Garik16 from Hockey Graphs, Lighthouse Hockey, and Islander Analytics wrote a good piece today on the defensive shell (a topic that’s been on my list to address for a while), following up on David Johnson’s initial look into the subject a couple of years ago. I highly encourage you to read both stories, but the general conclusion from today was that the shell doesn’t actually help a team because the opponent’s scoring rate – what you’re trying to minimize – actually increases. I had a couple of thoughts on the issue, because while the material is interesting, I don’t necessarily agree with the conclusions.
Today, the Toronto Blue Jays signed Canadian Catcher Russell Martin to a huge 5 year, $82 million contract. I’m no expert on baseball analytics, but I know enough to be able to find concepts to apply to hockey where possible. I have, however, seen many people making fun of this as a massive overpayment. They’ve called it “McCann Money” with the implication being that Martin is by no means the player that Brian McCann is. Now I don’t know how big the gap between the two players is, and frankly I don’t have the time nor the will to find out, but there is one factor fans – especially those who primarily follow hockey and thus appear on my feed – may not be taking into account that I’d like to address.
This piece from Trey Causey is absolutely spot on. If you’re involved in an organization in any sport, you need to give this to your President/GM/Owner. This is how analytics will help your team win, and luckily, you have a major first mover advantage – especially in something like hockey – because while teams are now using analytics, nobody is using it quite like this yet.
One point I’ll expand on quickly when it comes to hockey is the idea of time horizons. Coaches tend to worry more about immediate payoffs than GMs, because their jobs are more likely to be in immediate jeopardy if the wins don’t come. But that isn’t the way it should be. Coaches need to understand and employ analytics, but they also need to be given assurances that they will be judged based on process, rather than results. At least in the near term. All parts of the organization need to be moving in the same direction, and only then can output be optimized. If a GM isn’t willing to take that approach with a certain coach, then hire a coach with whom you’re comfortable enough to do so.
There’s an important difference between always taking the middle ground in an argument and recognizing nuance where many find none. Analytics are a case in which it is important to remember, whether it’s with corsi, or PDO, or fighting, or any other issue, that because of the imperfection of our metrics, our understanding of psychological factors at play, and our understanding of just what goes on behind closed doors, that what the numbers tell you isn’t always entirely accurate. This nuance is something that I’ve tried to emphasize with this blog over the past few months, and will continue to push. There isn’t a middle ground just because somebody says there should be…there’s a middle ground because of the number of factors in play that simply haven’t been taken into account by any model we have at our disposal right now.
There’s a fascinating look at skill development here that reminds me of an interesting anecdote I read in Sports Illustrated a while back. When people think of sports inefficiencies these days they think of analytics, numbers, Moneyball, etc. But those are just the most the most prominent modern manifestations. Back in the late 19th century, Baltimore Orioles manager Ned Hanlon began bringing his team down south prior to the season to work on their skills and ability to execute plays like the squeeze bunt and the hit and run. He had players field grounders and fly balls for hours every day, and his teams, more ready for the season than ever before, won three straight National League pennants, leading other managers to copy his practice and develop what has become known as Spring Training. Hanlon actually developed baseball’s first true inefficiency: fundamentals.
My story of the day from yesterday turned into a more extended column, so I decided to post it this morning.
There has always been a conflict between the values of analytically inclined hockey people (let’s call them analysts) and old-school minds (purists). I’ve written before about how my experiences have allowed me to gain some insight into both schools of thought, and in many ways fuse them into my views on the sport, but I wanted to bring up a couple of issues with regards to the questions surrounding Michel Therrien and his coaching following an absolute drubbing — both in terms of possession numbers and the score — at the hands of the Calgary Flames. Friend of the blog Andrew Berkshire wrote a great recap of the game and criticized Therrien for the team’s possession struggles, which is justified. But some other analysts tend to simplify the game down to a variety of semi-predictive statistics without considering other circumstances. I wanted to use this situation to share some more general thoughts on the use of analytics.