My NCAA hockey team was, by comparison to the division we were stuck in, not particularly good. We always earned a dozen-plus wins over each 35-40 games, but our division was just too laden with superstars for us to hang. This was during the peak of the WCHA, where they’d send a future minor-leaguer like me out against guys like Jonathan Toews and Phil Kessel and Joe Pavelski.
There was one season, though, when we didn’t get to that dozen win mark: my junior year. We won six times in 36 tries, and that win-loss record might be generous to how it felt. We stunk. I was fresh off a season when I had scored 12 goals and 23 points, and I simply could not do anything right to get back to those totals.
I wasn’t very good that year, and as one of the guys expected to produce, I take my share of the blame for that. But part of it was undeniably that we had lost some other good players, the team was overall worse, and so we spent copious time in our own zone. Whole games would go by where, as a winger, it felt like I never got the chance to have a good game, as I rarely touched the puck. I just stood in my own zone, marking my D-man (which was basically all wingers did 15 years ago), en route to a five-goal, 13-point season.
The next season, we had a great freshman class, we scored more and won more games, and I pushed that total back to 31 points in 37 games while playing a fairly comparable game.
Which brings me to my understanding (and sympathy) for what players on bad NHL teams are going through, and why we can’t just look at any one metric in the lead up to the trade deadline to judge potential trade pieces. All circumstances are not the same.
So, how can we tell which players on bad teams are seeing their individual results suffer based on their teams/situations, and which are a bigger part of the reason that their teams are struggling?
This is where the multitude of departments in an NHL front office would come together. The team running analytics could certainly find some points of data that would help. Video work would help too, and discovery surrounding that player’s attitude wouldn’t hurt either (which may come from scouts and those with boots on the ground). And, with all this information, teams are left to triangulate their best guesses of what’s left in a player.
The two names I have in mind while writing this are Patrick Kane and Vladislav Gavrikov, both rumoured to be trade pieces at the deadline, both coveted for very different reasons, both of whom may inspire numbers people to shout “Buyer beware!” from the rooftops.
By some basic stats, they don’t look great.
Gavrikov has three goals and seven assists this season, and finds himself with a minus-10. And while those numbers don’t matter to many people for the stay-at-home D-man, the next layer looks similar. He’s 17th on his own team in shot-attempt percentage, as when he’s on the ice, some 55 per cent of the shots happen against the Blue Jackets. It’s one thing to look bad compared to the league, another to your teammates. If you dial it in to expected goals percentage he’s … also 17th on his own team.
So, who wants that in a stay-at-home defender, right?
But this is where the analytics department has to find the stats that provide the context. Gavrikov has started more in his defensive zone than anyone else on the Blue Jackets, and when you don’t have players who excel at breaking the puck out, that’s going to mean a lot of attempts against your own net. It doesn’t help that he’s also played against top-six lines, as opposed to being handed softer competition.
He’s the sacrificial lamb they send out to defend when it’s almost certainly going to go poorly for the team. But when you zoom out, he’s a big body who can clear the net front, and he’s an elite penalty killer, and again: reinvigorated on a good team – where breakout passes may actually take the play the other way – who knows how valuable he could be. There’s also the option for a good team to get him and give him third-pair minutes against softer competition, where he could mop up.
None of those good things are guaranteed to happen for Gavrikov, and teasing out the player from their context remains a huge hurdle for teams in the weeks ahead.
The Kane one is more complex, because the reality is that he may be more prone to the type of statistical punishment that can come from being on a bad team. It’s tough to get points when nobody scores, and tough to do much about all that D-zone play as a winger. There’s also to reality that he’s won three Stanley Cups, and is less likely to pour his heart into games with no meaning, so the attitude question is more prominent.
Would a motivated Kane on a good team give you more than what we’ve seen in Chicago this season? Because, frankly, it’s looked pretty bad for the Blackhawks.
Through 45 games, Kane has just 36 points and only nine goals. His defensive metrics are among the worst in the NHL, but again, he plays a lot on a team that’s a defensive disaster and he’s a winger. It’s a hard position to control for what’s happening in front of your team’s net in the D-zone.
When you hand that to your analytics team, they may say, “Look, he starts in the offensive zone a lot, the play constantly goes the wrong way when he’s out there, and his name is bigger than his true performance at this point. We don’t want him.”
But there’s always the reality that he can break a game open with an elite play (it’s tough to not see him shaking Kimo Timonen to score the Cup winner for the Blackhawks), and for a team hunting goals, maybe they’ll believe in the rising tide of a good team raising Kane’s boat along with the others. Maybe they can use his remaining strengths to pull out of them something they need, even if the defensive stuff is still an issue.
Because of factors of motivation, it’s possible he’s a player they believe there’s more to than what you can find with the numbers, and here’s where scouts and conversations with the player matters more than anything else.
As we see names kicked around heading into the deadline, there’s a lot of misuse of stats that flies around social media. Excelling as a good player in a bad environment is more than swimming against a gentle current, you’re the salmon trying to climb the waterfall to get upstream. It’s not that their performance to date doesn’t matter, it’s that it comes with several asterisks.
Whether it be Kane, Gavrikov or any of the other players rumoured to be on the move in the days ahead, find all the context you can with these players. The initial reaction will always be “They gave up too much!” when someone pulls out a player’s stats from this season, but it’s very possible that a change of jersey is all they need to re-establish themselves as a more effective contributor.