Practical Concerns: “The Blind Side”, Intangibles and My Off-Season Plan At McGill


(Photo credit: Derek Drummond)

At VANHAC, I was asked by a few people about how we use analytics in our program. Every season is different, and to gain a full appreciation of my intentions this summer, it’s worth digging into the central thesis of a football book.

What Really Drives Results?

“[Quarterback Joe Montana, wide receiver Jerry Rice and running back Roger Craig] are stars. They accumulated the important statistics: yards, touchdowns, receptions, completions. [Left tackle Steve] Wallace is not considered a producer. He has no statistics.” – The Blind Side: Evolution of a Game (Michael Lewis, 2006)

While Michael Lewis’ Moneyball did much to improve the popular understanding of analytics in sports, I happen to think that The Blind Side can help bridge the gap between traditionalist and numbers-driven analysts just as much as Moneyball did.

If you peel away the diverse storylines in The Blind Side, this is the central question behind Lewis’ book: What does a good left tackle do for his quarter-back (and by extension, their team)? And how much is that worth?

Very valuable, as it turned out. Unless an NFL team wanted your multi-million dollar quarterback seriously maimed by an opposing pass-rusher, it had better hire a left tackle with the size, speed and sense to keep up. The problem is, if this player does his job well, nothing happens that can directly be attributed to him – he has no statistics.

But conceptually, his impact on the game is not all that hard to identify. A good left tackle provides a safe, productive (and dare I say, fun) work environment for his teammates. By paying attention to the process of football, you can probably come up with a few good ways to account for that.


(credit: Derek Drummond)

Building A Bridge

When you arrive to this conclusion about football players, it becomes a lot easier to see why the idea of “being a good teammate” and “having intangibles” matters to people working in hockey. I’ve alluded to this elsewhere, but there are really two aspects to creating that good working environment for other people – one can’t be expressed in numbers conveniently, but I reckon the other already can be. Both matter a great deal to the end result, and to how people feel in the process to getting there.

I didn’t have time to really dig into this during my talk at VANHAC, but this is probably the most important realization I’ve had in two years working for the McGill Martlets hockey program.

Continue reading

How Can We Quantify Power Play Performance In Formation?

Screen Shot 2016-02-26 at 4.55.31 PM

Last week I wrote about a new metric, ZEFR Rate, which measures zone entry success on the power play and is relatively repeatable and predictive of future goal scoring efficiency. The metric was based around the idea that getting into formation efficiently — most frequently a 1-3-1 — is a catalyst for power play success.

But now let’s say you’re a team that has perfected your entry scheme, and you find yourself setting up in formation at a consistent rate. What now? How can one maximize one’s use of possession in formation to score goals at the highest possible rate?

Continue reading

ZEFR Rate: A New and Better Way to Evaluate Power Plays

Screen Shot 2016-04-17 at 4.49.36 PM

Some day we will reach the point where we can comprehensively analyze which power plays are the best, which players drive that success, and most elusively, what roles to place players in to maximize a unit’s output, but statistically, our special teams cupboard is pretty bare. This season, as many of you know, I took on the long and arduous task of hockey tracking in the interest of trying to get us even one step closer to our objective: how can we better evaluate and predict power play success? So let’s dive right in. Continue reading