The Loser's Curse and the Critical Role of the Utility Function

TL;DR

This paper challenges previous claims of bias in NFL draft decisions by showing that when considering utility functions focused on acquiring elite players, general managers' choices appear rational rather than irrational.

Contribution

It introduces a Bayesian hierarchical Beta regression model to redefine utility functions, demonstrating that draft decisions align with strategic goals when properly modeled.

Findings

Reconsidering utility functions alters interpretations of draft decision rationality.

Alternative utility models show no systematic bias in NFL draft trades.

Highlighting the importance of utility function specification in decision analysis.

Abstract

A longstanding question in the judgment and decision making literature is whether experts, even in high-stakes environments, exhibit the same cognitive biases observed in controlled experiments with inexperienced participants. Massey and Thaler (2013) claim to have found an example of bias and irrationality in expert decision making: general managers' behavior in the National Football League draft pick trade market. They argue that general managers systematically overvalue top draft picks, which generate less surplus value on average than later first-round picks, a phenomenon known as the loser's curse. Their conclusion hinges on the assumption that general managers should use expected surplus value as their utility function for evaluating draft picks. This assumption, however, is neither explicitly justified nor necessarily aligned with the strategic complexities of constructing a National Football League roster. In this paper, we challenge their framework by considering alternative utility functions, particularly those that emphasize the acquisition of transformational players--those capable of dramatically increasing a team's chances of winning the Super Bowl. Under a decision rule that prioritizes the probability of acquiring elite players, which we construct from a novel Bayesian hierarchical Beta regression model, general managers' draft trade behavior appears rational rather than systematically flawed. More broadly, our findings highlight the critical role of carefully specifying a utility function when evaluating the quality of decisions.