Poker and the Psychology of Uncertainty

Poker and the Psychology of Uncertainty

“You are going to be a gambler?”

That’s my grandmother Baba Anya speaking. My last living grandparent. I’ve come to Boston for a family visit, nearly bouncing with excitement at my new project, and she is not impressed. To call her lukewarm would be the understatement of the hour. She has a way of setting her jaw that makes it jut out like it’s about to slice through stone. The chiseled expression of a conquering hero atop a pedestaled horse. A conquering hero—or an angry general. I can feel the full brunt of grandmotherly disappointment gather on my shoulders. She has almost (though not quite) come to forgive me for not wanting kids after over a decade of my persistent explanations, but this—this is a new low. If you think you know the kind of disappointment a five-foot-some-odd 92-year-old is capable of, think again. She was a Soviet-era schoolteacher. She’s had more practice than an army drill sergeant.

She shakes her head.

Courtesy of Penguin Press

Excerpted from The Biggest Bluff: How I Learned to Pay Attention, Master Myself, and Win by Maria Konnikova. Buy on Amazon.

“Masha,” she says—my Russian nickname. “Masha.” The word is laden with so much sadness, so much regret for the life I’m about to throw away. In a single word, she has managed to convey that I’m on the brink of ruin, about to make a decision so momentously bad that it is beyond comprehension. A Harvard education and this, this, is what I’m choosing to do?

“Masha,” she repeats. “You are going to be a gambler?”

My grandmother’s reaction may be extreme—nothing is quite as personal as your grandchildren heading out to ruin on your watch; you have to throw your body in the breach—but it is far from atypical. In the coming months, I’ll be accused of being responsible for a society-wide “sin slide” for advocating for poker as a teaching tool. I’ll be called a moral degenerate by strangers. A group of highly intelligent people at a retreat will tell me playing poker is all well and good, but how do I feel about encouraging people—children even!—to lie?

The world of poker is laden with misconceptions. And first among them is the very one I’m seeing from a stricken Baba Anya: equating poker with gambling. To my mind, the journey was well motivated: Of course people would understand that poker was an important way to learn about decisionmaking. I mean, think of John von Neumann! One of the great polymaths of the 20th century, father of the computer, one of the inventors of the hydrogen bomb, the creator of game theory. And a poker player! Not just a poker player, but someone for whom poker inspired brilliant insights into human decisionmaking, someone who considered it the ultimate game for approximating the strategic challenges of life. Let’s get to the tables! But looking at Baba Anya, I realize that the battle for support—and the justification for poker as not just a learning tool, but as one of the best tools there is for making decisions that have nothing to do with the game itself—is going to take a bit more fighting. I’m going to be explaining this over and over, so I may as well get it right.

Poker, to the untrained eye, is easy. Just like everyone who meets me seems to have “a book in them,” which they’ll write just as soon as they get a chance, so everyone who meets my coach, Erik Seidel—one of the most legendary poker players in the world—thinks they are just a hop away from becoming a poker pro or, at the very least, a badass poker bro. Most of us underestimate the skill involved. It just seems so simple: get good cards and rake in the dough. Or bluff everyone blind and rake in the dough once more. Either way, you’re raking it in.

And poker does have an element of chance, to be sure—but what doesn’t? Are poker professionals “gamblers” any more than the man signing away his life on a professional football contract, who may or may not be injured the next week, or find himself summarily dropped from the team in a year because he failed to live up to his promise? We judge the poker player for gambling; we respect the stockbroker for doing the same thing with far less information. In some ways, poker players gamble less than most. After all, even if they lose an arm, they can still play.

But the misperception is ingrained in the popular mind for one simple reason. Unlike, say, Go or chess, poker involves betting. And betting involves money. And as soon as that enters the picture, you might as well be playing craps or baccarat—games that truly are gambling. And so I tell my grandmother the words that I’ve come to repeat so often they are like my own private mantra: In poker, you can win with the worst hand and you can lose with the best hand. In every other game in a casino—and in games of perfect information like chess and Go—you simply must have the best of it to win. No other way is possible. And that, in a nutshell, is why poker is a skilled endeavor rather than a gambling one.

