Well, not literally. As funny as it would be, nobody is expecting the Senior Editing staff of Journal of Applied Psychology to march the ball up the field. But I/O psych actually does have practical applications to sports.
We already know that if you have a bunch of job applicants you can use properly constructed and skillfully administered employment tests to pick out the most suited to the job. If you have a Pipeline Operations Tech, for example, you may test for mechanical knowledge, basic mathematical ability, and upper body strength. Add up those three test scores and blammo! You just have to pick the applicant with the best results to maximize your chances of getting a high-performance employee.
And so it is with sports –or can be. Coaches and scouts already use lots of information about athletes to draft new players or trade veteran ones. 100 meter dash, bench press, high jump, height, weight, number of yards gained during high school or college, et cetera. These analysts of talent look at all these things and make a determination about an athlete’s potential performance. It’s not that different than looking at an applicant’s mechanical knowledge, mechanical ability, or upper body strength, is it? (Hint: no, it’s not.)
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Thing is, coaches and scouts usually aren’t scientific or methodical about it. Going by gut and experience only lets our puny human brains take into account a few factors at a time, and it leaves us vulnerable to all kinds of human foibles and biases. So coaches and scouts are only taking advantage of a tiny fraction of the data’s true predictive power (or worse, they’re making entirely wrong predictions).
Enter I/O psychologists or others trained in the mysterious ways of data management and statistical analysis. It’s fairly straight-forward to take a bunch of data and see what predicts what by building a multiple regression formula, a path analysis, or a structural equation model. (That’s basically statistical l33t sp34k for saying “to the degree that a player has X, Y, and Z, he/she will do well”.)
As a matter of fact, my friend and fellow U. of Missouri -St. Louis graduate Spencer Stang has a company called SportLab that does this very exact thing with a product called “BASELINE”.
Another interesting example of this sort of thing can be found in a book called “Moneyball: The Art of Winning an Unfair Game”. I haven’t read it yet, but I did hear a fascinating interview with its author on NPR. The book describes how Billy Beane, general manager of the Oakland A’s, looked at these kind of stats and systematically interpreted them to scoop up the right players (most often those who were not highly sought after by others) to assemble a winning team –all on one of the League’s smallest budgets.
If this catches on, we’ll be worshiped like tiny, number crunching demigods. It’ll be awesome.
That Spence guy sounds pretty cool.