The Tool Desk
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Start with comparable situations
Before comparing numbers, make sure they describe the same kind of hockey. A full regular season and a short playoff run are not equivalent samples, and totals can be misleading when one goalie played far more than the other. Keep the comparison window and game-state scope consistent, and show the workload behind each rate.
- Match the season and competition: compare regular season with regular season or playoffs with playoffs, and label any mixed comparison.
- Show workload: include games, starts, minutes played or shots faced. A rate from a small sample can look more meaningful than it is; available sources do not establish a universal minimum sample size.
- Separate starts from relief appearances: games played alone may not show how each goalie was used.
Read SV% and GAA as outcome summaries
Save percentage (SV%) is saves divided by shots on goal faced. It is a useful summary of how often a goalie stopped shots that counted as shots on goal, but it treats those shots alike: a shot from distance and a screened or deflected attempt do not receive different weights. Standard SV% also excludes pucks that miss the net or hit the post.
Goals-against average (GAA) is goals allowed per 60 minutes played. It shows the rate of goals allowed over playing time, but like SV%, it does not adjust for shot difficulty or the quality of the defense in front of the goalie. Read the two together as conventional results, not as isolated measures of goalie skill.
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Expected goals (xG) models assign a scoring probability to each shot and add those probabilities together. For a goalie, expected goals against (xGA) estimates the quality-weighted challenge faced. Public models may use factors such as shot location, game state and events leading up to a shot, but their inputs differ; xGA is a model estimate, not a directly observed count.
That distinction matters when two goalies face the same number of shots. Their workloads may still differ if one sees more dangerous attempts. NHL goalie Philipp Grubauer described the challenge of classifying tipped shots: a shot from the blue line can become a different scoring chance when a player tips it in front of the net. A category or model may not capture every detail of what the goalie saw.
Rank #2
Compare GSAx—and name the provider
Goals saved above expected (GSAx) compares expected goals against with actual goals allowed. In the Seattle Kraken’s explanation, it is calculated as expected goals against minus actual goals allowed: a positive value means the goalie conceded fewer goals than that model expected. Because models and definitions can differ, state the provider and comparison scope; do not assume two providers’ GSAx figures are interchangeable.
Related measures answer slightly different questions:
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Rank #3
- dFSv% (save percentage above expected): Seattle Kraken describes this Evolving-Hockey measure as actual SV% relative to what shot quality predicted. Use the provider’s definition when reporting it.
- GSAA (goals saved above average): estimates goals saved relative to an average goalie using league-average SV% and shots faced. Its baseline is an average goalie, not the shot-quality expectation used for GSAx.
Do not put these measures in the same column as though they share a baseline. GSAx asks how results compare with modeled shot quality; GSAA compares results with an average-SV% reference.
Add danger and location splits as supporting context
High-danger save percentage and distance-based splits can show where outcomes differ. NHL EDGE offers goalie statistics by high-danger category and distance. Those splits are useful for asking a narrower question—such as how a goalie has fared on attempts classified as high danger—but the reviewed sources do not establish a universal definition that makes categories interchangeable across providers.
Use a split alongside overall stats and its denominator, not as a stand-alone verdict. A goalie’s result in one location or danger category does not, by itself, explain the shot mix, screens, tips or other circumstances behind those attempts.
Account for the team and the goalie’s usage
A goalie’s win total depends in part on how many goals the goalie’s team scores, so wins are not an isolated measure of goalie performance. NHL.com illustrated this in 2019 with two Nashville goalies who had similar save percentages but different win totals alongside different team scoring support; that historical example explains the confound, not how current goalies compare.
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Rest is another useful context when available. NHL.com’s statistics redesign discussion described views that let readers consider rest and team scoring support alongside goalie statistics. Such context can help explain a result, but it does not replace the goalie’s workload or shot-quality measures.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A practical comparison checklist
- Set the scope: choose the same season, competition and game-state scope for both goalies.
- Record the denominator: show games, starts, minutes or shots faced so the amount of evidence is visible.
- Compare conventional outcomes: read SV% and GAA together, remembering they do not adjust for shot quality or team defense.
- Add the modeled workload: compare xGA, then GSAx, with the model provider, definition and scope clearly identified.
- Check supporting splits: review high-danger or distance-based results where available, with the provider’s category definitions and sample size.
- Note team context: consider scoring support and rest rather than treating wins as a direct goalie ranking.
- Keep the conclusion proportionate: stats can organize evidence, but watching technique remains part of evaluation and is less quantifiable.
For current official category views, use NHL EDGE goalie statistics. For explanations of goalie measures and their limitations, see the Seattle Kraken’s goalie-statistics explainer. NHL.com’s 2019 statistics redesign article offers historical context on workload, rest and scoring-support views; its figures should not be read as current benchmarks. For one provider’s glossary and terminology, consult HighDanger’s glossary.
Quick Recap
What to avoid concluding
- Do not call a goalie definitively better from SV%, GAA or wins alone.
- Do not compare model-based figures from different providers as if they use identical inputs or conventions.
- Do not treat a high-danger split as a complete goalie ranking.
- Do not present historical NHL.com figures as current league averages or thresholds. The cited 2019 article reported league-average SV% of .915 in 2015–16 and .910 through 483 games of the 2019–20 season, and reported Tristan Jarry at .900 SV% or better in 10 of 12 starts (83.3%); those are dated examples, not present-day benchmarks.
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