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New York Rangers G Henrik Lundqvist – GAVE Analytics Study

By Brian Draus

Apr 23, 2016; Pittsburgh, PA, USA; New York Rangers goalie Henrik Lundqvist (30) sweeps the puck from in front of the net against the Pittsburgh Penguins during the first period in game five of the first round of the 2016 Stanley Cup Playoffs at the CONSOL Energy Center. Mandatory Credit: Charles LeClaire-USA TODAY Sports
Apr 23, 2016; Pittsburgh, PA, USA; New York Rangers goalie Henrik Lundqvist (30) sweeps the puck from in front of the net against the Pittsburgh Penguins during the first period in game five of the first round of the 2016 Stanley Cup Playoffs at the CONSOL Energy Center. Mandatory Credit: Charles LeClaire-USA TODAY Sports /
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New York Rangers G Henrik Lundqvist: “Project Helium” Analytics – Goals Above Value Equalizer (GAVE) First Study

Project Helium is a personal set of original hockey analytic formulas.  Today’s opening study will focus on New York Rangers G Henrik Lundqvist.

Now that I have introduced GAVE, it makes sense to do a study involving the formula. While I may have avoided the Big Apple for Regulated Goalie Value (RGV), I am not going to do so with GAVE. Let’s see how King Henrik stacks up.

One difference between GAVE and any of the other formulas that you have seen studies for is that there will be a combination for this one. It might seem a bit odd, but I am going to use both artificial and actual statistics when calculating the studies.

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The reason I am doing this is due to the fact that I cannot watch every second of an old game, however I can find highlights of the goals scored. So in other words, the goals will be scored realistically however the saves won’t.

There is one catch with the number of saves being correct, but the location on the ice being artificial.

Now, it is time to pick the game that I will use for the study.

Since the first Lundqvist game will be a victory for the Blue Shirts, he will only allowed two goals.

The study will be from March 23rd, 2016, a game in which the Rangers defeated the Boston Bruins 5-2.

Everything in bold is an actual statistic, everything in italic is artificial statistic.

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Click the link to see what each variable means

(1st Pd)

No goals allowed

Since all the shots were stopped, I am now going to move to the saves category

Saves (9)

4 difficult, 3 average, 2 easy

(2nd Pd)

goal allowed at 9:34: (H+H3)

Saves (13)

6 difficult, 2 average, 5 easy

(3rd Pd)

goal allowed at 12:06: (J+J3+J10)

Saves (17)

4 difficult, 2 average, 1 easy (after 30 shots were taken)

5 difficult, 5 easy

(we need to link back to the variables, as it would be far too extensive/tedious to continually re-write)

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After totaling up all of the necessary values, Lundqvist’s GAVE for this game was +6.2807.

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I believe that is going to end up being a very good score for one game, especially considering when you combine the fact that you take into account the amount of shots he faced and goals allowed.

Now, assuming that he allowed a couple more goals or was pulled early, it is possible that his GAVE value would have been very low.

What a low score will end up being is TBD, but considering the fact that the next study will be a poor performance from New York Rangers G Henrik Lundqvist, we should find out quite soon.

All in all, I think things went fairly well considering the fact that I had yet to test GAVE.

While I don’t know how much the variables will need to be adjusted over time, I think that I am going to get a better idea of an actual score with the artificial statistics for GAVE than I did for Regulated Plus/Minus (RPM).

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Using saves instead of time played is a bit risky, but has a similar effect due to the fact that if a goalie plays less/is pulled, he will not be making saves. On the flip side, anytime a goalie allows a goal he is charged with a goal.

While this formula may be altered a bit, expect it to stay the same for the most part. And expect more studies to come soon, so stick around.

Source: http://rangers.nhl.com/

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