You Might Be More Average Than You Think.

Here’s what’s in store for today:

• Understanding “regression to the mean”

• Reward vs. Punishment

• Talent vs. Luck

Read time: 4 minutes

Here’s an exercise for you:

Forecasters predict a store chain will have a 10% increase in average revenue across all stores next year.

These are the sales from last year, broken down by each store:

Given the predicted 10% increase, what do you think the sales at each store will be for next year?

It’s okay to complete this exercise mentally, but it’s important to give a rough estimate.

You’ll understand why shortly.

Rewards or Punishments?

I recently read about how renowned psychologist Daniel Kahneman, author of Thinking, Fast and Slow, went to an Israeli flight school to teach about psychology and effective training.

He aimed to demonstrate how rewarding positive behavior was more effective than punishing negative behavior.

The flight instructor disagreed, providing evidence that punishing pilots with poor performance actually led to better results during the next flight test.

So, what was the instructor missing?

Turns out, his evidence was actually correct—but for the wrong reason.

What he didn't understand was the concept of regression to the mean.

This is the idea that we tend to even out towards the average over time, similar to the law of averages.

When a pilot had an extraordinary day at flight school, they were rewarded for their outstanding performance.

Whether it was luck, extra motivation, or some external factor, they performed well above their typical baseline.

Chances are, the next day, they'll be closer to their "normal" performance—but compared to their previous stellar showing, it actually appears they performed worse.

Similarly, when a pilot performed poorly and was punished, they likely just had an off day and would bounce back the next (regardless of the punishment.)

We see instances of tending toward normality today, right in front of our eyes.

The famous “Sports Illustrated Jinx" is when an athlete typically has an under-performing year after being on the cover of the Sports Illustrated magazine.

Some say it's due to over-confidence, while others say it's because of extra pressure.

However, it's much more likely the player had a phenomenal outing the previous year (usually a career-high performance), which led them to be selected for the cover of the magazine—and then they returned to normalcy the following year.

Calling it a "jinx" is a causal story, created as an explanation for the underperformance, when in reality, they were just regressing towards the mean.

Was it raw talent, or dumb luck?

Kahneman defines success as the following two equations:

Warren Buffet understands these equations well.

He even said that he was lucky to be born at the time and place he was—if he were born into a nomadic tribe in an African desert, he probably wouldn't be a billionaire today.

Luck is fickle—it's hard for those athletes to attain the same levels of luck in back-to-back years, regardless of their skill level.

Here's another example of how luck contributes to success:

Kahneman and his research partner Amos Tversky were listening to the announcers at the Winter Olympics discussing the ski jump, which consisted of two consecutive jumps.

Kahneman heard the following conversation during the event:

This is yet another causal story, invented to explain the changes in performance after the first jump.

Maybe if you hooked up a heart rate monitor to each jumper, you'd see a change in stress levels that correlates jump performance and heart rate.

But it's much more likely that regression to the mean is a mathematically inevitable consequence of luck playing a role in the outcome of each first jump.

Understanding the game.

Now, let's look at the department store exercise again.

Now that you understand regression to the mean, you know that a 10% overall increase does not mean each store will increase its revenue by 10%.

The stores that had less-than-expected sales the previous year (Stores A, D, and E) will likely have >10% increase, while the stores that over-performed (Stores B and C) will have under 10% growth (or even go negative!)

So while the overall average might still increase, Store C, for example, might regress towards the average and actually be closer to $100,000, whereas Store E will likely increase its sales.

Here's how you can apply this concept to your life starting today:

Whether it’s writing, poker, or life itself, you’re bound to have downswings.

Maybe a piece of content underperforms.

Maybe you have a sh*tty day.

But next time you have one of these days, remember the concept of regression to the mean.

Good days usually follow.

On the flip side, learn to cherish your great days.

Most days will be average, so take advantage of the best ones when they come.

So many people share their wins online—and while that’s great, it makes you forget that no one wins 24/7. We’re human and destined to make mistakes.

Remember this, and you’ll start to see that our “average” days (and even our worst days) are what allow us to appreciate the best times of our lives.

Quote of the week

Thanks for reading!

If you have any questions, hit me up on 𝕏 at @sam_starkman, or feel free to reply to this email!

— Sam