It’s NFL draft week, a time when hope springs eternal for every fanbase. The draft offers an opportunity for Super Bowl-contending teams to plug any holes or provide depth, while the worst teams hope to land the next Joe Burrow – a player who can singlehandedly change the direction of their franchise. It’s impossible to overstate the importance of the draft, which is why teams gather countless data points on players, trying to quantify their potential as NFL players. Where there is data, there are economists, whose research is valuable to both NFL teams and investors.
Cade Massey and co-author Richard Thaler’s seminal paper, “The Loser’s Curse: Decision Making and Market Efficiency in the NFL Draft”, has been partially adopted by some NFL teams over the last decade. It’s a delightful read if you love 60 pages of academic jargon, but if not, here are two of the main takeaways:
1. Teams overvalue high picks, so trading down is a profitable strategy.
Massey and Thaler came to this conclusion after considering a simple question: “What’s the likelihood that a player is better than the next player chosen at his position?”
If teams were adept at valuing prospects, the probability would be very high. If teams had no ability to judge talent, the better player would be selected higher only 50% of the time. After combing through all rounds and all positions of prior drafts, the authors arrived at the answer…52%, hardly better than a coin flip.
Despite evidence to the contrary, teams believe in their ability to differentiate between, for example, the best and second-best quarterbacks. They are willing to pay a huge amount to move up in the draft to get “their guy.” There are notable exceptions, but generally, teams near the top of the draft benefit from trading down. The Chicago Bears did this last month, trading the first overall pick to the Panthers and receiving a haul: two first-round picks, two second-round picks, and star receiver DJ Moore.
2. Teams overvalue immediacy, so patience is rewarded.
A widely-accepted guideline for trading draft picks, confirmed by historical trades, is that teams can “gain a round by waiting a year.” For example, a team trading this year’s 3rd-round pick can expect to receive a 2nd-rounder in next year’s draft. This principle, being paid for patience, applies to finance – I wouldn’t give you $100 today to receive $100 a year from now, I might demand $105 as the price for waiting. But, the authors conclude, teams willing to surrender a future pick a full round higher to acquire a pick in this year’s draft are overvaluing immediacy. Their analysis equates it to trading $136 next year for $100 today.
Teams that can be patient should “sell” overvalued picks today to “buy” undervalued future picks.
Other economists have built on Massey and Thaler’s research, confirming their conclusions, and offering other ways teams can improve their odds in the draft. Despite the mounting evidence, few teams lean fully into “draft analytics.” It raises the question: If the research is so well-established, why haven’t more teams embraced it?
A few theories…
- Overconfidence
Imagine you’re Scott Fitterer, the general manager of the Carolina Panthers and owner of the first overall pick. You’ve invested hundreds of hours personally dissecting film, talking to coaches, and interviewing players. You’ve meticulously charted every measurable on every player, from broad jump to hand size. Every additional bit of information gives you more confidence in your final decision. On draft day, with the clock ticking, your team of scouts and analysts looks at you, anxious to hear: Bryce Young, CJ Stroud, or Will Levis?
Will you stare at your shoes and, slight quiver in your voice, nervously propose: “The expected value between the players is extremely similar with a wide standard deviation and dozens of confounding variables. Perhaps we should trade back to 3rd, receive extra picks, and select whoever is remaining.”
F no!
“We’ve done the homework and we’re sure that Bryce Young will be the face of the franchise for the next decade.”
- Career risk.
Imagine you’re Chris Ballard, general manager of the Indianapolis Colts. Your tenure as GM started strong, but you haven’t been to the playoffs since 2020 and the seat is getting uncomfortably hot. Your analytics guy wants to trade the 4th overall pick to move later in the first round and acquire multiple future picks that could form the core of the team. Internally, you see the value of making the trade, but you doubt ownership and the fans would agree. Make the trade, and you may not be around long enough to see that core develop. With the 4th pick, you feel the pressure to draft someone that the fans will be excited about, who will sell jerseys and season tickets, and, hopefully, buy you a few more years to rebuild the roster.
- Model aversion.
Imagine you’re Mike Brown, owner of the Cincinnati Bengals. Your dad was a founding father of the NFL. Football is literally the family business. Now, a baby-faced, Ivy-league intern is in your office, explaining nonlinear regressions, algorithms, and other academic terminology that will allegedly revolutionize your approach to the draft. Even if you could understand the inner workings of his model, how could you trust its recommendation over your own instincts?
- A focus on outcomes, instead of probabilities.
We live in an outcome-driven world. Win-or-lose? Success-or-failure? Judging decisions solely based on the outcome is a useful mental shortcut – we can’t possibly explore all the alternate universes where things work out differently. But drawing incorrect conclusions from past decisions will lead to worse decisions in the future.
One of my first blog posts centered on the self-employed day trader who won $1.2 million betting his life savings on Tiger Woods to win the Masters and the world’s oldest man who smoked 2-3 cigarettes daily. Keeping with the sports theme, Coach K’s decision to intentionally miss a free throw that nearly became a legacy-altering loss. We’re surrounded by other examples of objectively poor decisions that pay off.
The opposite happens, too, when the right decision, the one that puts the odds in your favor, doesn’t pan out. But that shouldn’t encourage us to pursue strategies with low probabilities of success. The best way to win in the long run is by understanding the odds.
Tying this back to investing – there are well-documented advantages that every investor can, and should, employ, but most investors don’t. To name a few:
- Everyone knows the benefit of diversification, but many investors, confident in their ability to pick the top stocks and avoid the worst, forgo it.
- Expenses and taxes erode returns, so minimizing costs is crucial, and yet most investors aren’t aware of their expenses and fail to engage in tax-saving strategies.
- Research has proven that tilting your portfolio toward value stocks and away from expensive ones can improve returns, but high-flying growth stocks are usually the darling of retail investors.
- There are clear advantages to international diversification, but after a decade of international stocks trailing US stocks, impatient, outcome-based investors have jumped ship.
With the abundance of data available, we have more resources than ever to make informed decisions. However, one obstacle to purely objective, research-backed decisions remains…human nature. We are hardwired for overconfidence. We can’t help but consider career risk when making decisions. We’re desperate to avoid potential regret (what if the pick I trade winds up being a Hall of Famer?). As investors, we’re subject to the same flawed instincts as NFL GMs. The key to successful decision-making lies in employing research-backed strategies while avoiding the pitfalls of human nature.
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