency of events ("how many times did 'X' occur? with X=pass, tackle, shot...) as a performance index, one should use a more accurate index: T-pattern.

A T-pattern is essentially a combination of events where the events occur in the same order with the consecutive time distances between consecutive pattern components remaining relatively invariant with respect to an expectation assuming, as a null hypothesis, that each component is independently and randomly distributed over time.

This study is of particular interest in terms of how to analyse a mobile game experiment:

The research utilized multiple game analysis with each game being treated as a single case.(...) Coding included data on pi tch posit ion, player and match events. Pitch position was classified according to the pitch divisions shown in figure 3. The primary event categories for data collection were: pass; tackle; header; run; dribble; clearance; shot; cross; set-play; lost control; foul.

They found patterns and structure in football teams play. What is also interesting is the fact that "The link between performance rating and pattern participation suggests that coaches were recognizing, albeit at a potentially subconscious level, the structure within a teams play."