by Forechecker on 01/25/09 at 09:11 PM ET
The ascent of sabermetrics in Major League Baseball sparked a confrontation between the new-fangled math geeks with their correlation studies and algorithms, and the old-school empiricists, the traditional scouts who relied upon observation and experience to build winning organizations (as told in Moneyball, for example). While the progress of advanced statistical analysis in hockey has lagged well behind that of baseball, the opinions expressed in various forums (mostly blogs) built upon measures like Corsi Numbers, Shot Quality (PDF) and On/Off Ice +/- have been enough to create a threat in the minds of some, who fear an overthrow of the established understanding of the game.
A good example of someone reacting to that perceived threat comes today from Jason Gregor over at OilersNation.com:
Sabremetrics[sic] and Moneyball have worked in baseball, but would the same work in hockey?
To me the sports are just too different to allow statistical data to overtake live scouting.
Sigh… I cruise a lot of the statistically-oriented hockey sites, and I’ve yet to ever read anyone even remotely suggesting that statistical analysis could ever replace or overtake live scouting. Yet here we have another stirring defense against that imaginary foe…
Let’s take one portion of Gregor’s evisceration of statistical analysis in hockey:
Also in Sabremetrics, they feel that drafting a college ball player has a much higher rate of success than drafting a high school player. We will need to see at least a 15-20 year study to see if this is indeed true. That doesn’t seem to be the case in hockey. Almost all of the top young players have come from Major Junior or the European leagues the last ten years, and beyond. Crosby, Kane, Oveckin, Phaneuf, Getzlaf, Carter, Richards, Malkin to name a few.
The point that Gregor is missing here is that the baseball analysts identified a trend with collegiate players that they could exploit; just because that same trend doesn’t appear to exist in hockey doesn’t mean that statistical analysis is to blame. Similar methods, however, might point to strategic gains for the teams that investigate them. For example, are there lefty/righty matchups worth using when selecting players for a shootout? What about trying to identify which teams are likely to give up more rebound chances in their own crease, which could influence line combinations and offensive strategy? A GM reviewing the potential of various prospects would be wise to consult the notion of League Equivalencies (PDF), to help put into proper perspective offensive stats from various leagues like the AHL or Canadian Junior.
The bottom line is, statistical analysis in hockey is just a tool to open another line of inquiry, and every exercise in number-crunching needs to be placed in its proper context. The article over at OilersNation.com makes some good points, and the discussion in the comments afterward is even better. Sure, for a number of reasons hockey will always lag behind baseball in terms of how well numbers alone can describe the game, but that doesn’t mean we shouldn’t push those boundaries as hard as we can. As I’ve written before, to me, this question brings to mind Plato’s Allegory of the Cave; having watched the game in the traditional manner for so long, and then getting a peek at what statistical analysis might do to help illuminate it that much more, this hockey geek can only continue to walk into the light.
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