Why Analytics Need to Take Over Hockey

Analytics in hockey. A much discussed and quite the controversial topic among hockey fans. The debate of “shall analytics be incorporated into the game by general managers and coaches like baseball has, or not”. For years now, it’s been something that fans have discussed, and fairly, there are solid points from each side. For example, analytic deniers have the argument that judging a player purely off of analytical value is a poor idea, but vice versa, leaving them out completely would be a thickheaded decision.

Everyone is entitled to their own opinion, no matter how dumb or unreasonable it is. So, in today’s article I’ll go over my personal opinion on where I stand in the analytical debate.

Where I stand:

I think analytics are a beautiful and relevant part of hockey in the 21st century. As early as the late 2000s, advanced metrics were turned a blind eye on and they were never actually taken too seriously. Obviously the boys club general managers have the mindset that “advanced stats are bad! The game isn’t played on spreadsheets, instead grab a hockey stick and get on the ice”. Even to this day, there are older hockey fans that still see eye-to-eye with this notion towards these stats. Dare I say, even some NHL managers refuse to work around the basis of analytics.

To those older hockey fans, statistics are goals, assists, points, and penalties in minutes. That’s not the case whatsoever. In fact, analyzing players based off of those four painfully mundane “stats” makes my head spin.

The issue with those quota “basic” statistics, is that they miss context and they never actually objectify the full story to that player’s playing style. For instance, a player could have a hundred points. That’s great for the player, happy that he could accomplish such a strong achievement. But what if that player is playing on a line where he gets so called “carried”? That’s where the quality of competition and the quality of teammates comes into play. Using that analytic scale to determine whether a player’s skill comes from his linemates, or if the player is the moneymaker.

Analytics help you tell the backstory. That’s what’s so great about them. A basic fan or a more casual and newly-made spectator would see a player and consider them as a good player if they score lots of goals or record a high amount of points. Reasonable. But a more experienced fan that’s adapted the usage of these metrics, will look further than the basic points. But there’s one thing no fan will see, and that’s the smaller things a player does. To list a few things: zone possession and zone exits, shot contributions, play driving, and entry passes. Again, those are the more basic analytics when it comes to advanced stats.

For those reasons, I’ve started to study analytics and attempt to bathe myself in the glory of them. I’ve fallen in love with analytics and I use them every day to asses, and understand hockey players. Whether it’s goalies, skaters, and prospects, I’ll use analytics from different creators, and apply my analogy on them. I’ve also started to code and learn how to create my own analytics, but that’s not important for this article.

Why analytics are important in today’s game:

As mentioned earlier, analytics help you get a better understanding of the game. When it comes to stats, they can be used for anything and everything. You can learn about the players, the team’s success, and even the small things like where a team struggles when they shoot on the powerplay or where on the ice they get scored on the penalty kill the most.

One of my favored analytical creators are Andy and Rono. Their stats that show off goalies, skaters, and team’s play, have been a great help to make the harder parts of analytics much more easier to understand. Their charts are relatively straightforward.

Lets use analytical god, Jack Johnson, as an example. On his player card, Andy & Rono include a lot of analytical (and basic) keys. To reflect, even strength offense and defense, scoring, and passing are some of the more basic aspects to the chart. They’re easy to understand and they’re fun to look at.

They also have some in-depth things. For instance, they’ve got entry passes, possession exits, and high-danger assists. Those are some of the harder and more confusing stats to calculate and present, but A&R managed to show them off in simple and easy ways to let even the newest fan understand. Give the guys a follow on Twitter, @HockeyStatsCZ.

Another analytical creator that makes analytics fun and easy to understand, is Jfresh. @JfreshHockey on Twitter, has created a patreon where he creates a ton of easily accessible statistics. I would place him as one of the best, if not the best, analytical visualizer in all of hockey. He has interactive stats such as contract production projections, daily statistics, and his infamous player cards.

Didn’t choose an analytical god this time, but here’s Zach Parise.

The great part about Jfresh’s player cards is that it expresses a player’s analytical skill using an easy-to-read plot. It’s got even strength play, WAR (wins above replacement), powerplay, penalty killing, finishing, goals for per 60, yada yada yada. Basically it’s the juicy stuff that you see everyone posting and talking about. But another aspect to his player cards is that you can decipher the weighted average of the past three years (or less depending on how long the player has played). The WAR and all the other tiny boxes you see are the weighted average from the past three years. Essentially, the stats you see from Zach Parise isn’t only from this year. It includes his last two seasons with the Minnesota Wild as well. On the very right side, the card demonstrates two miniature graphs. One representing the WAR on a three year scale using an ogive graph. Using another linear graph below, it gives us the even strength offense, even strength defense, and finishing over the course of three years. This lets us see how a player has trended from three years ago, to today’s date. For Parise in this case, he’s managed to stay an offensive productive player, but the defense has stabilized in the 25% range to 10% range. The finishing on the other hand, has had a steep fall. Notice how when the finishing fell in 2021-22, his WAR also had a steep fall. That’s because the player card loves its finishing. Wins above replacement takes into account a lot of smaller details, but it takes in finishing the most, and that’s why it’s had this much of an influence.

Then there’s a few more difficult ones that we won’t go over, for the sake of saving time. Evolving Hockey and Hockey Viz are two very important analytical sites that have created a ton of charts, graphs, plots– you name it. Most people stick with Jfresh, but I personally use Evolving Hockey the most as they’re the most advanced and have the most information out of anyone else, despite how difficult it is to understand. It took me some time to learn and get used to, but I implied it into my daily life and have learned to love it.