Imagine two players at a table. The cards are dealt. Each player must look at her cards and decide whether or not the cards on their own are good enough to bet. If she wishes to play, she must at minimum “call” the big blind—that is, place as much into the pot as the highest bet that already exists. She may also choose to fold (throw out her cards and sit this hand out) or raise (bet more than the big blind). But who knows what factors she’s using to make her decision? Maybe she has a premium hand. Maybe she has a mediocre hand but thinks she can outplay her opponent and so chooses to engage anyway. Maybe she has observed that the other player views her as conservative because she doesn’t play many hands, and she’s taking advantage of that image by opening up with worse cards than normal. Or maybe she’s just bored out of her mind. Her reasoning, like her cards, is known only to her.

The other player observes the action and reacts accordingly: If she bets big, she may have a great hand—or be bluffing with a bad one. If she simply calls, is it because her hand is mediocre or because she’s a generally passive player or because she wants to do what’s known as “slow playing”—masking an excellent hand by playing it in a restrained fashion, as Johnny Chan did in that 1988 World Series Of Poker matchup with Erik Seidel? Each decision throws off signals, and the good player must learn to read them. It’s a constant back-and-forth interpretive dance: How do I react to you? How do you react to me? More often than not, it’s not the best hand that wins. It’s the best player. This nuance, this back-and-forth, this is why von Neumann saw the answer to military strategy in the cards. Not because everyone is a gambler, but because to be a winning player, you have to have superior skill, in a very human sense.

Indeed, when the economist Ingo Fiedler analyzed hundreds of thousands of hands played on several online poker sites over a six-month period, he found that the actual best hand won, on average, only 12 percent of the time, and less than a third of hands went to showdown (meaning that players were skillful enough to persuade others to let go of their cards prior to the end of the hand). In mid-stakes games, with blinds of 1/ 2 and 5/10—that is, where the blind bets two players are forced to pay each round to start the action are $1 and $2, or $5 and $10, respectively—there were some players who were consistent winners, and as stakes went to nosebleed, 50/100 and up, the variability in skill went down significantly. That is, the higher the amount of money for which people played, the greater their actual skill edge. When Chicago economists Steven Levitt and Thomas Miles looked at live play and compared the ROI, or return on investment, for two groups of players at the 2010 WSOP, they found that recreational players lost, on average, over 15 percent of their buy-ins (roughly $400), while professionals won over 30 percent (roughly $1,200). They write, “The observed differences in ROIs are highly statistically significant and far larger in magnitude than those observed in financial markets where fees charged by the money managers viewed as being most talented can run as high as 3 percent of assets under management and 30 percent of annual returns.” Success in poker, in other words, implies far more skill than does success in that far more respectable profession, investing.

Of course, the rationale goes much deeper. Betting—that bête noire that seems to be such a stumbling block for even rational minds when you try to explain the skilled nature of poker—is actually at the heart of what makes it superior to almost any other game of skill: Betting on uncertainty is one of the best ways of understanding it. And it is one of the best ways of conquering the pitfalls of our decision processes in just about any endeavor. It doesn’t take a gambler to understand why. In his Critique of Pure Reason, the German philosopher Immanuel Kant proposes betting as an antidote to one of the great ills of society: false confidence bred from an ignorance of the probabilistic nature of the world, from a desire to see black and white where we should rightly see gray. From a misplaced faith in certainty, the fact that to our minds, 99 percent, even 90 percent, basically means 100 percent—even though it doesn’t, not really. Kant offers the example of a doctor asked to make a diagnosis. The doctor reaches a verdict on the patient’s malady to the best of his knowledge—but that conclusion isn’t necessarily correct. But what if he had to bet on it? With something real at stake, he has to reevaluate just how sure of a sure thing his opinion really is.

