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How to Compare NHL Goaltenders With SV%, GAA and GSAx

Compare NHL goalies fairly by matching season, competition and workload, then use SV%, GAA and model-specific GSAx together rather than treating any one statistic as a verdict.
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Use save percentage (SV%), goals-against average (GAA) and goals saved above expected (GSAx) together, comparing goalies over the same season and competition and accounting for workload. SV% and GAA describe results; GSAx adds a model-based estimate of shot difficulty. None is a complete measure of a goalie’s performance.

What each goalie statistic tells you

Save percentage (SV%)

SV% is saves divided by shots on goal faced. It is an intuitive measure of how often a goalie stopped shots that counted as shots on goal. The NHL defines a shot on goal as one that would have entered the net had it not been saved (NHL Hockey Glossary).

SV% does not distinguish an easy shot from a dangerous one: each shot on goal contributes to the rate without an adjustment for its difficulty. Read it as a broad save-rate signal, not a shot-quality-adjusted score.

Goals-against average (GAA)

GAA is goals allowed per 60 minutes of playing time. A lower figure means fewer goals were conceded per 60 minutes in the sample being compared. It is a time-based result, not an explanation of how difficult the shots were or how much the team’s defense affected them. The Seattle Kraken’s goaltending analytics explainer describes GAA alongside other measures.

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Goals saved above expected (GSAx)

GSAx compares the goals an opposing team was expected to score with the goals it actually scored against the goalie. A positive value means fewer goals were allowed than expected; a negative value means more were allowed than expected. It adds shot-quality context to the recorded result, but it is an estimate produced by a model—not a direct count of goals the goalie personally prevented.

Expected-goal models can use factors such as shot location, game state, preceding shots and shooter, and different models make different choices about inputs and calculations. The Kraken notes that public models vary and depend on the data available. When comparing GSAx, identify the provider and use the same model and game-state scope for both goalies.

How to make a fair comparison

  1. Set the timeframe. Compare the same season or the same defined multi-season span. NHL.com’s goalie statistics table provides season and game-type filters, along with workload and results fields.
  2. Match the competition. Keep regular-season figures separate from playoff figures. A goalie’s regular-season rate and playoff rate describe different samples and should not be combined as if they were the same competition.
  3. Check workload and playing time. Look at games, starts, shots against and time on ice alongside the rates. Those fields help show how much play a statistic represents; two goalies’ rates are harder to interpret as a head-to-head comparison when their workloads differ substantially.
  4. Read the three measures in their proper roles. Use SV% for the share of shots stopped, GAA for goals allowed per 60 minutes, and GSAx for the result relative to a model’s shot-quality expectation.
  5. Align the GSAx model and game state. Use figures from the same provider and check which situations the calculation includes. The Kraken’s introductory analytics guide discusses game-state groupings and public-data limits.
  6. Explain differences rather than forcing one ranking. A strong SV% alongside less impressive GSAx can be consistent with facing shots that were easier than the model baseline. A lower SV% alongside positive GSAx can be consistent with facing more difficult chances. These patterns describe how the measures relate; they do not establish a specific cause or prove overall skill.

Why the statistics can disagree

SV% and GAA record outcomes without fully accounting for shot quality. GSAx attempts to account for that quality, but its result depends on the model’s expected-goal estimates and available inputs. Different models can produce different estimates, so a GSAx number without a named provider and matching scope is incomplete context.

Even detailed public metrics cannot fully capture positioning, screens, reads, defensive breakdowns or whether a goalie made the right decision. NHL reporting on goaltending highlights how shot type, distance, angle, rush context and defensive mistakes shape interpretation (NHL: “Elite goalies trust process, not stats”). The Kraken’s goaltending coach Colin Zulianello has also cautioned that numbers can mislead when separated from process and structure (From the Front Office: Colin Zulianello).

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A practical comparison checklist

  • Same season or clearly matched span
  • Same competition: regular season or playoffs
  • Games, starts, shots against and time on ice considered alongside rates
  • Same GSAx provider and, where possible, the same game-state scope
  • Outcome statistics distinguished from shot-quality estimates and qualitative evaluation

NHL.com’s goalie table lets readers examine season, game type, shots against, saves, goals against, SV%, GAA and time on ice. Historical, multi-season and game-by-game queries are also discussed in the NHL’s statistics-section overview. Public analytics resources mentioned by the Kraken include Natural Stat Trick, MoneyPuck, Evolving Hockey and HockeyViz; availability and metric definitions can vary by provider.

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