Super crunching has applications in a wide range of fields, such as wine dealing and baseball.

Super crunching might sound like something from a video game, but it refers to the statistical analysis of large data sets – and its applications are nearly endless. Let’s start with some surprising examples.

Super crunching can be used to predict the future quality of vintage wine – indispensable knowledge for wine dealers.

A high-quality red wine is an investment because it gets better as time goes on. This means wine dealers need to be able to predict a wine’s future value.

Orley Ashenfelter, an economist and wine enthusiast, has found a way to accurately predict the quality of Bordeaux wines by analyzing historical relationships between weather and the price of wine.

Ashenfelter has found that each centimeter of winter rain raises the expected price of a wine by 0.00117 dollars. His analysis is so accurate that wine dealers now use it to determine whether or not they should buy a wine, and at what price.

Super crunching can also be applied to baseball. Bill James, a baseball writer, has done for baseball what Ashenfelter did for wine.

James challenged the assumption that baseball experts could assess talent simply by watching the players. He postulated that data-based analysis of players’ previous form in the game would be superior – and he was right!

Traditional talent scouts had little faith in Jeremy Brown, an aspiring player who was overweight, but James’s calculations said otherwise. The Oakland A’s decided to sign Brown based on James’s analysis of his past runs and the decision turned out to be a wise one: Jeremy Brown had his major league debut in September 2006.