When it comes to goaltending, bet on consistency

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Evaluating goaltenders remains one of the most difficult objectives in hockey, whether you are pouring through video or analyzing data.

So much of the position’s performance hinges on the defensive structure and integrity in front of the goaltender, and our eyes frequently lie to us. What appears to be a great save may be a goaltender merely recovering poor positioning; what appears to be an ugly goal may have been a shot impeded by traffic in front.

But we aren’t flying totally blind (pun not intended). We know the core deliverable of a goaltender is to thwart the opposition and minimize goals against. And we know a goaltender does this by, simply put, making lots of saves.

After hundreds of games, we get a sense for which goaltenders are better than others – Tampa Bay’s Andrei Vasilevskiy, New York’s Igor Shesterkin, and Winnipeg’s Connor Hellebuyck have shown themselves to be a cut above the rest, regardless of how you analyze their play.

From a data perspective, we’ve made advancements to better quantify goaltending performance. Raw save percentage never seemed adequate enough a measure because it is comprehensively clouded by team effects.

More recently, we’ve used Goals Saved Above Expectations, which attempts to baseline all goaltenders by measuring saves in the context of the difficulty of shots faced. This measure may have helped us better differentiate between the likes of, say, Dominik Hasek and Martin Brodeur. Both are Hall of Fame goalies, but Brodeur’s workload – no matter how you quantified it – was routinely less burdensome. Such is the luxury of backstopping a Devils team with impeccable structure and a knack for pushing shooters to the least dangerous areas of the ice.

Goaltenders are