Practical Concerns: A Better Way To Talk About Hockey?

“The Pittsburgh Penguins won.” “The San Jose Sharks lost.”

Do those statements have the same meaning? The answer depends entirely on what you mean by meaning.

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Following the suggestion of my friend Arik Parnass, I’ve began re-reading the book Thinking Fast And Slow, which explores many ideas that can be applied to hockey.

One of the chapters in the book deals with the concept of framing – how people can be influenced to think about a certain situation depending on the words used to describe it. Going back to our initial example, did the Penguins win the Stanley Cup (because of their superior tactics, teamwork and talent level)? Or did the Sharks lose the Stanley Cup (because of their reliance on defensemen who are slow and can’t make a pass)?

There is no right or wrong answer, but we can see how a simple difference in phrasing can lead us down different avenues.

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Video Analysis: How The Penguins Extend Zone Time With “Total Hockey”

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By any predictive metric, the Pittsburgh Penguins have generated a staggering amount of offense against the San Jose Sharks in the Stanley Cup Finals. Earlier this week, we looked at how the Penguins are able to create possessions with good defensive habits in the neutral zone. Today, we’ll examine how they create a volume of offensive chances via positional switches.

To fully understand the ideas behind the Penguins’ offensive zone play, it is necessary to study the “Total Football” philosophy:

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The line of thinking lends itself well to the speed and teamwork-oriented nature of hockey as well. While the Penguins are by no means the first team to apply these ideas, they are a good example of how they can be used effectively at the highest level of the game.

Here are some clips from Game 3 and Game 5 of the Stanley Cup Final illustrating the tactical benefits of fluidity and positional switches.

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Video Analysis: In the Penguins-Sharks Stanley Cup Final, Possession Starts With Good Defensive Gap

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In the playoffs, details make the difference.

Heading into Game 4 of the Stanley Cup Final, the Pittsburgh Penguin have had the measure of the San Jose Sharks in terms of shot differential. Looking at the game tape, we can see that one of the contributing factors is the way both teams defend the rush.

As a group, the Pens’ defensive corps is fleet-footed and blessed with good offensive acumen. They are also undersized and prone to being muscled off the puck by San Jose’s skilled forwards. In order to minimize their exposure to defensive-zone breakdowns and to maximize the team’s speed and skill, the Penguins have been playing a very tight gap across the neutral zone, funneling San Jose puck carriers toward the end boards and standing up at the red line in order to encourage the Sharks to dump the puck in.

A hallmark of the Mike Sullivan-coached Penguins is the team’s attacking mindset on and off the puck, as evidenced by the way they suppress the San Jose transition game.

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Practical Concerns: On Randomness, Risk-Taking And Coaching

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Something I set time aside for during the off-season is reading non-hockey books in an attempt to gain a better perspective on hockey. The work of Michael Lewis (Liar’s Poker, The Big Short, Boomrang) and Nassim Taleb (The Black Swan, Fooled By Randomness) were of particular inspiration.

Below are some assorted thoughts based on recent readings and events. Tweet me (@ML_Han) if you’d like to disagree and tell me why. Eventually I hope to spend some time talking about this or a tangential at the second edition of RITHAC this September.

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NHL Analytic Teams’ State of the Union

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Fandom means a lot of different things to different people. But one thing unites us all: we hope our favorite team will win, and spend a great deal of time thinking how they can.

For those of us who dig a little deeper on the “how” side and use analytics, we hope that our work will eventually make its way to a front office. In some ways, it already has: numerous “hockey bloggers” hirings have been made recently.

But how many and for which teams?

With some research, I’ve culled a working document on all analytics hires for NHL teams and how they may be using analytics. The following descriptions comes from a variety of sources including Craig Custance’s Great Analytics Rankings [Paywall], fellow bloggers from across the internet, media reports, word of mouth and anonymous insiders.

It should be noted that just because a team has made an “analytics hiring”, it doesn’t necessarily mean that they value their input or use the analysis provided properly. In fact, hires can be made simply for PR reasons, and some teams may even give analytics tasks as secondary duties to staff members who do not posses any formal background in the subject. Teams may also have hired private firms providing proprietary data, which in reality may not provide any tangible, verifiable value than what is free and readily available online.

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A Tank Battle in Pictures: Toronto Maple Leafs, Edmonton Oilers, Arizona Coyotes, & Buffalo Sabres in 2014-15

Having just added the 2014-15 season to our historical comparison charts, now was a good time to revisit (as I promised in my posts here and here on Pittsburgh’s 1983-84 tank battle) this season’s battle between Arizona, Toronto, Edmonton, and Buffalo. To do this, I tracked the progression of each teams shots-for percentage across two periods (or 2pS%), a possession proxy I developed for historical data that can help us compare teams back to 1952. As you can see above, the perception of the tank battle among these four teams wasn’t quite accurate to their results; Edmonton and Buffalo did not seem to have a marked drop-off in the final quarter-season.

