Thesis advisor: Michael Grubb / This paper investigates the discount rates applied by NFL teams to future draft picks when engaging in trades during the annual NFL Draft. Utilizing a dataset of 353 draft pick trades from 2010 to 2024, the study employs a non-linear regression model to estimate the parameters of a Weibull distribution, which captures the value decay of draft picks over time. The model incorporates a discount factor to account for the devaluation of future picks. The results provide evidence of varying discount rates across the three days of the draft, with the highest rate of approximately 182% on Day 1, and lower rates of 53% and 97% on Day 2 and Day 3, respectively. These findings suggest that NFL teams place a greater premium on immediate returns when trading early round picks. The study contributes to the understanding of decision-making under uncertainty in high-stakes environments and offers insights into the strategic considerations and market dynamics of the NFL Draft. / Thesis (BA) — Boston College, 2024. / Submitted to: Boston College. Morrissey School of Arts and Sciences. / Discipline: Economics. / Discipline: Departmental Honors.

Berri and Simmons (2009) investigate the relationship between the NFL Combine and the NFL Draft. They find that a quarterback’s performance in the Combine can have a significant impact on that player’s draft position. However, they find that no known aspect of a quarterback before they are drafted is an indicator of success in the NFL. I examine if these relationships exist for the Running Back position. I find similar results to Berri and Simmons: that performance in the Combine does have an effect on that player’s draft position, but that no aspect of a running back’s pre-draft characteristics can be seen as a sign of future NFL success.

This paper uses empirical analysis to value of each section of the NFL Draft relative to the others in order to establish which NFL draft picks are undervalued. We crafted a new performance metric that uses the size of a given draftee’s second contract relative to his peers to evaluate his performance over the course of his previous contract. Using two OLS regressions, we predict the level of performance, given by our metric score, for each section of the draft. We then use the residuals from these regressions to investigate which sections of the draft are undervalued. The results show that mid-3rd round picks and late 5th round picks are the best value per dollar in the draft.

NFL teams spend massive sums to ensure they are prepared for the future, but how should they determine whom that future includes? This study set out to find what predicts NFL success more accurately – collegiate in-game performance or the NFL Draft Combine. In the sample of 2007-2012 first-round picks, 191 athletes were measured in three NFL Draft Combine drills, two physical components, and a varying amount of ingame collegiate and NFL performance statistical categories, dependent on position. Secondarily, this work examined Power 5 and non-Power 5 players to determine if attending a more prolific program was predictive of NFL success. Findings included that 40-yard dash and vertical jump are predictive of offensive linemen and cornerback NFL success, that in-game collegiate statistics are most indicative of NFL success amongst defensive players, and that Power 5 prospects are no more prepared for NFL success than those coming from non-Power 5 schools.

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