Yesterday was the NFL Draft. It is a day of hope where teams can look to their future and see a potential Pro-Bowl individual joining their cadre of players. For instance my favorite team, the Green Bay Packers, selected linebacker A.J. Hawk from Ohio State University. The team was considering trading their number 5 pick and multiple other draft picks for the No. 2 pick to select Reggie Bush from USC. Would this have been a wise choice?
A recent 2005 working paper by Cade Massey and Richard Thaler suggest that teams are overconfident in their ability to predict the sucess of a given player in the draft. They hypothesize that teams who trade picks to move up in the draft ‘overpay’ for the value they receive. To quote the article:
“Our findings suggest the biases we had anticipated are actually even stronger than we had guessed. We expected to find that early picks were overpriced, and that the surplus values of picks would decline less steeply than the market values. Instead we have found that the surplus value of the picks during the first round actually increases throughout the round: the players selected with the final pick in the first round on average produces more surplus to his team than than the first pick, and costs one quarter the price!
“Our modest claim in this paper is that the owners and managers of National Football League teams are also human, and that market forces have not been strong enough to overcome these human
Massey and Thaler believe that the excessive self-confidence can also be applied to physicians.
“…even professionals who are highly skilled and knowledgeable in their area of expertise are not necessarily experts at making good judgments and decisions. Numerous studies find, for example, that physicians, among the most educated professionals in our society, make diagnoses that display overconfidence and violate Bayes’ rule (cf. Christensen-Szalanski & Bushyhead, 1981; Eddy, 1982). The point, of course, is that physicians are experts at medicine, not necessarily probabilistic reasoning. And it should not be surprising that when faced with difficult problems, such as inferring the probability that a patient has cancer from a given test, physicians will be prone to the same types of errors that subjects display in the laboratory. Such findings reveal only that physicians are