So why are analytics so important in the modernized game of hockey? Because they help us get the full understanding for a player. Now I don’t care who you are, a fan, a pro scout, or a rhinoceros, your eye test isn’t perfect. It will never be. You can watch and scrutinize a player your entire life, but without analytics, you won’t get the real story with the player.

Sure he may be a fast skater with a good game sense, but what sort of impact does he have to his team? That’s something you won’t easily find while simply watching the player. That is why analytics exist, so you can see the difference the player truly makes. Now I’m not cutting out scouting as a whole and saying “watching a player play the game is bad”, what I’m actually vindicating is that analytics help you get the full grasp of a player.

For example when the Florida Panthers signed Carter Verhaeghe in the free agency period of 2020, everyone thought of it as some sort of random bottom six forward signing for a million bucks. Nothing more, nothing less. But thanks to Bill Zito’s fantastic analytically-based front office, they knew exactly what they were doing. The Panthers didn’t have money and they needed to bring in good players. Verhaeghe was cheap, and the front office did a deep dive on him to find out that he was going to be good. And guess what? He was. Verhaeghe had 36 points in 43 games. That’s absolutely fantastic compared to his previous season where he had only 13 points in 52 games. It wasn’t the simple eye test that got them Carter, because if it was, the guy would have teams knocking on his door offering him millions of bucks, Rolexes, and a new ferrari. That’s the beauty of analytics. They can predict ahead of time who’s going to explode, and who isn’t. Some other players that advanced stats knew would do well include Troy Terry, Roope Hintz, and Andrew Mangiapane. All of those players have broken out of their shells and have become crucial parts to their respective team’s success quite recently.

Graphs, Charts, & Tables:

Remember back in elementary school when your teacher would tell you to graph out how many apples Sally would get if she planted 2 apple trees every year for 5 years? Yeah, me too. It was hell.

Although you probably hated it, it actually kind of made sense. We as students learned that graphs help us visualize statistics and growth (or maybe shrink) much more simply. It made us realize we could see stuff, basically, easier. We wouldn’t need to do the math anymore if we have something to look at. The truth is, 65% of human beings are visual learners, which means we gather information by looking at something happening.

Graphs, charts and tables do that job in hockey. Let’s say you wanted to see how a player has been trending throughout his career via SPAR (standing points above replacement). Instead of going through the data and memorizing how much he’s improved or not, you can plot it out all on a chart and have a much more simple and quicker way of accessing the chart.

Above is Marcus Foligno’s career flow chart based off of SPAR. Look how clean and simple it looks. It makes you understand that he started off slow, but as his career went on he got better and better, to the point where in 2020-21, he was one of the best players in the league when it came to SPAR. This year is obviously a little slower, but he still ranks in the middle. Now look at the graph without caring about the stat. How nice is it to have a career trend of a player so accessible and look so uncomplicated.

I want you to think of how that chart would look like, if it wasn’t a chart and it was just numbers. That would probably give you a headache, wouldn't it? It would probably be a little overwhelming for someone who isn’t too good with advanced stats. That’s why graphs and charts are so important. They give you a much more transparent view on analytics. They make it fun and easy to understand.

Why analytics need to take over hockey-

This is the most essential and the most noteworthy part of the entire article, so keep going. You’re almost there. I’m proud of you for making it this far.

Hockey is no longer just about scoring goals and landing a big hit to get the team riled up. That’s old time hockey. That’s something my grandpa wants to see more often; another guy getting his head chopped off in a game and then scoring in the very next shift. That’s not what the sport is anymore. Hockey has adapted with the modern age of all sports, where the players are more athletic and the gimmick of hockey has completely been altered.

We can’t keep stupidly judge NHL and other high level hockey players based off of how fast they can skate or how many goals they can score. You can have a decent goal scorer on your second line scoring 25 or-so goals a season, but a blind eye test won’t tell you if the player is doing more harm than good to your team. That player could be the biggest defensive liability in the world, or maybe he just never gets the puck out of his zone. What if he let’s up the most fenwick shots (unblocked shot attempts) out of everyone on the team? You’re not getting that from the eye test.

The game is growing and we should be thankful that there have been people smart enough to create these analytics to help us get a better understanding on how this all works. The game will continue to get faster, stronger, and more competitive, and it won’t slow down for anyone. You see 16 and 17 year olds like Matvei Michkov and Connor Bedard tear up world junior’s and their respective leagues, and if those players at their current state would be put on the ice against players in the 1980s, they would dominate.

The game keeps growing and expanding, and we need to grow and expand with it. Who knows, maybe even the hockey world will start to see WAR and GAR as basic stats like goals and assists one day and we’ll have bigger and better stats take over as the “advanced analytics”. I sure hope so, at least.

Advanced metrics will assist us in creating a more competitive and a blatantly smarter sport. More players will start to work on their offensive and defensive games, and before you know it, these players will start to understand the leaps they need to take in order to be seen as good players. Heck, a lot of NHL front offices have started to use analytics a lot more, and that’s an amazing thing to see. We’ve already gone over how Bill Zito has adapted analytics, but credit needs to go to people like Eric Tulsky of the Carolina hurricanes, Chris MacFarland of the Colorado Avalanche, Sam Ventura of the Buffalo Sabres, and Alexandra Mandrycky of the Seattle Kraken. These all are some of the smartest minds in hockey, and these men and women have done an amazing job at bringing a new meaning to analytics when it comes to the sport of Ice Hockey.

As a fan, and as someone who aspires to become a part of an NHL front office one day, I love to see that analytics become more and more serious in the eyes of GMs, AGMs, presidents of hockey ops., and fans. I hope that analytics do continue to grow within not only hockey, but other sports. Even if you may not understand them or even if you hate them, it’s time to accept them into your sporting fandom because they’re here, and they’re taking over.