25 July 2013

Analytics Creeping Slowly to the NBA and PBA?

Basketball Analytics
I know the dynamics involved in baseball and I have a good idea on how numbers are used in that game. My interest was tickled after watching the movie "Money Ball" starring Brad Pitt way back in 2011. The movie emphasized the significance of how the proper interpretation of numbers can bring to success to a sport.

In the National Basketball Association (NBA), some of us saw how John Hollinger, a former statistics geek, basketball analytic and now Vice President of Basketball Operations for the Memphis Grizzlies, developed and used Player Efficiency Rating (PER) to gauge performance. It was rumoured that those same analytics were used in deciding to trade Rudy Gay, which later led to the team’s improved success rate.

Boston Celtics General Manager was the latest proponent that supports intensive use of numbers and analytics to gauge player performance and develop strategies. This led him to hire Brad Stevens to replace Doc Rivers and also Drew Cannon, the statistics man for Stevens at Butler.

With all these development, are we seeing the growing movement towards the utilization of analytics in the NBA? Will we see the same form of analytics being adopted by the teams in the Philippine Basketball Association (PBA) to evaluate both a player's and a team's performance and constantly evaluating players for the draft or for a potential trade?

Right now, all anybody in the NBA or PBA had was the box score that any fan can see in a local newspaper. Those numbers, along with a good pair of educated eyes, supposedly told you all you needed to know about players and teams.

But basketball is a little bit more complicated than baseball as the game is in continuous motion and more factors affect the numbers. The basic numbers like shooting percentage, scoring and rebounding still have meaning, but don't address the full picture or capture the subtleties of the game that went undiscovered before.

Those basic numbers, when put in proper perspective and taken into account with terms like pace and usage, become much more relevant. Evaluating total team performance not only relies on the old-school talent evaluator's eyes and experience but also an assortment of advanced metrics that are getting ever more complicated.

However, many who oppose the use of analytics in basketball claim that it's simply a way for those who don't know much about the game to justify their beliefs. This is the "old school" explanation of analytics, as it is was never much of a tool in basketball years ago. While neither the "old school" or "new school" beliefs are necessarily right or wrong, it is foolish to completely throw away either.

Those who use analytics must also have a great understanding of the game to properly draw conclusions. Anyone can look at numbers, but it takes a smart basketball mind to interpret them. It is a great way to confirm what your eyes see, or to clear up something that might not be easy to pick up on by simply watching film.

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