Great piece in Harvard Business Review about FC Barcelona, who recently won soccer’s prestigious treble, and the way in which they attract players. In hockey, teams talk about “instilling a culture” or “fostering a winning culture” a lot, but it’s not usually specific beyond that. The Bruins, with their smashmouth play over the past decade are probably the closest recent example of a team searching for a specific kind of player and intimidating opposing teams with a specific identity, and obviously the Broad Street Bullies are an older illustration of this. Barcelona is successful because it is rich, but also because it has always been a team built on skill above all else, so skillful players want to play there, good players want to play there, and because of the success of La Masia, the team’s academy, kids want to play there as well. Coaches and players come and go, but the fans know what to expect, and they feel that something is special to them. It brings the best out in the team, and ultimately leads to success.
It is something that, depending on where I was in a rebuilding cycle, I might look to establish if I were an NHL team executive.
I don’t have a ton of time to blog at the moment with finals coming to an end, but just wanted to throw this up quickly with Ray Shero becoming the New Jersey Devils’ new General Manager and the questions about his seemingly poor draft record. Corey Pronman wrote a nice piece a while back about why Shero’s record in particular is underrated, but I wanted to more briefly examine a few more general reasons why I would be weary about being too reliant on such a history or lack of history of success.
1. Small Sample Size.
One of the central themes with regards to analytics in hockey is that we’re trying to maximize sample size in order to get the most accurate possible view of a player or team’s talent. This is no different with regards to drafting. The fact is, a GM can only draft on average seven players per season, meaning that over the course of, say, a five year tenure, that’s only 35 picks. Some may get hurt, some might lose their love for the game, some might develop better than others simply as a result of random variation. It’s very difficult to isolate real success based on 35 or so picks – which is one of the big reasons why drafting also appears to be so random based on studies in just about every sport.
Kyle Dubas had the following quote in Elliotte Friedman’s great 30 thoughts columns this week:
“Here’s the way I look at it,” he said. “Right now, we aren’t good enough to be picky about smaller players. We need as many elite players as we can. If we get into playoffs and are too small, or overwhelmed, it’s easier to trade small for size than draft for size and trade for skill.” (bolding my own)
The quote struck me as interesting because it takes a fundamentally different angle on the size debate than the one I personally ascribe to, and I wonder whether it is simply a matter of semantics, or whether there is actually more to this.
My sense was always that size is not easier to trade for than skill – assuming we mean top 6 size and not grinder size – but that the reason you want to draft for skill was simply that skill players have a higher success rate than big players who don’t score as much. You prefer guys who can score over guys with size because once you accumulate enough of them, you can overpay for the big players that have succeeded, and not bear the risk that they may be busts.
Thank you to all who attended the DC Hockey Analytics Conference (#DCHAC) and watched via livestream. While there were some technical difficulties that prevented us from recording all of the presentations, we did manage to salvage a good portion of them. Here they are, as well as all of the slides.
Arik Parnass – Opening Comments & Introduction to Analytics
Slides: Intro to Analytics
When Peter Thiel, co-founder of PayPal and Palentir and the first outside investor in Facebook, conducts interviews, he always asks one very difficult question.
“What important truth do very few people agree with you on?”
I’ll wait while you struggle to find an answer that suits you individually….no go ahead….okay maybe table that for later. While straightforward, it’s an incredibly difficult question both because most of the knowledge we accumulate – particularly when it comes to conventional education – is widely agreed upon, and because in an interview setting, answering it inherently involves voicing an opinion that the interviewer doesn’t share. It takes courage, and courage is something that Thiel feels is lacking.
For those of you that have been following me for a while, you’ll know that I don’t throw around the term “must-read” every day. I reserve it for an article that I truly feel every person with an interest in hockey, sports, analytics — whatever it may be — has to take a look at. Take my word for it, therefore, that when I classify an article as one of the top 10 I’ve ever read, I’m not exaggerating. I would produce a list if necessary. This recent piece by Joel Achenbach is absolutely in my top 10. It is a great read on the scientific process, but it can be applied to analytics and sports and really any aspect of life.
Here are just a few excerpts from the masterpiece. It’s not too hard to draw the necessary inferences when it comes to hockey analytics.
I’ve written about the Cubs and their growing use of analytics before at this blog, and while I thought I had, it turns out I haven’t explicitly written about the Houston Astros and their extreme uses of analytics – in essence, treating their players as exclusively products and maximizing assets without regard for morale and the slippery slope that can result from that – but others have, so I would direct you here and here if you’re not sure what this paragraph is in reference to.
With Net Neutrality the hot topic today, in particular this article in the New York Times, I thought I’d post an op-ed I wrote about the topic for a Media Law class last semester. I can’t say I’ve stayed up to date on how the issue has evolved since the time this was written (November), so if anybody has new information they’d like to contribute, feel free to post in the comments. Here it is:
We’ve all seen it; we’ve all been captivated by it; we’ve allowed ourselves not to question it because it’s the American journalistic dream: take boring old news and make it interesting to the average consumer. John Oliver, television’s newest comedy anchor, has been great for American awareness. Unlike his contemporaries, Oliver has managed to not only entertain, but also to incite protest. The foremost example has been Oliver’s rant on Net Neutrality, in which he compelled Internet commenters to send complaints to the Federal Communications Commission, urging it to reconsider legislation that would, according to Oliver, fix a problem that doesn’t exist. And comment they did, as the FCC’s website crashed as a result of a wave of traffic the very next day.
On Sunday, the NHL’s website published my long read on the place of analytics in hockey and why they are so critical. As you know if you read it, it contained a lot of material, and good for you if you managed to understand it all. It was the product of months of revising and editing, and in the end a complete section needed to be cut. I made the decision to cut that section – which focussed on evaluating defense – in order to add substance to the other sections, and because I didn’t think it entirely fit. Here is that section:
EVALUATING DEFENSE WITH ANALYTICS
Evaluating defense is an area in which analytical findings have helped to shape perception. Conventional analysis dictates that the best players at preventing goals do so through proper positioning, good stick-work, blocking shots and hitting the opposition. Those things can be important when the other team has the puck, of course, but they don’t paint a full picture of a player’s effectiveness at preventing goals.
Stefan Wolejszo over the past year has written at a compelling blog called “Integrating Hockey Analysis”. With a background in analyzing both qualitative and quantitative variables, and research and expertise in sociology, Stefan made some very intriguing points on how to avoid the heated analyst/purist debate that has permeated the blogosphere and Twitter over the past few years. He has also done a great job of describing ways in which a team could incorporate analysis of latent variables (often referred to as intangibles) into evaluation of players and teams.