Select Page

GSAA: An Essential Statistic For Evaluating Goaltenders

Toronto Jonathan Bernier Leafs

Using GSAA, we discover that Jonathan Bernier has saved the Toronto Maple Leafs 18.22 goals against in 44 games this season, compared to if there was a league average goaltender in his place. That’s second in the league to only Ben Bishop.

Advanced statistical knowledge in sports has increased rapidly in the last two decades. Hockey has been a step behind most other sports, but is starting to catch up with the rise of possession statistics such as the wildly popular “Corsi” percentage. The sheer volume of information that is collected now can be enough to make your head spin, but a lot of it is extremely valuable when it comes to evaluating individual performance.

When it comes to evaluating a goaltender, three statistics in particular have been looked at throughout most of history. Those three stats are wins, goals against average and save percentage. While all three categories still have some merit, they have become somewhat outdated. Wins and goals against average are better looked at as a team statistic and is actually a very poor way to evaluate an individual goaltender’s performance. Even save percentage isn’t perfect. It can be skewed depending on the quality of team that the goaltender plays for.

In baseball, batting average, home runs and runs batted in were the “big three” categories for years. They have been effectively replaced by percentage stats, and statistics that compare a player to a “replacement player.” Essentially, if that player was replaced by a minor leaguer, would that minor league player perform better, or worse? It’s called “WAR” which stands for Wins Above Replacement.

There is a relatively new statistic for hockey that has been made available by the folks at Hockey-Reference. It’s similar to baseball’s WAR, and it is called “GSAA” – Goals Saved Above Average. You take the league’s average save percentage and apply it to the amount of shots a particular goalie has faced. You get a number of goals that the average goalie in that league would have surrendered if they faced the same number of shots as the goaltender in question. That number gets compared to the number of goals surrendered by that goaltender, and a plus/minus is created. If a goalie is in the positive, that is how many goals they have saved compared to a league-average goalie. If they are in the negative, then it is safe to assume that they are performing worse than how a league-average goaltender would perform in the same situation.

Here are the top ten goaltenders in GSAA in the 2013-14 NHL season, as provided by Hockey-Reference:

GSAA Leaders

For the full list of GSAA leaders, click here.

Every stat has pros and cons, which is why you must look at the entire picture. GSAA does a lot of things better than other stats, but is still not perfect. Here is a breakdown of what it does well, ways that it is biased, and how it can be improved:

What GSAA Does Well

  • It is a very good stat at equalizing goalies across the league, regardless of the team that they play for. For example, a goalie that has a .925 save percentage and has faced a lot more shots than average is actually playing better than a goalie that has a .930 save percentage and has faced less shots. The first goalie has faced more scoring opportunities, and has saved more goals from going in based on their quality of play.
  • It tells you how much a team relies on their goaltending to win games. If a team gives up a lot of shots, but their goalie is continually bailing them out, their goalie will have a very high GSAA number. Those teams are more likely to struggle if their goalie goes into a slump or gets injured. Teams that succeed despite having a goaltender that is in the middle of the pack (or worse) in GSAA are actually more stable, because if their goalie slumps or gets injured, they still have a very good chance to win using a replacement netminder.
  • It gives you a physical number of goals saved, rather than a percentage. It’s a stat that can be very shocking. For example, Ben Bishop has saved almost 24 goals from being scored on the Tampa Bay Lightning in 44 games. A number that large will draw a lot of attention. It is a great stat to prove Bishop’s worth to the Lightning. 24 goals saved is a VERY significant number.

What GSAA Does Not Do Well

  • Goalies that play more games will accumulate more goals saved. If the stat was expressed as GSAA/per 60 minutes, it would be even more accurate. You would have to turn it into a percentage, though. Only goalies that have played a certain number of games would be able to qualify.
  • It does not take penalty killing into account. On average this season in the NHL, goalies have seen a 4.4% drop in save percentage while on the penalty kill compared to even strength. This is a major problem for some goalies that play for a team that is constantly killing penalties. Undisciplined teams will have goalies with a lower save percentage and a lower GSAA as a result.
  • It does not take fatigue into account. Saves that are made after the 30 shot mark should be worth more, because goalies that face more shots than the league average will be more tired, and will make less saves due to the poor quality of the team in front of them giving up more scoring attempts.
  • It also does not take shot quality into account. This can be related to the number of penalties a certain team commits, or even a team’s quality of defence, but that would be very difficult for any statistic to quantify.

GSAA is definitely not a perfect statistic, but it is one of the best ones available at the moment when it comes to analyzing goaltenders. It has flaws, but it is more accurate than save percentage and should become more widely used.

