Biggest Mistake When Drafting a Quarterback?

Here are two: drafting a quarterback at the wrong time, and not drafting enough quarterbacks. 

I was reading about the concept of ergodicity and immediately thought of the New York Jets. Before we get to the Jets and their future draft selection, we need to understand ergodicity and path dependence. A situation is ergodic when path dependency is present. For example, if it’s near the end of the fantasy football season and the playoffs are a couple of weeks away, the order of wins and losses matter. I may enter each matchup with a 60% chance of winning, but a loss in the regular season is not nearly the same as a loss in the playoffs. 

Conversely, “a situation is deemed non-ergodic when observed past probabilities do not apply to future processes.” If fantasy football were non-ergodic, I’d have a 60% chance of winning the championship game regardless of my previous results in the playoffs. Alas, that’s not the world we’re living in. In fact, quite often we mistake ergodic situations for non-ergodic situations. 

Take Nassim Taleb’s casino example. About half the people in a casino will win money on any given night. The ruin of one player does not affect the ruin of others. This is what he refers to as ensemble probability. Let’s say there are 100 people in a casino on the average night. Instead of viewing the probability as it applies to an ensemble of 100 people at once, we need to view the probability as it applies to a single person taking 100 consecutive trips to the casino. Why? Because the individual will likely reach ruin far before their 100th trip to the casino, while the ensemble will not collectively be ruined. The state of ruin is an absorbing barrier that the individual cannot come back from. That’s the difference between ensemble and time probability, as well as the main concept behind ergodicity.

photo by Nassim Taleb

How does that get us to the Jets? I was listening to the Spotrac podcast, and something Mike Ginnitti said finally stuck with me after repeated exposure. He referred to the Jets and said “this team isn’t ready to draft a quarterback.” What was he referring to? Ergodicity, of course! The Jets have a unique problem, their team does not have the surrounding pieces to allow a quarterback to thrive. Even if they went 0-16 and drafted Trevor Lawrence, they are ignoring the concept of path dependency.

Let’s say Trevor will be a surefire star quarterback in the NFL. How often have we seen quarterbacks switch from one team to another and seemingly play like a new player? Just recently, Ryan Tannehill departed the Dolphins for the Titans and his career hit an entirely new trajectory. The Titans, like the Cowboys when they drafted Dak Prescott, were ready for a quarterback.

Taleb writes “If the investor has to eventually reduce his exposure because of losses, or because of retirement, or because he remarried his neighbor’s wife, or because he changed his mind about life, his returns will be divorced from those of the market, period.” If a team has the number one pick but their roster can’t support a quarterback, the return on the quarterback will not be equal to whatever return the team is estimating.

The most interesting part is this is the inverse example of ergodicity as the casino example. In that case, the absorbing barrier was individual ruin. In the NFL, there is no risk of ruin. Teams can’t be relegated, and most of the league’s revenue is divided evenly. With a star quarterback, however, there is the opportunity for an asymmetric payoff. Take Taleb’s warning to “never cross a river if it is on average four feet deep.” Self-explanatory. How about applying that to drafting quarterbacks? 

If you’ve been watching NFL games this season, you’ve probably seen a graphic displaying the records of the 5 quarterbacks drafted in round 1 of the 2018 draft. You can even take a step further back and look at the average record for a quarterback drafted #1 overall throughout NFL history. If you take the average record of all the quarterbacks from 2018, or all the ones drafted #1 overall, it’d be like crossing a river that’s on average four feet deep. You’d be ignoring the distribution. 

Here’s another example from Taleb’s article: Russian roulette. 

“Assume a collection of people play Russian roulette a single time for a million dollars –this is the central story in Fooled by Randomness. About five out of six will make money. If someone used a standard cost-benefit analysis, he would have claimed that one has 83.33% chance of gains, for an “expected” average return per shot of $833,333. But if you played Russian roulette more than once, you are deemed to end up in the cemetery. Your expected return is … not computable.”

In this scenario, expected utility is not entirely accurate because it’s skewed by outlier possibilities that aren’t representative of what people experience on average. 

That level of analysis is what teams need to be doing with quarterbacks. Starting with the end and working backwards. This reminds me of previous talk in the media regarding what the Cardinals should have done with Josh Rosen. For a multitude of reasons, people claimed that the Cardinals couldn’t possibly draft another quarterback with the #1 pick after previously drafting Josh Rosen. However, if the benefits of drafting a quarterback aren’t linearly distributed (they could certainly be lucrative), why not keep drafting quarterbacks until you find your franchise player?

The caveat being that the team is ready for him.