Analytics - Useful Tool Or New Age Gimmick?

The rapid development of the Digital Age has ushered in an overabundance of new tech. Smart phones, quantum computing, re-usable rockets. Quite literally, the sky's the limit. One unique revolution is the dependence on data to reach conclusions; the invention of the personal computer has allowed humans to stockpile absurd amount of data & store it on a simple hard drive. This is incredibly useful for generating math-driven hypotheses but also confusing in terms of deployment. Many folks hesitate to rely on data-driven assertions, especially when they contradict personal experiences AKA anecdotal testimony. However, data-driven analytical hypotheses serve to provide context to our personal accounts rather than replace them, which is a key distinction. Analytics serve a valuable purpose in assessing all ranges of subjects, and sports is no exception.

Bill James first proposed the analytical approach re: sports when he shook the world of baseball by introducing the colloquially termed "Moneyball." (Also a great movie starring Brad Pitt, streaming on Netflix.) This approach, in short, sets out to find undervalued assets and maximize value; in other words, create a sum greater than the value of its parts. This approach has drawn much controversy, but it is growing increasingly difficult to dispute whether or not it is effective. The Boston Red Sox finally overcame the Curse of the Great Bambino after 86 years largely because of their deployment of analytics. That and one of the deepest purses in professional sports, but I digress.

The analytic presence in the NHL cannot be ignored either. Back-to-back Stanley Cup winning GM Julien Brisebois has publicly disclosed his belief in data-driven analysis to construct his team.

One of the best in the business at making analytics easily digestible for NHL audiences is JFresh (@JFreshHockey on Twitter). His quickly accessible Player Cards provide a holistic capture of players, teams & prospects. Take this Auston Matthews player card for example:

A quick, concise view of Auston Matthews' rank vs. his peers in all areas of the game.

Also consider these microstats, which are quite fun. These illustrate specifically what a player does well & what he does not compared to his peers.

(Conclusion: Auston Matthews is good at hockey)

Analytics aren't meant to be relied upon for sole testimony, but if deployed properly they've proven a vital asset in constructing valuable insight to the game.

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