Pittsburgh Penguins Offseason Rants: Hockey Analytics and Their Place in the Sport

It’s the ever popular debate among the Pittsburgh Penguins faithful, and really all fans across the NHL. At this point, it seems that you’re either a fan of analytics in hockey or you aren’t. There is no middle ground.

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I’m the type of person that likes to use as many resources as possible when evaluating a team or individual. Part of that is to weigh the analytics behind their performance, as well as what I see from them on the ice. I’m probably the furthest thing from a statistician as you can get, but I’m continuously digging into the available metrics and interpreting them to the best of my ability. I can honestly say that I’m constantly learning something new about how to measure this data, and it’s actually quite fun.

I have a piece of advice for both sides of this debate. First, you have to realize that analytics in hockey are here to stay. The use of this information may be in it’s infancy, but NHL GM’s are catching on and realizing the potential here. Traditional media types are doing a lot to try and curb the interest in this information, but it’s a losing effort.

For the folks that are onboard, I recommend taking a step back and opening yourself to debate past what you see in charts and graphs. Trust me, I understand that numbers don’t lie, but there are situations where there’s more to a player’s numbers than simply running a report and charting them. How much has their environment impacted what they’ve done? What kind of trends have they showed and what type of role are they expected to fill? Are they a player that’s expected to produce points but find themselves failing to do so, despite solid possession numbers?

Chris Kunitz is the best example that I can think of as someone that requires more than just data. If you look at Kunitz’ underlying numbers last season they were outstanding. However, after a fast start in October and November, he only produced 20 points over the last four months of the season. Many cited his possession stats and continued to wait for a turnaround in production, but it never came. He’s paid to produce points, and he failed to do it. So, rather than ridiculing those that feel he was subpar by simply throwing charts at them, why not consider the different aspects of the game that impacted his production and discuss it?

Another player that comes to mind is Daniel Winnik. I was hard on Winnik for his performance with the Pittsburgh Penguins. But to consider him a total failure in Pittsburgh may be unfair to him based on the single most important piece of weighing this data in my opinion, and that’s player usage.

Injuries launched Winnik into a top-six role and put him a position to fail. He looked slow, out of place, and disinterested. However, the biggest issue was that he isn’t cutout for that type of role. You can’t place Daniel Winnik alongside Sidney Crosby and expect him to change who he is overnight. If Winnik remained a bottom-six wing throughout his stint with the Pens, there would be a lot less criticism of him.

I’m not going to pull a bunch of data or get into an in-depth discussion about a specific player’s performance here, as that isn’t what this article is aiming to do. I’m simply stating that advanced stats are here to stay, so it’s probably a good time to at least familiarize yourself with the basic concepts. And, if you’re already using this information, understand that it’s a tool and not the end-all be-all of player evaluation.

Hockey fans don’t have to be at odds over the use of data to measure performance. I’ve had folks tell me that they want to debate hockey and not math. I’ve heard that analytics will take the fun out of the sport because it becomes too focused on numbers and not enough on the game itself. But, I disagree. You’d be surprised how supportive the numbers are to your opinions and theories. You just have to be willing to give it a chance.

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