Analytics - What makes a great player?

While surfing the outer region of the Habs' hockeysphere, in a 'fanpost' seeking to crowdsource raw passing data from NHL games for an amateur advanced statistics project, I came across references to the book/concept of 'Soccernomics'. Which in turn led me into the region of soccermetrics. Which still seemed a little amateur.

So, knowing that the Moneyball Concept seems to be most developed in American sport, I drifted to the NFLsphere and discovered a nascent, monetised version of advanced analytic concepts at work in relation to american football, and signs of the self reflexive awareness of this intellectual movement - where it ties in to the growing movement of industrial level analytics in the 'real world' in general.

Of course, the academic psychologists would have had to have been amongst the first on the field, and it is just like them and their sense of humour to have used basketball as the subject of their seminal study applying the science to the art of the sport. Needless to say, and staying within the psychological zone, their sub-industry has grown in a fractal bloom (eg this meta-analysis of the field of perception/expertise). Which is getting ultimately to the core questions, what makes a great player?

Moving back into the world of the hockeysphere, I passed through the more analytic oriented form of "sabermetric" moneyball logic in its native sport of baseball,before ultimately returning to one of my favorite hockey analytics sites for a good read.