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 07-12-2012, 11:18 PM #5 Czech Your Math Registered User     Join Date: Jan 2006 Location: bohemia Country: Posts: 4,846 vCash: 500 Nice work, this is an interesting study. I like how it's translated into a metric of value which allows direct comparison between the goalies in terms of total value. I also like the general design/methodology of the metric. If I understand correctly, your metric rests on a couple of fundamental assumptions: - that save % better measures the quality of goaltending than the more direct GAA (of course various factors influence each) - that the replacement level of goalies is a constant .015 below league average of save % If you already have the data in a format that allows you to make additional calculations relatively quickly, you might want to try some alternative approaches and see how the results compare. Have you considered using the more direct GAA? I'm not familiar with much work on goalies, so I wouldn't be surprised if that had already been done, or you have other reason to believe your approach superior to that one. Whether you use save % or GAA, you might also consider different ways of determining replacement level goaltending. For instance, you could approach it as follows: - Sort the top 2N (where N is # teams in league) goalies in NHL in terms of games played. Assume the top 1N (in terms of games, or alternatively in terms of either save % or GAA) of those 2N are the "starters" and that the remainder are "backups." Use either the mean or median goalie among goalies 1N+1 to 2N as the replacement level. An alternative to selecting the top 1N goalies is to simply use the "actual" starters and then use the same basic method from there. - Sort all the goalies in terms of games played or GAA/save% (if use either of latter two, could use min. games or top ~2.5N goalies in games). If sorted by save % or GAA, use the 2N+1 goalie as replacement level. If sorted by games, use a weighted average of GAA/save% for all goalies > 2N in games. - Sort the top 2N goalies in one of the above ways, and calculate a standard deviation of GAA/save% among those goalies. Then calculate replacement level as X standard deviations below the mean of those 2N goalies. I'm not saying any of these will necessarily yield better results, but I think they at least some are worth considering. Besides being arbitrary, a fixed number may be more or less accurate as the depth of goaltending and/or league parity vary. I know it's difficult to determine replacement level, but the approaches I outlined above rest on logic of different sorts that might be accepted over a SWAG (however accurate that may be).