Advanced Statistics for Beginners: Introduction

So if you haven’t picked up on it in Andrew B’s posts or in Mike’s A Modest Proposal series we’re getting nerdy on you all. Whether you like it or not, advanced statistics, sabermetrics, or any of a dozen other names are an increasingly important part of sports writing. And the reason why is as simple as can be: for as cliché as it may sound, numbers don’t lie. We can try to explain what we think we see on the ice or the field or any other playing surface, but it is not easy. Even if we could find every single clip from a game and pinpoint exactly when and what happened, there is still a lot of vagueness in attempting to describe what otherwise fails to meet the proverbial “eyeball test.”

And that’s where advanced statistics come in. These mathematical formulations quantify the unquantifiable; they give meaning to the indescribable, and now they will be part of our blog. Of course there are certain times where we all say reason and science be damned, there are certain times when the eyeball test is not reinforced by the numbers, and there are certain times where a gut-feeling is over-ridden by objective reality. We understand that and we are not setting out to be a numbers only blog. But which two sports could be more interesting to digest through statistical analysis than hockey and baseball?

Baseball is of course the granddaddy of all advanced statistics sports. As a sport with clearly defined roles and positions, clearly defined strategies, and inherently individualistic performance objectives, sabermetrics have been an essential part of the sport for longer than any of us have been alive. No sport uses them to a greater extent, and no sport can be quantified any better than baseball. On perhaps the exact opposite end of the spectrum is hockey—with players moving into and out of specified roles at a whim, with an extremely fluid playing surface, and with a great deal of team-oriented play culminating in nothing except “possession”—the process of quantifying hockey is still a relatively new phenomenon. As such I am dedicating the rest of this post to explaining a number of the important hockey metrics. These metrics will start to influence our posts starting Monday when we begin to layout our official Penguins season preview. The metrics we wish to explore below are Goals Versus Threshold (GVT), Points per 60 Minutes, and Player Usage Charts. Other metrics such as Fenwick, Relative Plus/Minus, and others may appear from time to time but for now GVT, Corsi, P/60 and Player Usage are the most informative, and more importantly the most well developed.

We have come to be completely enamored with the guys at and in fact, all of our stats will be coming from their most recent publication “The Essential Guide to the 2012-2013 NHL Season: Hockey Prospectus 2012-13” an incredibly well-written and well-researched document if I’ve ever seen one. We will split up each topic into separate posts, because although our explanations are very short they still take a few levels of explanation.


3 Comments on “Advanced Statistics for Beginners: Introduction”

  1. […] Advanced Statistics for Beginners: Introduction → […]

  2. […] we are at the third of a four part series, you can read the introduction here, and part 2 here. For a much more in-depth explanation of this methodology, please check out […]

  3. […] we are at the final installment of a four part series, you can read the introduction here, part 2 here, and part 3 here. For a much more in-depth explanation of this methodology, please […]

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