In poker, this certainty gauge is a built-in feature of the game. How sure are you that you hold the best hand? How sure are you that your opponent will fold the best hand if you’re running a bluff? I think she’s bluffing or I think I’m good here or I think he’s weak as an argument doesn’t quite cut it when money is on the line. Your rationale has to be far stronger than that. You begin with the basics: pot odds. How much money do I need to put in, in order to win the pot? And is that amount justified based on the cards I hold and the cards on the board?

Back before my first-ever day playing poker, when I had only the vaguest notion of what the game entailed, I held a somewhat bizarre misconception: I thought that a deck held 54 cards. I proudly told Erik as much during our first meeting, only to be met with a look of such incredulity that I realized I’d strayed far afield indeed. This isn’t just a funny anecdote (though it’s that, too). If you don’t know the number of cards, you cannot possibly calculate your correct strategy. How do you know how many outs you have—that is, how many cards can conspire to give you the best of it—even if you have the worst of it now? And if you don’t know that, how do you know whether the price you are paying is justifiable? Myriad concepts stem from this one simple element. Given the size of your opponent’s bet, what is the minimum amount of time you have to call in order to avoid being taken advantage of (the minimum defense frequency)? Fold too often and your opponent can bluff with impunity. Call too often and you go broke. And on the flip side, how much—and how often—do you yourself choose to bet? The bigger you bet, the more your opponent risks—but the more you risk too. Bet small and you can bet more often; but know that your opponent, too, will need to stick around more often to see the next card, to avoid being exploited in turn.

Now take it one step further. What cards do you hold? How do they affect the possible hands your opponent holds, or doesn’t hold? If I have a card, it means you don’t have it. And it means you likely don’t have the combinations of cards that would include it. (This is the so-called blocker effect.)

I remember another misconception that needed correcting early on in my poker days: I’d heard that holding suited cards only added a 2 percent advantage to your position versus holding the same two cards but of the unsuited variety. And boy was I proud of that knowledge. Two percent was nothing! It didn’t matter. How wrong I was. Very quickly, I learned just what 2 percent feels like—and how powerful it is. Two percent is a hell of a lot. If I can gain a 2 percent edge over you, I’m on cloud nine. There is a chasm of difference between each percentage point—and that chasm plays out in real time, as you find yourself a bigger winner or loser, depending on which end of the stick you hold.

The betting in poker forces you to pay attention. It forces you to question your thought process. It forces you to recalibrate and rethink, if you want to stay solvent. If you keep following your hunches instead of the mathematics of the thing, you’re doomed. Sure, you might get lucky a time or two. But eventually, variance will catch up with you. If you keep calling when the odds are against you, if you keep betting when the odds of a fold are slim, that is money you will never reclaim.

Of course, there’s quite a chasm between betting on your own opinions and judging someone else for theirs. When we err, we are much more tolerant than when we think someone else has gone astray. Think of the 2016 presidential election. Every media source had polls showing Hillary Clinton winning—and every media source was wrong. No one was on the receiving end of the subsequent ire more than Nate Silver. He had done such an accurate job forecasting past elections that he was practically pilloried for being so “wrong” this time around. But what exactly did Silver say? In his final poll, on November 8, 2016, he gave Clinton a 71 percent chance of winning—and Trump a 29 percent chance. Twenty-nine percent. That’s a whole lot of percent. That’s nearly a third. And yet most people saw the 71 and read it as certain. The complexity of the alternative is just too taxing to take into account every time we make a judgment. To the vast majority, 71 is synonymous with 100. Clinton was winning.

But what if you had to bet, given Silver’s estimates? Would you bet as much on a 71 percent certainty as you would on 100 percent? Or would you then realize that there was a more-than-notable margin of error? It turns out that the odds of Trump winning are roughly the same as the odds of flopping a pair in hold’em—and you only have to play once or twice to realize that the odds of flopping a pair are a far cry from zero.