Arizona and Toronto, on the other hand, did noticeably drop, and in Arizona’s case to a level below the hapless Sabres. Ultimately, the fight was more to maintain their improved odds, because Buffalo managed to hold at rock bottom. As I asked when I wrote about the topic with Pittsburgh in mind, it still gives rise to an interesting question: is it more wrong to tank than to maintain a low level all year? In some cases, a team that’s already laid low doesn’t need to tank deliberately…but on the flip side, I suppose that team also assumes risk in losing support and fans by not appearing competitive all season.

How did the Coyotes and Maple Leafs compare to what I’ve christened the “gold standard” for tanks, the 1983-84 Pittsburgh Penguins’ tank for Mario Lemieux? Well, the nice thing is that the plus- and minus-one standard deviations in 2pS% were virtually identical in 1983-84 and 2014-15, so I didn’t have to tinker with them:

While Pittsburgh had probably the starkest, earliest drop-off, both Arizona and Toronto were able to reach the same kinds of lows by the end of the season. To their credit, while the Coyotes and Leafs were, at best, in the lower half of the league in possession, they certainly did their best in the race to the bottom. You could question the wisdom of this kind of thing, since Pittsburgh was guaranteed the top pick if they reached the cellar, while this year’s tanks were struggling for a higher probability.

The Greatest Tank Battle: Penguins vs. Devils, 1983-84

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Mario Lemieux with Laval of the QMJHL in 1984; photo by http://www.lhjmq.qc.ca/ via Wikimedia Commons

What do you do when a 6’4″ QMJHL forward who scored 184 points in 66 games in his last underage season scores at a 282-point pace in his draft year? You tank — you tank as hard as you can. In the latter half of the 1983-84 season, the Pittsburgh Penguins and New Jersey Devils were in an unspoken, pitched battle for the bottom of the league and everybody knew it. While the Penguins would ultimately win out, sputtering to a 16-58-6 record (“good” for 38 points in the standings) to New Jersey’s 17-56-7 (41 points), the two teams were coming from distinctly different franchise backgrounds.

Using information from our new interactive charts, we can see what set these teams apart, and led them to take different paths in what turned out to be a pretty wild race to the cellar of the NHL.

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The Art of Tanking: The Pittsburgh Penguins in 1983-84

While tanking is a hot topic in this year’s NHL, the act of tanking is as old as the idea of granting the worst teams a shot at the #1 pick in the draft. Case in-point: the 1983-84 Pittsburgh Penguins, routinely considered the most overt of tankers in NHL history. The graph above is just one example of their tank, and man is that bad. The yellow and grey lines indicate one standard deviation above and below league-average historical possession (using 2-Period Shot Percentage, or 2pS%, explained here). The blue line is a 20-game moving average (the orange is cumulative), and you’re seeing that right; a team close to the middle of the pack dropped nearly two standard deviations, or from near the top to near the bottom of the league. That graph, and all the ones below, are just some examples of the kind of tinkering you can do with our new interactive graphs, which I highly recommend you check out.

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2014-2015 Season Preview: The Metro Division

Image from Michael Miller via Wikimedia Commons

Last year, in preseason, the Metro Division, was considered by far the strongest division in the East and the likely bet to take both Wild Cards.  The whole division, minus the Pens, promptly started the season by getting hammered, only recovering later in the season to grab one of the two wild cards.

This year again, the top 5 of the division looks strong enough to take two wild cards.  The bottom 3, particularly the bottom 2, are very weak, but the top 5 is strong and near evenly matched such that they could wind up in any order.  But, given the requirement to project the division, these are how I believe the division should finish up, from worst to first:

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Using NHL Coaching Changes to Identify Historically Good and Bad Coaches

Iron Mike no like. - Photo by "Resolute", via Wikimedia Commons; altered by author

Photo by “Resolute”, via Wikimedia Commons; altered by author

Having now looked at the overall effect a coaching change might have on a team, and identified some outstanding examples where a coaching change had a drastic impact on a team, it’s now time to shift over to some juicier matters. For the most part, I don’t think one coaching change is necessarily sufficient to say a coach is good or bad; there is a possibility the previous coach was just that bad. But if the coach returns the same signal a couple of times or more, you are probably getting closer to a true reading on what they might bring to the table.

Across the 140 or so coaching changes these last 60 years where both coaches led the team 20+ games, there were 69 coaches who were a part of that change twice or more (which, to me, is quite a remarkable number). The full list, followed by an explanation of the measures:
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