At the turn of the millennium, the raw power and potential of the World Wide Web was beginning to come into focus. E-Commerce sites first bloomed in the late-90s, recognizing that there was an untapped market just sitting there with a wallet and without any pants. A small bookseller named Amazon went public in 1997, a small shoe store named Zappos began in 1999, and a small online DVD rental store named Netflix kicked off operations in 1998. These were just three of many.
Of course, no one knew that these companies would become what they became. But there was a widespread fascination with the internet, and professionals everywhere knew that there was a future there.
There was one, slight, tiny, gigantic problem. What these smart and invested investors missed was what about the internet was actually important. Simply existing on the internet wasn’t enough. Simply having a dot-com at the end of your company name wasn’t enough. Profit does not always come after growth.
Eventually, the dot-com bubble popped. The savvy investors and businesspersons who pushed it, the ones with the experience and careers on the line, whiffed hard.
The fascinating part of the Dot-Com Bubble was that investing in these new online companies was the right idea. On May 16, 1997, Amazon’s stock was at $1.67 per share. On May 16, 2017, the stock was at $1587.28 per share. Amazon acquired Zappos in 2009 for $1.2 billion. And Netflix’s stock has risen from $1.21 on May 24, 2002 to $332.61 on May 24, 2018.
Investors just didn’t invest well. They ignored price-earnings ratio and other metrics, even some as essential as profitability. They didn’t ignore all metrics; growth was of paramount important, and the fastest companies often attracted the most investment.
The reasons why this happened were numerous. Investors thought they knew better. They thought there was a new economy on the rise. They were caught up in the moment. They were a part of a massive groupthink. If you were an investor, and you weren’t investing in dot-com companies, what were you even doing?
In baseball, the investors of this metaphor are those with direct experience working in the dirt of the game: players, coaches, managers, front office staff. These are talented humans, smart humans, who, like the dot-com investors, have a personal and professional stake in how well they do their jobs. These are humans who are good at what they do, no; they are the best at what they do.
And sometimes these professionals disagree with the numbers, the statistics, the cold hard math. What are we to do? Who do we deem right?
This isn’t just a baseball problem, although it is often one in today’s sabermetrically-inclined game. It happens in basketball, in football, and in varying fields of economics and commerce. Normally, when given a well-researched and relevant statistic, we believe it. But suddenly, those same statistics wilt when professionals disagree with them. We want to empathize with humans, especially with those who have so much experience.
However, humans happen to be wrong sometimes. Often. Historically, almost always. For instance, when confronted with science and numbers that, hey, maybe the universe doesn’t revolve around us, the powers that be hundreds of years ago disbelieved. They trusted in the professionals of their day, the religious and cultural leaders who couldn’t reconcile their worldview with the numbers.
Heck, when confronted with an overwhelming body of research that says that vaccines are awfully safe and effective, today, a depressingly large portion of Americans choose to not to think so, instead placing their trust in the “professionals” of the matter: their own fear.
But professionals, legitimate or fabricated, can be wrong. Yes, there is a widespread and fundamental misunderstanding of how statistics work and what they mean. However, that’s not the real reason why people fight the comprehension of statistics they don’t like.
Sabermetric arguments are never about the statistics. They are never about the decision process about what goes into the statistic, or about the figures included in the calculations, or the underlying assumptions about what is valuable or even what should or is being measured. Rather, those arguments about baseball statistics are about something more fundamental: that human beings know more than the numbers do. That, despite an obvious human hand in the creation and usage of the statistics, professional opinion takes precedence.
Any cursory glance at human and sports psychology should put a massive ding in that idea, though. A quick Google search shows why the congealed sameness of traditional baseball thinking makes baseball decision makers highly susceptible to groupthink, which negatively impacts decision making and hampers creativity. Another Google search will talk about how we’re susceptible to confirmation bias or emotional reasoning, both methods our brains use to convince ourselves of something we held as true even in the face of clear evidence that it isn’t. And it goes on.
We shouldn’t take every number we see at face value all the time. That kind of trust is unwarranted considering how adept humans are at tricking people with numbers. Rather, we should just be way more cognizant that even professional opinions made by smart and invested people can be wrong. By understanding that, we can come to a more healthy realization of statistics. Maybe Salvador Perez isn’t as good as we’ve thought, for instance—at least, not when you take into account the raw, uncaring pitch frame data. And maybe he is.
Ultimately, humans, even professional ones, make mistakes. Even the smartest aren’t immune. On the other hand, a formula is a formula. It can be improperly applied or wielded incorrectly, but it is what it is. It can’t think for us. But it’s foolish not to consider it.