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The summer boredom is soon coming to an end and with that, the opportunity to drop in non-newsy posts about hockey is coming to an end as well. That probably serves you the readers well, but we’re not quite there yet. Instead I give you an idea stolen from 538…

Interesting, right?

Well, it’s a bit easier to do that with baseball than it is to do with hockey, but screw it, I’m going to try anyways using 6 equally weighted measures for forwards, 6 equally weighted measures for defensemen, and ditto for the goaltenders. The end result, you guessed it, a completely average team.

The Forward Criteria

This isn’t an attempt a truly profound analytical model. This is just some fun to have in late August, so that being said the categories are time on ice, points, expected goals for %, corsi for %, penalty minutes, and hits. I can sense a lot of you cringing and others shrugging in acceptance.

Here’s where the title of the post becomes quite misleading. I’m not looking at averages, I’m looking at percentiles for each of these categories and then averaging them out. Annoyed yet? Sure you are. In reality only a select few of you are actually reading the methodology part, so I can put whatever I want in here. Banana fart sundae. See? No one is even going to acknowledge that.

Here are your forwards…

Player Pos Avg Dif
Mario Kempe R 0.500 0
Trevor Lewis C 0.500 0
Mikko Koivu C 0.500 0
Kyle Turris C 0.502 0.002
Luke Glendening C 0.502 0.002
Brandon Dubinsky C 0.498 -0.002
Dale Weise R 0.498 -0.002
Alex Galchenyuk C 0.497 -0.003
Lukas Radil C 0.497 -0.003
J.T. Brown R 0.495 -0.005
Michael Raffl L 0.495 -0.005
Dominik Kahun C 0.495 -0.005
Jason Pominville R 0.507 0.007

This is the most Minnesota Wild team that ever Minnesota Wilded. Not just because of the number of current or former Wild players on it, but the fact that is absolutely a perpetual bubble team group. It’s entirely possible that Turris and Galchenyuk are better than average, but using just 2018-19 numbers, this is how it shakes out.

The Defense Criteria

Well, it would be boring if I did it exactly the same as the forwards, so we’ll switch it up and go with ice time, points, hits, penalties, blocked shots, and corsi against. I’m writing this before seeing the results, so I can tell you, I’m excited to see what this produces.

Player Avg Dif
Igor Ozhiganov 0.501 0.001
Radim Simek 0.499 -0.001
Josh Brown 0.502 0.002
Jordan Oesterle 0.503 0.003
Sami Vatanen 0.510 0.010
Ben Harpur 0.490 -0.010
Cam Fowler 0.489 -0.011
Jonathan Ericsson 0.483 -0.017

There’s the Leafs content you expect to see on Leafs blog. While Ozhiganov may have moved on, using my hastily thrown together criteria he was the most average defenseman in the NHL last season. I’m not sure what witchcraft I cast to lump Vatanen and Fowler into this mix, but there will be no second guessing of this, and we will all accept that Ben Harpur is marginally better than Cam Fowler. After all, hits, PIMs, and blocked shots, dude.

The Goaltender Criteria

While I think it is important to acknowledge their voodoo, and the fact that pretty much every goaltender has the same stats, I’ll proceed with the charade that is already producing what is a completely nonsensical lineup, that does in fact seem capable of being the 16th best team in the league.

For goaltenders we’re looking again at ice time, then we’ve got a whole lot of variations of save percentage. You’re getting shots against, save percentage, expected save percentage, high danger save percentage, and goals saved above average. Folk’s… this might actually tell us who the statistically most average goaltenders are.

There winners are…

Goaltender Avg Dif
Curtis McElhinney 0.498 -0.002
Anthony Stolarz 0.508 0.008

C’mon… deep down you knew it was going to be McElhinney, right? I guess the rub here is that we’re looking at all goaltenders that played in the league last season without a minimum ice time attached to them, and it was bound to be a couple of backups. I’m going to adjust it for goaltenders with over 500 minutes so we have something more applicable.

Goaltender Avg Dif
Philipp Grubauer 0.497 -0.003
Mackenzie Blackwood 0.492 -0.008
Mikko Koskinen 0.510 0.010

Honestly, I think I’m just as comfortable with the McElhinney and Stolarz results as with this group. Anyways, let’s look at the a potential roster

LW C RW
Galchenyuk Turris Pominville
Raffl Koivu Kempe
Dubinsky Lewis Brown
Kahun Glendening Weise
Radil
LD RD G
Fowler Vatanen Grubauer
Oesterle Ericsson Koskinen
Harpur Ozhiganov Wedgewood
Brown Simek

Yeah, there have been worse teams put together, but you should in no way be excited about any of this. It’s probably interesting that there’s no shortage of right shot defensemen on this team. It’s also likely this team can kill penalties. This team can make the playoffs, but you probably hope they don’t because who the hell would want to watch this group play?

Isn’t this a Leafs blog?

Fair enough. Here’s the breakdown of how the Leafs fared using my criteria which was used to find the most average player, not identify the best players. (remember hits, blocked shots, and PIMs)

Forwards

Player Team Position Overall
John Tavares TOR C 0.810
Zach Hyman TOR L 0.803
Kasperi Kapanen TOR R 0.737
Mitchell Marner TOR R 0.705
Kenny Agostino N.J L 0.650
Alexander Kerfoot COL C 0.635
Auston Matthews TOR C 0.633
William Nylander TOR R 0.595
Pontus Aberg MIN L 0.490
Jason Spezza DAL C 0.448
Frederik Gauthier TOR C 0.435
Trevor Moore TOR L 0.338
Nic Petan TOR C 0.293

It’s time to catch Kenny Agostino fever. WOOOOOOOOOOOOOO!!!!

I’m going to state right now that I think Auston Matthews is better than him.

Defense

Player Team Overall
Jake Muzzin TOR 0.804
Tyson Barrie COL 0.714
Cody Ceci OTT 0.649
Travis Dermott TOR 0.642
Morgan Rielly TOR 0.629
Jake Gardiner TOR 0.585
Ben Harpur OTT 0.490
Kevin Gravel EDM 0.360
Martin Marincin TOR 0.342
Justin Holl TOR 0.259

I found a way to create decent looking numbers for Cody Ceci, I’ll take my Nobel Prize in Math now please.

Also at this point it still feels like it’s worth include Jake Gardiner on this list while the Leafs move mountains to bring him back.

Goaltenders

Freddie Andersen had the 5th highest score in the league at .781, and neither Hutchinson or Neuvirth played enough to make the cut.

So…

None of this really means anything. This wasn’t really about finding the true middle of the pack based on true predictors of talent or what helps a team win. This was six categories on three different position groups and averaging them out into seeing what average players look like. While there’s some value in considering all these categories in establishing a single number to judge all players by, I’m going out on a limb here to say that there should probably be heavier weighting attached to points over penalty minutes.