This is an attempt to leave behind the question of goalie variation (for now!). Some points:
1) Man, I need to learn more before I go further. Pretty clear.
2) In the meantime, I did produce goalie figures for the top 23 goalies from 2013: game-to-game SV% along with standard deviations (SDs) and mean absolute deviations (MDs). I included MDs as well because, as was mentioned earlier, the spread of gtg SV% is far from normal. Having MDs calculated does no disservice. (There's a significant break between 23 and 24 in TOI, so that's why I did the top 23.) The top 3 in terms of possible "inconsistency" characteristics (i.e. greatest SDs/MDs) were Schneider, Rinne, and Backstrom. The top 3 in term of possible "consistency" characteristics (i.e. lowest SDs/MDs) were Lundqvist, Niemi, and Reimer. All the numbers I used are in this .xls file (I think one person asked, so feel free to have a gander). Here's the summary (sorted by total SV%):
|name||gtg mean SV%||gtg SV% dev||mean absdev|
Table 1. Game-to-game SV% mean with standard deviation and mean absolute deviation of top 23 goalies by TOI (sorted by total SV%) in 2013.
3) If I were to go farther, the way I'd do it is to stick to 2013. (I know, I'm in a stick in the mud.) I'd use the season SV% for a particular goalie as a probability. I'd then do a simulation of each game, knowing exactly how many shots they faced in each game in 2013. I'd then, using the season SV% and a random number generator, determine save-no save for each shot in each game. In doing so, one creates a simulated set of game-to-game SV% that has normal distribution characteristics derived purely from the season SV%. I'd do that a 100 times and figure out what might be the closest thing to a "normally distributed" game-to-game SV% looks like. (Another idea was to look at SV% by score situation. Obvious issues there with team play. Also, game-to-game SV% has its own issues as a measure.)
4) There's other stuff I'd like to try out first, so this is going to the back burner. My final thought before I leave this behind for now is partly inspired by Bull Durham, but it came up as I was getting knee deep in the goalie data.
Here it is.
I was simulating Bobrovsky for his 38 games, and I was thinking, wow, this dude won the Vezina. Good for him, right? And then Bryzgalov got bought out, and I thought, man, that must suck for him. I know a guy who played goalie growing up and it's such a tough position mentally.
Then Crash Davis appeared.
I looked at bob vs. bryz in 2013. How many saves would bryz have needed to make to be in Vezina contention? How many saves would it have taken to just be average and maybe no buyout of that big contract (he'll lose about $11.5 million dollars with the buyout--I know he still gets $23 million, but still)?
Bryz played 40 games in 2013. If he makes just ONE extra save every game, his save percentage jumps to 93.7% (higher than bob's 93.2%). If bryz just makes ONE extra save EVERY OTHER GAME, his SV% jumps to 91.8%, above the league average. That's it. 20 extra saves. Just 1 save every other game. (Who doesn't want to see Bryzgalov re-enact the Crash Davis scene in the pool hall? C'mon!)
Anyway, it's tough to get my head around this when thinking about goalie "consistency". Deserving of a re-visit after a bit, perhaps. For kicks, here's their cumulative SV% for 2013. (There was another thought about trying to find number of games where this volatility in SV% drops heavily. It looks like around 20 games, but this is likely only an educated guess at this point.)