Nate Silver is a poker player. In fact, once upon a time, he made quite a tidy living playing online. And poker has taught him something fundamental about the nature of the world that most of us simply never bother to grasp. Poker is such a powerful window into probabilistic thinking not in spite of, but because of, the betting involved: The betting in poker isn’t incidental. It’s integral to the learning process. Our minds learn when we have a stake, a real stake, in the outcome of our learning. If I am wrong but I don’t see an immediate, tangible result, I have no need to question my experience. If my wrongness compounds into tens, hundreds, thousands of dollars in my opponents’ pockets: Well, all of a sudden I might pause and reconsider. It’s why kids learn so much better—and remember what they’ve learned—if they know exactly how or when they’ll apply the knowledge. This is the partner element to learning probabilities from experience: Not only do we understand what 29 percent feels like, we now retain that knowledge because if we don’t learn, it hurts us. If we keep betting the wrong amount, we will be punished. If we keep saying “I think I’m good here” without quantifying how often we’re actually good, we’ll lose all our money.

But in life, we normally do just that without a single thought. Why did I buy that stock? Another investor said it was good over lunch. Why did I sell that? Well, he shorted that one and that sounds right to me. We react emotionally rather than looking at the statistics: traders sell winning stocks to lock in the wins—it feels good, even though the numbers say that winners continue to go up in the short term; they hold on to losers to avoid locking in the losses—that would feel bad, even though the numbers say you should cut and run. In fact, numerous studies show that professional investors have a remarkable ability to ignore statistical information for their own gut and intuition—and that they’d often be better served not trading at all as a result.

It’s a difficult lesson to internalize outside the poker table. Even people who seem like they suffer consequences, like stock traders, are often loath to admit that they were wrong in their certainties. Because the world is much messier than the poker table, it’s far easier to blame something else. It’s easy to have an illusion of skill when you’re not immediately called out on it through feedback. Poker rids you of the habit in a way nothing else quite does—and in so doing, it improves decisions completely unrelated to the game itself.

When I’d just started dating my husband, he would often fact-check me mid-conversation. I did in the past have a habit of investing my statements with perhaps a bit more certainty than they warranted. “Are you sure?” he’d ask, endearingly. “I think I might want to check that.” And he would pull out his phone or a book to do just that. I got better, but I could never quite kick it. It wasn’t until I entered the world of poker that the process really sank in. I hadn’t been playing long before I found myself saying things like “Well, I’m about 75 percent sure.” This was that two percent edge made real. I’d realized that I had relied far too much on rounding, on approximating, on figuring, well, it’s close enough, but that probabilities really did merit far greater precision. Think about the weather. When do you bring an umbrella? Is your threshold a thirty percent chance of rain? Forty? Fifty? Sixty-five? It’s likely you have one—and that you realize that the numbers are not one and the same. As I entered the world of serious poker, I’d come to experience the consequences of improper certainty a few too many times in my bank account, and knew that I had been the only one to blame for my bad play.

That personal accountability, without the possibility of deflecting onto someone else, is key. One specific class of lawyer, in fact, actually fares far better at probabilistic thinking than financial professionals whose jobs are more explicitly tied to probabilities: the lawyers who take cases for a percentage of the eventual settlement. You have a far higher personal stake in calibrating correctly, and so you learn to do just that. Likewise, meteorologists and horse-race handicappers: their calibration of risk is accurate because they not only deal explicitly in percentages but have immediate feedback on their performance—and no one else to blame if their estimate is incorrect.

Outside the realm of games, accurate probabilistic thinking is a rare skill. Dan Harrington, one of the greats of the poker world, left poker some years ago to start a real estate investment business that has performed very well. He told me the story of one hire that hadn’t gone according to plan. He’d seemed nice and qualified, but his judgment ended up leaving something to be desired; it wasn’t nearly as sharp as it had seemed during the interview process. There was a key difference between him and other employees: he had a traditional finance background; the others were connections from the poker and backgammon worlds. “My partner said to me, ‘Dan, in the future if we hire a nonprofessional gambler, just give me a swift kick in the ass,’” Dan remembers. “The successful hires understood equity and they understood the decision tree matrix that that involves, and they don’t get involved in it personally. And that comes from gambling. It’s invaluable for life.” They never hired someone who hadn’t spent some time in the world of gaming ever again.

