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04-04-2012, 10:49 AM
  #139
MathMan
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Lafleurs' Guy, we've been over all that before. Personally, I'm not interested in spending more hours putting together the same answers just so you'll reject them out of hand again.

I've said this before, but if you have interest in serious hockey analysis, you're going to need to start looking at things below the surface level. Analytics are about finding out the right process. It is a basic prerequisite when discussing them to understand that the quality of the results do not always (and in a game as variable as hockey, often do not) reflect on the quality of the process; the right process gives you the best odds of the right results, but nothing is guaranteed. In other words, the team that wins may not have been playing well and the team that loses may not have been playing poorly.

This is a difficult lesson for sports fans, because it forces one to give up some much-cherished notions, most notably that the team that wins always "deserves" to win. It took me a while myself. It only really fully resonated with me after looking back at the way the Habs fluked their way to the ECF.

This, I suspect, is why you don't really understand analytics; you only view the game at the results level, and then only the shallowest, least granular level. The kind of stuff you find in the average sports section in the newspaper, basically, and you aren't motivated in actually putting those assumptions in question.

Now. Montreal, it is true, has gone through a number of upheavals and odd occurences lately which makes it a difficult example for analytics, unlike most other teams; it hasn't landed in the middle of the bell curve very much, it's been either feast or famine from 2007-2008 on out. It happens, but it means the team we follow the most is not the best case study for analytics compared to most others. But personally, I'm interested in finding out why the Habs end up where they are, on a level of detail you don't seem to be interested in. That's fine, but maybe it means that analytics are not for you.

ADDENDUM: Also, if you want to cogently discuss analytics in any depth, it's important to acquire at least a basic understanding of probability science. Not hockey analytics, just basic statistics-and-probabilities stuff. If you don't want to do that, that's fine, but again: analytics may not be for you.


Last edited by MathMan: 04-04-2012 at 11:05 AM.
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