Some visualization on Zach Bogosian, Evander Kane, Tyler Myers, Drew Stafford, Joel Armia, and Brenden Lemieux

Yesterday we at Jets Nation posted some interesting articles breaking down some of the assets the Winnipeg Jets received in return for trading Evander Kane and Zach Bogosian. If you have not read them yet they are highly recommended:

While researching for these articles, I accrued some data visualizations and thought I’d share them with you.

Let’s take a look.

Here we can see how each of the Jets forwards have performed in Corsi% relative to 50% and their ice time per game. 

Here is Evander Kane’s results for each game he played this season as a Jet.

These are With Or Without You (WOWY), showing how players performed with and without Kane. On average most performed better (1.6%), but not all did. Blue is together; grey is apart.

Here we can see how each of the Jets forwards have performed in Corsi% relative to 50% and their ice time per game. You can see one of the largest inefficiencies is too much icetime (or too tough of usage) given to Zach Bogosian.

Here is Zach Bogosian’s results for each game he played this season as a Jet.

These are With Or Without You (WOWY), showing how players performed with and without Bogosian. On average most performed worse (-2.7%), but not all did. Blue is together; grey is apart.

Buffalo Sabre’s forwards: Corsi% relative to 50% and ice time per game.

Drew Stafford’s results for each game this season on the Sabres.

Buffalo Sabre’s defenders: Corsi% relative to 50% and ice time per game.

Tyler Myers’ results for each game this season on the Sabres.

These are With Or Without You (WOWY), showing how players performed with and without Myers. On average most performed worse (-4.9%), but not all did. Blue is together; grey is apart.

Joel Armia’s and Brendan Lemieux’s NHL equivalent points per game production for each season relative to other Jets draft picks.

These are the same NHLEs as the previous graphs, but this time the data is cumulative with each progressing season.

Thes graphs show the value (in terms of GVT) of every top 30 draft pick since 1990 draft. As you can see, the value becomes a lot more even once you pass the top 5 or so pics.

This is the same visualization, but with all forwards removed. This shows how terrible goaltending and defensemen evaluations have been historically.

To show that it’s not goaltenders skewing the data, here is just defenders for the same sample.