I’d wager it’s no coincidence that the father of probability—the first person who we know of to go beyond a vision of chance as some sort of unknowable goddess, or otherwise in the purview of the supernatural— was a gambler. Girolamo Cardano was a doctor, a mathematician, a philosopher—and he combined that background into a deeper understanding of practical probability than anyone before him. Cardano had little patience for the prevailing divination methods of the day, like astrology.

Trusting in luck as a vague sort of higher power, Cardano realized, was a losing enterprise. It was pointless to try to divine whether there was a god or spirit or other guiding force at play. He offered another way: prediction through probabilities. He remembers the moment he realized he could make certain plays based on specific frequencies being in his favor. He’d lost a lot of money to a man who had lured him into a game with marked cards. In contemplating how to regain his belongings (he’d also lost many of his clothes and personal effects), a more mathematically minded approach came to him.

It just so happens that, in musing on the ways to calculate dice throws and card distributions, Cardano also wrote a description of what many take to be the earliest form of poker, primero. It wasn’t played with a full deck, and the rules of betting were somewhat convoluted, but the essence was similar to the games we have now: some cards private, some in common, and a complex interplay between representing the hand you may or may not have and interpreting the signals of your fellow card players. Primero traveled across Europe, variably termed primiera, la prime, and eventually pochen, a German name derived from the verb “to bluff.” The French took pochen and made it poqué—and soon, the game would morph into a new form.

Cardano lamented one thing, though. Understanding probability wasn’t enough to tame the luck factor. Unless you cheated—and he spent quite some time describing how that would be possible, with crooked dice and marked cards—you had no way of winning consistently. If you want to improve your odds, understand probabilities; if you want a sure thing, rig the deck.

Poker isn’t just about calibrating the strength of your beliefs. It’s also about becoming comfortable with the fact that there’s no such thing as a sure thing—ever. You will never have all the information you want, and you will have to act all the same. Leave your certainty at the door.

Baba Anya is not convinced. Poker may teach you that nothing is certain, but she is still positive I’m going over to the dark side. I realize that nothing I say will change her mind. She waves away all my talk of skill with a dismissive hand. She has more arguments in mind.

“But this isn’t serious,” she says. Skill or no skill, there is one other element of this whole thing that bothers her. “It’s only a game. How can you be serious about a game?” She wants me to be a professor—now that’s serious business. A real job. A skilled job.

Until it isn’t. The more I think about it, the more I start doubting just how much of a gamble- free endeavor it could be. Imagine me going down the academic path. What did I choose to study? Social psychology. Ah, but neuroscience is having a moment. I may have followed my interest, but not the job market. With whom did I study? Good luck to me getting a job in any psychology department where the Big Five personality traits are still big— studied with Walter Mischel, and he and the Big Five are not on speaking terms. What about academic publications? Who might get assigned to review my manuscript— someone with a sympathetic ear or someone who thought my research was so much hogwash? I’m not going to get kicked out of a poker tournament for choosing a style of play that goes counter to the strategy of the bigwigs of the day and may challenge their ascendance. But if I were to go against the head of a department or hiring committee—or even one of the celebrity hotshot professors? Bye- bye, job prospects.

In many ways, poker is the skilled endeavor. The job market is the gamble. How did my job talk go? Where did I go to college? To grad school? Did I rub someone the wrong way in an interview? These details, all subject to a big dose of chance, can make or break me. At the table, I play how I play. And I rise or fall on my own merits.


Adapted from THE BIGGEST BLUFF: How I Learned to Pay Attention, Master Myself, and Win by Maria Konnikova. Copyright © 2020 by Maria Konnikova. Published by arrangement with Penguin Press, an imprint of Penguin Publishing Group, a division of Penguin Random House LLC.

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