3BI: behavioral economics in the NFL playoffs, Jerry Seinfeld, and cognitive biases
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3BI is back with the first newsletter of 2021! Though, so far, it just feels like we’ve entered the 13th month of 2020.
Here are this week’s insights:
Behavioral economics in the NFL playoffs
The NFL playoff’s divisional round is this weekend, and two of the teams can attribute behavioral economics to at least a part of their success.
The Cleveland Browns are traditionally one of the worst teams in the league, but won 11 regular season games this year and beat the Pittsburgh Steelers in a major upset last weekend.
The team’s turnaround began with a behavioral economics paper:
The turnaround was orchestrated by a small team of analytics wonks in the front office, led by chief strategy officer Paul DePodesta, who was Billy Beane’s assistant general manager at baseball’s Oakland A’s during the early 2000s. They based their strategy on an academic paper published in 2013 by Wharton’s Cade Massey and Nobel laureate Richard Thaler, “The Loser’s Curse: Decision Making and Market Efficiency in the National Football League Draft.”
In the famous paper, the researchers evaluated the market value versus the actual value of players selected in the league’s draft. The market value is demonstrated by trades: when a team trades later round selections in exchange for another team’s earlier pick. For example, a team might give up the 4th pick in the draft and get the 12th pick and the 31st pick in return.
That market value is compared with the actual value of the player later in their career, when performance is valued instead of potential. If the player is more valuable later in their career than in the beginning, than they’ve shown “surplus value” and have become more valuable over time.
They found that surplus value was much more common with later picks rather than higher ones:
…we find surplus value of the picks during the first round actually increases throughout most of the round: the player selected with the final pick in the first round on average produces more surplus to his team than the first pick!
This means a few things:
Predicting which players will be successful is extremely difficult.
Thus, most highly touted prospects won’t pan out, despite the high cost of acquiring them.
Most teams are better off making more picks at a lower value to have more chances at finding a star at a lower overall cost.
Despite this data, teams generally do the opposite and do whatever they can to get higher round picks. There are a few behavioral biases causing this:
Predictions based on intuition tend to be more extreme and varied than is justified by data. Sports teams rely heavily on scouts who watch prospects in person. Such input has value, but is also easily swayed by the many biases in our decision-making (the famous book and movie Moneyball is basically about this). They’d be better off combining scout’s input with evidence (e.g., player’s running speed) and the prior probabilities of future value.
People tend to be overconfident in their judgements, and overconfidence is exacerbated by information—the more information experts have, the more overconfident they become. Teams spend months poring over prospects and get overconfident that this increases the certainty of success. Further, teams are likely to believe they are closer to winning than they actually are, justifying paying more for a potential immediate star using earlier picks.
The winner's curse, a phenomenon most commonly observed in auctions, wherein the winner is the bidder with the most optimistic evaluation of the asset, and therefore will tend to overestimate its value and overpay. In the NFL draft, “teams will overestimate the need to trade-up in order to acquire a player they value because they will believe, unduly, that other teams value him similarly.”
Loss aversion and anticipated regret. The idea of missing out on a superstar would be particularly painful, so teams pay more to avoid that regret.
This systematic bias among teams meant there was opportunity:
A smart NFL front office could exploit other teams’ impatience by systematically trading higher-round picks for more lower-round ones and the current year’s picks for higher-value ones in future years. At least one team had already tried it. Patriots head coach Bill Belichick read a previous version of the paper in the early 2000s and used its insights by trading down first-round draft picks in seven of the 18 NFL drafts during his tenure—during which the team has made the playoffs 15 times and won nine conference championships and five Super Bowls.
After a series of meetings with Mr. Thaler, the Browns analytics staff also took his idea to heart. With a patient long-run goal of “winning 100 games in 10 years”—an average seasonal record of 10-6—owner Jimmy Haslam told the front office to follow the strategy of exploiting other teams’ impatience. He understood the Browns would have bad seasons in the short run but would accumulate valuable picks and perform well in the future.
A few years into implementing this strategy, it seems to have begun paying off.
The Browns aren’t the only one of this weekend’s teams utilizing behavioral economics to create an advantage. The Baltimore Ravens do so, as well, but directly on the field rather than the front office.
The Ravens have 26-year-old Yale behavioral economics major Daniel Stern in the booth communicating win probabilities during games to maximize in-game decision-making. While most coaches and coordinators rely on intuition and gut feel to make key play calls, they’ve turned to statistics and probability.
First, Stern works with the coaching staff set the rules of the upcoming game’s decisions. From baltimoreravens.com:
"During the week, Stern, Harbaugh and other members of the Ravens coaching staff come up with a plan for how they want to approach each game from a strategic perspective," Kapadia wrote. "They decide on a set of rules that will give them the best chance to win, and Stern reminds Harbaugh of those rules on the headset during the game."
From the Athletic:
Every week, Stern watches games from around the league and studies how teams handle clock management timeouts, two-point decision-making, fourth-down decision-making, accepting/declining penalties and other in-game situations. The Ravens have a meeting where they discuss how they’d handle similar scenarios.
They then use that data to dictate decisions on the field:
“I just think that every decision, you have a confidence interval,” he says. “An economist would say you have a confidence interval, but just as a person thinking about it, you know that you’re just making these guesses about how likely you are to win the game. You’re making your best guesses. Math is helping you make better guesses than you might be able to make purely with your intuition. But you’re making your best guesses, and every single one of those guesses, it’s not precise. Like you don’t know for sure, ‘Ok we have a 65% chance of getting it.’ What does that mean when you get to the line and you see how they’re lined up and you see who they have on the field?
You know where you are in the ballpark, and if there’s an extreme difference between how likely you need to be to get it and how likely you are to get it, then those are the situations where you want to go for it, right? But then when it gets tighter, who’s to say that his intuition about how likely we are to get it isn’t better than whatever estimate that we have is? What’s important is that he’s cognizant, which he is, of if we do get it and we don’t get it, how does that impact our probability of winning the game down the line? And then with all of that information, he is better at making decisions than a computer would be. But better for it also because he has a really acute awareness of what the computer would do if it were him.”
The Ravens utilized those analytics to have one of the best offenses in the NFL last year, and, after a slower start to the year, a playoff win last week.
Read more in the Wall Street Journal, The Athletic, and baltimoreravens.com.
Jerry Seinfeld’s take on behavior change
Jerry Seinfeld was recently interviewed on Tim Ferriss’ podcast and shared some interesting insights on the principles of behavior change he used to climb to the top of the comedy world.
To build a habit and get anything done, especially creative endeavours, you have to train your brain:
It’s like you’ve got to treat your brain like a dog you just got. The mind is infinite in wisdom. The brain is a stupid, little dog that is easily trained. Do not confuse the mind with the brain. The brain is so easy to master. You just have to confine it. You confine it. And it’s done through repetition and systematization.
Seinfeld’s commitement to systems and repitition led to the famous “break the chain” productivity strategy:
He said the way to be a better comic was to create better jokes and the way to create better jokes was to write every day.
He told me to get a big wall calendar that has a whole year on one page and hang it on a prominent wall. The next step was to get a big red magic marker. He said for each day that I do my task of writing, I get to put a big red X over that day.
“After a few days you'll have a chain. Just keep at it and the chain will grow longer every day. You'll like seeing that chain, especially when you get a few weeks under your belt. Your only job is to not break the chain.”
See the interview here and learn about break the chain here.
20 cognitive biases
Here’s an informative list of 20 foundational cognitive biases from Business Insider (click the picture to expand):
Have a great weekend!