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The art of hockey analytics

NHL teams are crunching numbers like never before

Welcome to the NHL of the 21st century — an analytics arms race where the 30 teams are not only waging war on the ice, but looking for every kind of advantage they can find off it by crunching numbers on their players into a variety of metrics

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"The New Jersey Devils are looking for someone with the passion, intelligence and experience to lead its hockey analytics group. The position reports directly to the President and General Manager, Lou Lamoriello. Interested applicants should have a deep understanding of both hockey and advanced data-centric techniques to analyze games, players, and rosters. Experience on/around the ice is a plus while a deep passion for NHL hockey is required. Experience in statistics, data science, econometrics, computer science, or other data-driven fields is a must. The position will office in the Prudential Center in Newark."

—Job posting on NHL.com

Kevin Mongeon and Mike Boyle grew up together in Iroquois Falls, Ont. They played hockey together and kept their passion for the sport. All sports, really. The two started collecting hockey data in grad school, got to know more people in the game and then began doing the consulting thing as principal owners of their company, The Sports Analytics Institute.

And, like Tulsky, these aren’t just a couple of beer-leaguers when it comes to providing analytics information to their clients, who are spread out over a variety of industries.

Boyle is an Assistant Profession of Information Systems in the David Eccles School of Business at the University of Utah and has a Master of Science from DePaul University and a Bachelor of Mathematics from the University of Waterloo.

Mongeon is an Assistant Professor of Sport Management at Brock University, has a PhD in economics from Washington State University, his MBA from the University of Windsor, and his mathematics degree from a Lakehead University.

A small taste of what they can provide: not too long ago Mongeon and Boyle created PGS (Trademark) — Predicted Goals Scored — that calculated the predicted number of goals for and against while a player is on the ice and "accounts for shot characteristics including but not limited to shot location and type."

Old Stats: Plus-Minus

Click to Expand

New Stats: Corsi

Measures the difference in shots directed at a team’s net — including goals, saves, blocked shots and missed shots (excluding empty nets) — versus shots at its’ own goal. Used to track both a team rating and for players individually and is an effective measurement for puck possession. The more shots directed at the opposition net by a team or when a player is on the ice, the better the Corsi rating, which is expressed as a plus/minus or as a percentage (example: Blake Wheeler’s 49.9 Corsi is calculated because he was on the ice for 1,103 shots for by the Jets and 1,107 shots against).

Corsi can also be broken down further depending on offensive, defensive and neutral-zone starts (where on the ice a face-off takes place) as well as situationally depending on the score and the quality of competition or linemates on the ice.

Worth noting:
Corsi does not take into account special teams or goaltending, which can greatly impact wins. But as a possession baseline, Corsi teams are more likely to make the playoffs and more likely to go further into the postseason.

Background:
Created by former Quebec Nordiques and Edmonton Oilers goaltender Jim Corsi, who is the long-time goaltending coach of the Buffalo Sabres.

FYI:
Corsi can only be tracked back to 2007-08 when the NHL began providing detailed play-by-play of its games, meaning hockey fans will never know the rating for legends like Wayne Gretzky, Orr, Gordie Howe and the like...

The Top 3 Corsi players in the NHL in five-on-give situations this season were:
1. Patrice Bergeron, Boston (61.2%);
2. Jake Muzzin, Los Angeles (61.1%) and
3. Anze Kopitar, Los Angeles (61.0%).

L.A. (56.7%), Chicago (55.2%) and San Jose (54.6%) had the top team Corsi ratings.

They do a ton of other analytical work but, again, they aren’t going to offer up a lot to non-clients in a public forum.

"We take all this raw data and put it into a model or ‘black box’ and out comes some derived statistics that when you look at them in relative terms they more accurately describe what’s going on in the game or what a player is doing from a productivity standpoint," said Mongeon from his office in St. Catharines. "That then allows management better evaluate the players on the team.

"It’s just a different way to look at existing players and players across the league."

What Mongeon and Boyle find now is that with so much information out there and more clubs buying in to the power of analytics, they are doing more and more consulting for teams.

Essentially, they are hearing from sports-management types who are asking for help to just weed through all the stuff that is out there, how to determine what it all means and then use it effectively — if at all.

"A lot of teams are stumbling their way to it," explained Boyle, from his office in Salt Lake City. "Look across the different leagues, look at baseball, at football and basketball... we’re seeing people getting hired in analytics, but he often has other responsibilities. If you look at the head of analytics for any major league baseball team he has engineers working for him. I’m not saying you’ve got to go big, but you can’t take something that is of high importance to you and then stuff it down to the lowest guy on the totem pole and ask him to do five other things at the same time.

"Now, some of the best teams in the best leagues have reached out to us for this help. We had a conversation with a top team in another league, not hockey, and they asked us for help. They said, ‘We’ve hit a plateau. We need to get better.’ But yet we have conversations in the NHL where it’s ‘You need to give me this. I know what I want.’ I’m like, ‘Respectfully, I don’t think so...’

"This is the way most teams have gone about addressing their analytical approach: we got a ton of calls after Moneyball, the movie, came out. Owners were saying ‘What’s your Moneyball approach?’ But, at the end of day, I often heard something like, ‘I just need to have some sort of analytics so that I’m covered’ as opposed to embracing it as an approach. That’s changing now. It’s like a lot of us: our parents taught us a lot of things growing up, but we had to learn a lot of them again for ourselves.

"The NHL started later than Major League Baseball," Boyle added, "and if they were thinking clearly they would hire people from NFL and MLB to help them and give themselves a shot in the arm and skip through some of the mistakes they would make along the way. Hockey has an advantage in terms of being able to see into the future. Maybe it’s moving faster than we think. But we need a team to go out there and say, ‘It’s good for all of us as a sport if we’re all using analytics, but we’ll just continue to maintain our lead by hiring the best talent and having an analytic agenda than the other organizations.’

"Right now it’s as if somebody has the Colonel’s secret recipe and it’s about how long can they hold onto it."

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