The Futility of Predicting Playoff Series Goaltending

Goaltending is a devilishly difficult thing to predict at the best of times. In smaller samples, even the most powerful forecasting tools fall victim to variance and luck. Playoff performances, and to a greater extent single series, represent such samples and we’re frustratingly inefficient at predicting them using traditional methods. I’m excluding more refined models such as @Garik16’s Marcels, which may very well do a better job of it. I compared regular season 5v5 Sv% over different intervals of time, both total and strictly on the road, for all playoff goalies over the past three seasons and how they matched up with playoff 5v5 Sv%. Here are the results:
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How well do goalies age? A look at a goalie aging curve.

This guy may be lying flat on his face like this more and more often as he’s reaching the big 35.

 

A few weeks back, I unveiled Hockey Marcels: an extremely simplistic system for projecting goalies performance going forward, utilizing just the last four years of a goalies’ play to do so. Building off of work by the great Eric T., I weighted more recent years more heavily than older ones, to try and give a better estimation to what we should expect from goalies going forward.  In addition, I added a regression factor to Eric’s work, such that we could deal with varying sample sizes and the extreme variability of NHL goaltending.

But the one thing I didn’t include was an aging adjustment.  This is an integral part of any serious projection system for the obvious reason:  Using past years to project future data is sound, but players will be OLDER in the future and increased age generally results in worse performance (except for the really young).  This is especially the case with hockey, where peak performance has been found to be at ages 24-25.   If we really want to project goalie performance going forward, we need to find out how well goalies age.

A few people have looked at this before (both Eric and Steve Burtch have written about goalie aging in previous posts), but I wanted to actually get #s rather than just a graph on how aging affects goalies of all ages.  So I used hockey reference to get the seasonal data of all goalies from 1996-1997 to the present season who had played 20 years, and tried to take a look.

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Save Percentage vs the Experts: Round one, introduction of concepts

Photo Cred: Eric Hartline-USA TODAY Sports

Due to starting my dive into hockey statistics as a Winnipeg Jets fan, save percentage has always been a pretty big interest of mine, specifically in what it can and can’t tell us. The truth is, it is still a pretty rudimentary statistic and likely will be improved upon in the future. However, simple does not always mean bad or useless.

Of the three most common “goaltender statistics”, save percentage is the one controlled most by goaltenders. How can I be so sure of that? Well it can be provided with simple logic.
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