The NBA has a system called Sports VU that tracks x-y coordinates of every player and the ball every 1/10th of a second for every game of the 2013-2014 and 2014-2015 seasons. With some fancy web scraping I now have access to this data and -- because I'm such an avid fan of the NBA -- I would like to identify each team's most common plays. Assume I don't have any knowledge about each team's plays beforehand (so I don't think supervised learning would work here). What would be the best unsupervised learning techniques to use?
If I could trace each player's path over the course of the play, I imagine the problem would be similar to what you would see with image recognition/classification. Anyways, should I use PCA, some kind of neural network? I understand this is a very broad question -- I don't need to know how to code it (I'm a proficient coder and machine learning practitioner); I'm just looking for high level unsupervised machine learning details.