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Compare NHL goalies using the same provider’s goals saved above expected (GSAx), with the same season, competition, game-state scope and workload criteria. In the common convention, GSAx is expected goals against minus actual goals allowed: a positive figure means fewer goals were allowed than the model expected; a negative figure means more. It is a model-based measure of results in a defined sample—not a definitive, model-independent ranking of goalie skill.
What GSAx measures
GSAx adjusts for the quality of the shots a goalie faced. Rather than treating every shot as equally difficult, an expected-goals model assigns probabilities to attempts; those probabilities are added to estimate expected goals against. The comparison with goals actually allowed indicates whether the goalie conceded more or fewer goals than that expectation.
A useful conceptual formula is:
GSAx = expected goals against on shots faced − actual goals allowed
Under Hockey Acumen’s documented convention, positive GSAx means the goalie allowed fewer goals than expected, while negative GSAx means the goalie allowed more. Providers can differ in their models, event populations and metric labels, so check the provider’s definition before interpreting or quoting a number. The NHL’s August 27, 2025 goaltending analytics explainer introduces expected goals in this context, but its available description does not specify a complete formula.
How to make a fair comparison
- Choose one provider. Use the same provider and model for every goalie, and record the model version if it is disclosed and the date you retrieved the figures. Public values may differ because providers make different modeling and data choices.
- Match the time frame and competition. Compare the same season and competition, and keep regular-season figures separate from playoff figures. A full season and a short playoff run are not equivalent samples.
- Match game-state and event scope. State whether the figure covers all situations or a filter such as 5-on-5. Check which events are included; numbers drawn from different scopes answer different questions.
- Show workload and eligibility. Include starts, minutes or shots faced, along with any provider threshold. Cumulative GSAx reflects both performance and how much work a goalie did. PuckRank’s 2025-26 report, for example, defines its cohort using at least 20 regular-season starts, positive time-on-ice and shot totals, and a non-null provider GSAx value. That is the report’s filter, not an NHL-wide standard.
- Identify the metric form and sign. Say whether the value is cumulative GSAx or a rate such as GSAx per 60, and state the provider’s sign convention. A rate can help contextualize unequal playing time, but it does not make models or small samples interchangeable.
- Add conventional context. Present save percentage, goals-against average and a workload indicator alongside GSAx. Save percentage is a rate based on shots faced; goals saved above average (GSAA) compares results with league-average save percentage. Neither is the same as a shot-quality model’s GSAx.
Why providers can report different GSAx values
GSAx inherits the assumptions of its expected-goals model. Models can use different data and features, so values from separate providers should not be treated as interchangeable measurements on a single universal scale.
Hockey Acumen says its model uses shot location, angle, type and preceding play, and does not use goalie identity as a predictive feature. Its methodology page reports coverage from 2009-10 through 2025-26, with a stated caveat for 2009-10. Those are details of that provider’s implementation, not properties that can be assumed for every GSAx table.
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Recorded event data and model inputs also cannot fully describe every part of goaltending. Positioning, sightlines, screens, rebounds, defensive pressure and technique can be difficult to represent completely in public metrics. Seattle’s introductory hockey analytics explainer and goaltending statistics overview discuss the limits of goalie statistics. Treat GSAx as one view of observed results, not a complete account of how or why those results occurred.
How to interpret the number without overclaiming
A higher GSAx supports a narrow conclusion: that goalie had the stronger result relative to expected goals in the specified provider’s model and sample. It does not, on its own, establish who is definitively the better goalie or predict future performance. Team context, sample size and model limits all matter.
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For an example of what the arithmetic means, Seattle’s 2022 explainer describes Philipp Grubauer facing shots worth 5.2 expected goals and allowing two. In that illustration, he prevented more than three goals relative to expectation. It is an example from a team article, not a current-season ranking or league-wide result.
For a current-season comparison, use one provider’s live table and report its values with the retrieval date and filters. PuckRank publishes a provider-specific 2025-26 goalie-burden report; that does not establish an official NHL GSAx leaderboard. The NHL explainer is educational rather than a GSAx statistical table. Phrase a result as “had the higher GSAx in this model and sample,” rather than as a universal ranking.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What to include when publishing a comparison
- Provider and model version, if disclosed, plus retrieval date.
- Season or date range, and regular season or playoffs.
- Game-state filter and event scope.
- Starts, minutes, shots faced or the stated eligibility threshold.
- Cumulative GSAx or rate, with the provider’s sign convention.
- Save percentage and goals-against average as companion measures.
For broader background on goaltender metrics, see the 2019 Annual Review of Statistics and Its Application article “Goaltenders”. It is useful context on goalie measurement; the available summary does not establish a specific predictive figure for GSAx.
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