What we got here is failure to communicate


The Hockey News published a piece on hockey analytics the other day, which set off a tempest in a teapot on Twitter (no, really).

Yes, it was about analytics, but no, this one wasn’t questioning their value or usefulness. In fact, it was quite the opposite.

THN associate editor, Ronnie Shuker, made the case that the problem with analytics isn’t the stats and the analysis, it’s the way they are communicated. And in many ways, I tend to agree with him.

Sure, his piece was at times condescending, but the premise has a semblance of truth to it, even if his conclusion is unsupported by evidence.

But I’m not here to parse the Shuker piece. Instead, I’d like to offer my own thoughts on the state of hockey stats writing and maybe some suggestions on how to improve it.

The fact of the matter is that Shuker is right when he points out that what’s stopping statistical analysis from being more widely accepted is the way it’s presented, and not that casual fans don’t want it. I mean, sure, there are some out there that don’t want it and are actively hostile toward anyone that wants to turn their love of the game into a number crunching excercise. But if you’re a budding analyst, that shouldn’t be your target audience.

Heck, if anything, take those comments as a badge of honour. The fact is, this is the Internet. There is both an audience for everything, and trolls that will rail against that thing. The problem is, while the former represents a much larger number, the latter are much more vocal about it:


I’m all for the old adage that you should never read the comments, but if you want to know how you’re doing in your quest for world domination through hockey blogging, you need look no farther than the number and emphaticness of the comments on your posts. The stronger the vitriol, the wider your audience. Really.

But back to the task at hand: how can we improve the way we deliver statistical analysis in ways that enhance and engage a broader audience instead of turning them off?

Well, let me show you a real life example of how I think this is done really well in a completely different field.

If you think hockey stats are arcane, they have nothing on macroeconomics, yet Paul Krugman has had a very successful and popular run as a columnist in the NY Times writing about exactly that.

Here he is last November writing about the implications of near term interest rates, which handcuff the ability of central banks to apply monetary policy to improve the economy (essentially, they can’t lower the rates below zero, so they’re stuck in a trap). I don’t actually expect you to read that whole thing, but it’s written for a mass audience.The language is clear; there’s little, if any, jargon; and he doesn’t bother trying to explain terms or concepts that would derail the flow with too much technical detail.

He is trying to get a very basic point across, which is that normal policy options either aren’t available or don’t work when you’re at near-zero interest rates. And he tries to do that as clearly and succinctly as possible with examples and language that his audience can relate to. He doesn’t dumb it down. He just tailors the writing style and level of detail to his audience.

Now here he is on his blog writing about essentially the same thing. He’s way more casual and conversational on his blog, but he’s also more technical and at times can get into the minutae of macroeconomic theory (wonkish, as he calls it). But this is entirely appropriate. He knows that the smaller subset of people that read his blog posts have a deeper level of understanding of these concepts (or at least want to learn more about them). And even then, he labels the particularly arcane posts with (wonkish) in the title, so that you know what you’re getting yourself into.

I should add in a word about charts, here. The fact is, the vast majority of people don’t get charts. I know, it’s a heartbreaking thought, but it’s true. So it doesn’t matter how pretty you think your chart is, if you’re trying to reach a broad audience, don’t include it. And for God’s sake, if you do, keep it as absolutely simple and uncluttered as possible. Make sure you are clear on the one point you’re trying to get across and eliminate everything else that still allows you to get that message out.

I bring this up because if you go through Krugman’s columns, you’ll hardly ever see a chart or graph. Yet his blog is peppered with them. Again, like the writing style, that’s because the blog audience is more technically inclined and much more likely to appreciate and even want information that is passed on graphically. At the very least, they aren’t turned off by them.

In general, Krugman uses his blog to communicate the results of thinking and analysis that he’s arrived at through application of existing models or previous work. He doesn’t ever derive anything new there. Sometimes he shows his work, as he outlines the logic behind a conclusion, but more often than not he’s working within accepted knowledge with concepts that those familiar with the general topic will understand without much explanation.

When he does derive something new, it looks like this. It’s not full on academic journal writing, but it’s close. And in macro, most of the new ideas are now disseminated through these types of academic working papers rather than published in journals anyway. But the point is that the writing is much more technical, the formulas are shown and the intended audience is very, very small. His goal is to outline a new way of thinking about a topic (the same liquidity trap that is at the core of the other two pieces I’ve linked above), and to show the logic behind this approach and how he came to his conclusions.

So why did I take you on a tour of modern macroeconomic writing? Because I think Krugman does a really good job of writing with the audience in mind. He knows what he wants to say, why he wants to say it and who he wants to say it to. Once you’ve got those figured out, the how is part is easy:


To bring this back to hockey analysis and writing, clearly most of it right now is being done at the blog level, and that’s ok for that form of media. But for those that have earned the opportunity to write for more mainstream publications, I encourage you to think more about what that broader audience you’re reaching might actually respond to.

Don’t throw more stats and charts at them. Sure, use them yourself to formulate your opinions and draw your conclusions, but then tell them a story. Don’t dumb it down, but put it in terms they will understand. Use real life examples that they can relate to.

And whatever you do, don’t read the comments.

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