10 Rules Of Thumb For Hockey Analysts

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  1. The point of hockey is to create goal differential. The point of hockey analysis is to find ways to improve it.

  2. Shot differentials today is goal differentials tomorrow.

  3. 100-10-1. 100 minutes of your time to create data, 10 minutes of the coach’s time to digest the data, 1 minute of the player’s time to absorb the data.

  4. Optimise workload, reduce uncertainty.

  5. If your findings are either always or never surprising, then review your methodology. 80/20 (in favor of confirming existing beliefs) is a good place to start.

  6. Your priority is to help the coach get a better night’s sleep and to help players maximise their experience.

  7. Know your place, but stand your ground.

  8. We are all on the same team.

  9. Who you compete against influences your results; who you work with dictates your destiny.

  10. The job is only done when you’ve trained someone to make you expendable.

 

Jack Han is the Video & Analytics Coordinator for the McGill Martlet Hockey team (not his full-time job). He also writes occasionally about the NHL for Habs Eyes on the Prize. You can find him on Twitter or on the ice at McConnell Arena.

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

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(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.

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(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.

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The Shift: Breaking Down The L.A. Kings’ Secrets To Success

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By virtue of their 5vs5 shot differential, the Los Angeles Kings are the best team in hockey. As of Saturday night, the Kings are rolling along at 56.1% Corsi – #1 in the NHL by a long shot. In fact, the 3% gap between the Kings and the No. 2 Anaheim Ducks is the same as the one between the Ducks and the No. 15 Philadelphia Flyers.

So why are the King so good?

The simple answer is that they have good players executing a sound game plan developed by a good coaching staff. But how exactly does this manifest itself?

On March 26th, the Kings were beating up on the Edmonton Oilers in the middle of the second period when, in the span of 45 seconds, they put together – in my mind – a perfect, representative shift of everything that makes them a superior hockey team.

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Practical Concerns: Meatballs & The Art Of Deployment

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Last week, I dug up some old stats and posed this question to our Twitter followers and to a few people I know working in pro hockey.

Some interesting lessons were learned.

Information Underload

Marc Bergevin once said that it is difficult for fans to fully understand the decision-making process of NHL general managers and coaches because they don’t have access to all the information.

Most people I’ve talked to with at least a working knowledge of analytics were able to give very sensible suggestions on which three defense pairings to form given the available players, despite having no idea of who these players are and with only their 5vs5 With or Without You possession stats at their disposal.

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Practical Concerns: Analytics Resolutions For 2016

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Just a few hours into 2016, I had already received an email from a colleague in NCAA Division I hockey program, asking for my feedback on a specific area of analytics.  It goes to show that those who enjoy thinking the game never stop doing it, even on days when they should be giving themselves a little time off.

Since everyone is making New Years’ Resolutions, allow me to share the two things I will be working on this year:

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Practical Concerns: The Gift Of Goals

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Lighting the lamp is the hardest thing to do in all of hockey, and scoring is down yet again in the NHL.

But instead of talking about ways to make goalies worse, by reducing the size of their equipment or by limiting what they can do on the ice, let’s look at a few habits shooters can acquire to shift the odds in their favor.

While the statistics and research behind the information presented here come from the NHL and CIS levels, I’m confident that any player – from Peewee to Beer League – can put them to good use in 2016.

I’ve already written about scoring in the shootout, so here are four scientifically sound tips for scoring more in open play.

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Exploring the Impact of New NHL Coaches and GMs

With Todd Richards being let go after a disastrous 0-7 start by the Blue Jackets, and Bruce Boudreau on the hot seat (heck, he might be out of a job by the time I finish writing this), coaching is once again in the spotlight. After Richards was fired, I went on a mini rant about how I believe having a good GM is more important than having a good coach, and while I still believe this is true, I wouldn’t be a data person unless I tried to prove it.

This project has many parts to it. The first, which I’ll be doing here, is just looking at the breakdown of Scoring Chances For% compared to Coaches and GMs in the early days of their tenure, i.e. right after being hired. Scoring Chances, to simplify things, are basically “more dangerous shots” (click here for a more rigorous definition).

To start, I needed data. I pulled all 30 teams from 2006/07 to 2015/16, and coded each season by what kind of organizational changes happened within. This gave me 331 data points, as there were often midseason coaching or GM hirings to account for.

The states broke down like this:

1) No Change – 64%
2) Hired a new Coach – 21.5%
3) Hired a new GM – 7.3%
4) Hired a new Coach & new GM – 7.3%

In looking at the data, some patterns quickly emerged. The first two years of tenure in either role were where the most change, for better or worse, happened.

Because I had so much data in the No Change category, I wanted to see if there was any sort of trend year over year for the control group.

No Changes - Coaches SCF Delta YoY

No Changes - GMs SCF Delta YoY

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Practical Concerns: My analytics pot roast

Credit: Stuart West

Credit: Stuart West

Despite spending a lot of time at the rink watching hockey, most of my talents lie outside of the game. One of my favorite things in the world to do is to cook. And my favorite thing to make is pot roast – a big portion of the cheapest cut of meat from the butcher shop, cooked on low heat for seven hours in bottom-shelf red wine with some onions, carrots and a secret spice mix.

Making good food is a nifty ability to have on its own, but having more or less grown up in the kitchen, I can also appreciate how the process behind cooking has practical applications in sports. Ingredients, technique and (just as importantly) timing is everything when you’re cooking, and those three things matter just as much when you are trying to improve a hockey team.

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Practical Concerns: How I do video

Video is the best teaching tool there is.

Video is the best teaching tool there is.

Preparing and organizing game footage is one of my main responsibilities working for the McGill Martlet hockey team, and has become something that I enjoy quite a bit over the course of the past two seasons. Having played for coaches who use video analysis to various degrees in both hockey and tennis growing up, I think seeing one’s self play sports on video is the best way to correct deficiencies and identify areas for growth.

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