About The Author

Greg Balloch

Greg Balloch is a Vancouver-based writer for InGoal Magazine, broadcaster for Sportsnet 650, and goaltending coach. His career began in Hamilton, Ontario with the Junior 'A' Hamilton Red Wings, before moving to Vancouver to cover the Canucks on the radio and work with the Surrey Eagles of the BCHL. A lifelong goaltender, he has been teaching the position for over a decade.


  1. Matthew Schnoes

    This is an interesting stat, is there a simple way to compute it using your own statistics? It seems like a fairly daunting task to find it out for yourself but I would like to see what it would show.

  2. Greg Balloch

    Yes, Matthew. You have to know three things: Your Shots Against, Your Saves, and the average save percentage of the league you play in. If the average save percentage is .915, you find out how many saves would be made if you stopped 91.5% of the shots you faced. Then you calculate your saves – the league average save number. There you have it!

    If you don’t know the league average save percentage, you can also just pick a number that you would see as being “average” in your league.

  3. Anthony Santarosa

    I always thought a good measure of activity would be Shots Per Minute (SPM). This would only be an additional indicator of how active a goalie is. Using your stats above you would see that the busiest goaltenders, those that faced more shots per minute of play would be Miller, Bernier and Price.

    Then you can see that a similar save % was much harder to achieve for one goaltender as compared to another.

  4. Stephen Walker

    Thanks. Very interesting and it advances a much needed effort to really track and compare goal tender performance. The mathmatics is daunting however, so – is there an app for that? It would be good to incorporate another column in the Pointstreak stats. Thanks and we’ll stay tuned.
    Stephen Walker, PhD, CC-AASP

  5. Dave

    This new stat is worse than save %. The argument for it don’t make since.

    “a goalie that has a .925 save percentage and has faced a lot more shots than average is actually playing better than a goalie that has a .930 save percentage and has faced less shots.”

    -Not true. If Goalie A faces 10 shots and 1 slips in he will have a worse save % than a goalie who faces 15 shots and 1 slips in. Meaning the margin of error for a goalie facing less shots is higher.

    “It tells you how much a team relies on their goaltending to win games. If a team gives up a lot of shots, but their goalie is continually bailing them out, their goalie will have a very high GSAA number.”

    -That one I can agree with, but it still won’t tell you how well the goalie saw the shots or where they came from. A shot from the point with no traffic compared to a one timer across the crease with traffic. If a defensive system is playing well, the shots a goalie recieves are goingt to be easier to track, i.e. outside/bad angle with not oposing player screening.

    “It gives you a physical number of goals saved, rather than a percentage.”

    -So I’m not great at math, but that’s the same thing. A 92% save percentage is 92 saves out of 100 = 8 goals per 100 shots. Doesn’t do anything.

    Conclusion, another pointless stat that someone came up with. I agree with the article in the fact that, I have never been able to figure out why people ever use goals against as a goalie stat. An average of 45 shots a game is probably going to yeild a higher GAA than 25 shots a game. But, the guy getting 45 shots might just have the better save percentage.

    • Dave

      Greg, you did make a very good point in the article that linked this one. Two goalies playing the same system should be able to use this stat. This could be used to find out who the better back up would be or even if your back-up may be better off starting.

  6. Dusty

    I realize this article is pushing 6 years old now, but that idiot Greg from ESPN linked it in a contemporary article so here I am. There is a very good reason why hockey, along with football, soccer and basketball, lags behind in these advanced stats: they are only designed to measure individual performance. Using advanced stats to track individual performance in a team sport makes no sense. Take Corsi as an example. Corsi measures how many shots on goal were taken, for and against, while a particular player was on the ice. The purpose of Corsi is to track team dominance via individual player stats, with the idea being that if a player has a positive Corsi, his team is more dominant when he’s on the ice. Supporting this assertion is that if a team possesses the puck more they will have more shot attempts, and therefore could be considered the dominant team. In it’s essence, then, Corsi is measuring puck possession. There is already a stat that tracks possession time, and it’s called time of possession. The same is 100% true with all these advanced goalie stats. Take goals saved above average as an example. Last year the leaders in SV% and GAA also had the highest above average ratings. The only value above average has is weeding out goalies who didn’t start a lot but did well when they did start. But, guess what? Games played does the exact same thing. Why? Because above average depends on shots on goal, as does SV%, so the two stats will correlate almost exactly once you factor out small-start sample sizes (call-ups, backups). They are the same stat. The reason WAR is valuable is because it aggregates hundreds of stats into a single, easy-to-digest number. The reason it works is because it was developed by statisticians who understand how data works, what its limits are and what its purpose is. The reason hockey stats don’t work is because they were created by former players or coaches, and they are referenced by people who have no clue how data works.