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Toronto Maple Leafs vs Blue Jackets 5v5 Analysis

By Philip Van Riesen

TORONTO, ON - OCTOBER 21: Nick Foligno #71 of the Columbus Blue Jackets steals the puck from Cody Ceci #83 of the Toronto Maple Leafs during an NHL game at Scotiabank Arena on October 21, 2019 in Toronto, Ontario, Canada. The Blue Jackets defeated the Maple Leafs 4-3 in overtime. (Photo by Claus Andersen/Getty Images)
TORONTO, ON - OCTOBER 21: Nick Foligno #71 of the Columbus Blue Jackets steals the puck from Cody Ceci #83 of the Toronto Maple Leafs during an NHL game at Scotiabank Arena on October 21, 2019 in Toronto, Ontario, Canada. The Blue Jackets defeated the Maple Leafs 4-3 in overtime. (Photo by Claus Andersen/Getty Images) /
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TORONTO, ON – OCTOBER 21: Nick Foligno #71 of the Columbus Blue Jackets steals the puck from Cody Ceci #83 of the Toronto Maple Leafs . (Photo by Claus Andersen/Getty Images).
TORONTO, ON – OCTOBER 21: Nick Foligno #71 of the Columbus Blue Jackets steals the puck from Cody Ceci #83 of the Toronto Maple Leafs . (Photo by Claus Andersen/Getty Images). /

The Toronto Maple Leafs and Columbus Blue Jackets will finally get under way today.

The 5v5 game state is the most important out of any and the Toronto Maple Leafs and Columbus Blue Jackets will likely spend plenty of time playing at 5v5 given both teams don’t take too many penalties.

As many are likely well aware, the Leafs and Blue Jackets are polar opposites of each other. The Leafs are great at offense but poor a defense. The Blue Jackets are bad at offense but great at defense.

Let’s dig into the big picture 5v5 numbers for both teams.

What we will look at is the percentage of expected goals(xGF%), shot attempts (CF%), and the goals for (GF%).

Any team above 50% is effective overall if you have more scoring chances, shots, and goals you’re doing a good job.

Thus let’s get to the numbers:

Columbus Blue Jackets:
51.66xGF%

48.87CF%

50.55GF%

Toronto Maple Leafs:
51.62xGF%

52.28CF%

50.29GF%

All data from Evolving Hockey 

As you may have noticed both teams are basically neck in neck in when it comes to these numbers overall. This is especially the case when it comes to xGF%.

I tend to put more weight into the xGF% since it gives us data based on shot location, and there is enough happening over 70 games that the correlation is likely strong. And if I were to use only GF%, this would be flawed since it is not very replicable and highly influenced by S% and Sv%.

Teams generally don’t end up this tight in numbers but here we are. And the more interesting part is that both teams have put up these results in completely separate ways.

Let’s break down each team’s strengths and weaknesses at 5v5 and what they did to get to these numbers.

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