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Understanding NHL Advanced Stats: A Beginners Guide Part 3

NHL Analytics

“Advanced stats” has become a kind of buzz word around the hockey world. It’s emerging into the NHL as it did years ago with the MLB. Hockey teams have entire departments for analytics, and it has become a war (pun intended) of sorts between two sides: The Data Nerds vs. Old School Hockey. What I intend to do is break down some of the common stats used in analytics to help people get introduced into the world of NHL analytics.

Be sure to check the rest of the series:

Part One

Part Two

Part Three

Part Four

Understanding NHL Advanced Stats: Part 3

Let’s talk about goalies.

Goalie stats seem weird at first, but after understanding expected goals it becomes easier to understand some of the key goalie stats.

Goals Saved Above Average

Goals saved above average (GSAA) isn’t really an advanced stat. While it may not be advanced, it is still good to know when discussing goalies. To calculate GSAA, you compare how many goals a goaltender allowed against how many a league-average goalie would allow in the same amount of shots. Formally, it is the league’s average save percentage with the number of shots a goalie has faced. This number is how many goals a league-average goalie would allow. This number is then subtracted from the goalie that you are evaluating against. This will result in either a positive or negative number.

It is league save percentage multiplied by shots against minus goals against.

Goals saved above average is good to see how a goalie did against an average goalie in the league. What it doesn’t do, however, is adjust for shot quality or the team in front of them. This is where goals saved above expected emerges as superior. Goals saved above expected adjusts for shot quality and levels the playing field for goalies behind good teams and bad teams, whereas GSAA does not. It is similar to save percentage that it doesn’t adjust for quality in front of the goalie. A stat of 0 is the baseline for an average stat.

Goals Saved Above Expected

This is the key stat to use when evaluating goalies. We learned about expected goals in the last article, and this expands upon that. This stat evaluates how many goals a goalie saved above what he was expected to based on the shot quality he faced. The formula is simply expected goals against minus goals against. Unlike goals saved above average, goals saved above expected (GSAx) accounts for the quality of shots a goaltender faces and levels the playing field for goalies on good defensive teams and bad defensive teams. This is why it appears to be one of the best metrics for goaltenders.

Examples of elite metrics from goalies of the past are Connor Hellebuyck with a league-leading 19.86 in 2019-20, John Gibson with a league-leading 32.86 in 2017-18, and Carey Price with an astounding 38.88 in 2014-15. Typically when evaluating this 0 is the baseline for average.

High Danger Save Percentage

This is like a poor man’s GSAx that isolates high, medium and low danger scoring chances and exclusively measures a goaltenders save percentage with these types of shots. This evaluates shots taken from areas of the ice where goals are more likely to be scored and how well a goalie is at saving these types of shots. It is similar to GSAx in the way it accounts for shot quality, but it does not assign a value to that quality. More of a qualitative version of expected goals to put it simply.

Stats Not to Use

We’ll quickly go over which stats not to use when talking about goaltenders. The first, and maybe most controversial, is wins/losses. Knowing that Andrei Vasilevskiy went 35-13-3 in 2019-20 doesn’t tell us anything for a goaltender. Win/loss ratio is a team stat and should not have been adopted as a goaltender stat.

Goals against average is another stat not to use when evaluating goalies. Again, this seems to be more reflective of the players AND the goaltender than just as a means of evaluation of the goaltender. It just sees how many goals were scored on a per 60 basis. This doesn’t tell us anything of value when exclusively evaluating a goalie.

Next time in Understanding NHL Analytics: A Beginners Guide we will look at wins above replacement. If you have any questions, feel free to reach out on Twitter.

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