The Biggest Bluff

It was a philosophical query as much as anything else. And I tried to pursue it in the best way I knew how. I went to grad school. I posed the question. I developed some studies. How often are we actually in control, I wondered? And how does the perception of being in control in situations where luck is queen actually play out in our decision making? How do people respond when placed in uncertain situations, with incomplete information?

Over the course of five years, as part of my doctoral research at Columbia, I asked thousands of people to play a simulated stock market game, under time pressure. They would have to “invest” a certain amount of their money—real money; how they performed would translate directly into how much they were paid, and the range was vast, from one dollar to over seventy-five dollars—in one of two stocks, or in a bond, and do so over hundreds of trials. The bond always paid safely, and it always paid little—one dollar, to be exact. The stocks, however, mimicked the behavior of actual stocks in the market. They might earn you far more money—up to ten dollars a turn. But they could also be losers, wiping out ten dollars from your gains in the click of a mouse. In each round of the game, the two stocks (creatively titled “A” and “B”) were randomly assigned to be either “good” or “bad.” Choose the good stock, and you’d have a 50 percent chance of getting ten dollars, a quarter chance of making nothing, and a quarter chance of losing ten dollars. Choose the bad one, and your winning chances fell to 25 percent, while your losing chances jumped to 50. Here’s what I was interested in: What strategy would people follow in their choices—and how quickly would they learn which of the stocks was the winning one? (Optimal investment strategy would have you quickly gravitate to the good stock, as your overall earnings would be highest despite the intermittent losses.)

What I found was something completely unexpected. Over and over, people would overestimate the degree of control they had over events—smart people, people who excelled at many things, people who should have known better. Not only would they decide ahead of time how they were going to divide their investments, but they would decide based on incredibly limited information which stock was “good” and stick to their guns—even as they started losing money. The more they overestimated their own skill relative to luck, the less they learned from what the environment was trying to tell them, and the worse their decisions became: the participants grew increasingly less likely to switch to winning stocks, instead doubling down on losers or gravitating entirely toward bonds. Because they thought they knew more than they did, they ignored any signs to the contrary—especially when, as inevitably happens in real stock markets, winners became losers and vice versa. In other words, the illusion of control is what prevented real control over the game from emerging—and before long, the quality of people’s decisions deteriorated. They did what worked in the past, or what they had decided would work—and failed to grasp that the circumstances had shifted so that a previously successful strategy was no longer so. People failed to see what the world was telling them when that message wasn’t one they wanted to hear. They liked being the rulers of their environment. When the environment knew more than they did—well, that was no good at all. Here was the cruel truth: we humans too often think ourselves in firm control when we are really playing by the rules of chance.

The problem stayed with me. But what was its solution? How could you use that theoretical knowledge to make better choices, practically speaking?

It’s a tough ask, for one main reason: the equation of luck and skill is, at its heart, probabilistic. And a basic shortcoming of our neural wiring is that we can’t quite grasp probabilities. Statistics are completely counterintuitive: our brains are simply not cut out, evolutionarily, to understand that inherent uncertainty. There were no numbers or calculations in our early environment—just personal experience and anecdote. We didn’t learn to deal with information presented in an abstract fashion, such as tigers are incredibly rare in this part of the country, and you have a 2 percent chance of encountering one, and an even lower chance of being attacked; we learned instead to deal with brute emotions such as last night there was a tiger here and it looked pretty damn scary.

Millennia later, the shortcoming persists. It’s called the description-experience gap. In study after study, people fail to internalize numeric rules, making decisions based on things like “gut feeling” and “intuition” and “what feels right” rather than based on the data they are shown. We need to train ourselves to see the world in a probabilistic light—and even then, we often ignore the numbers in favor of our own experience. We believe what we want to see, not what research shows. Take something that’s on plenty of minds in recent times: disaster preparedness. What do you do to prepare for the extreme weather events—hurricanes, floods, earthquakes—that are increasing in frequency as the earth warms? What about nuclear war or a terrorist attack—do you need to worry about that? There are statistics to help you reach an answer, like whether you need special insurance for your home or if you should even be buying property in certain areas—just like there are probability charts that inform you of the risk of your being the victim of terrorism as opposed to, say, slipping in your shower and suffering a fatal or debilitating fall. But here’s what psychologists find, over and over: you can show people all the charts you want, but that won’t change their perceptions of the risks or their resulting decisions. What will change their minds? Going through an event themselves, or knowing someone who has. If you were in New York City during Hurricane Sandy, for instance, you are far more likely to purchase flood insurance. If you weren’t, you may invest in a beachfront property in Malibu even though the numbers say your beach will be gone soon, and your house along with it. If you lived through 9/11, your fear of terrorism will be vastly overblown. In all cases, the reaction isn’t in line with the statistics. Not every house in New York needs flood insurance—you’ve overcompensated because you went through a bad experience. Beachfront properties are an awful long-term investment—you’ve undercompensated because the statistics haven’t ever affected you personally. Your likelihood of slipping in a shower is orders of magnitude larger than your likelihood of being in a terrorist attack—but just try convincing someone of that, especially if they knew someone who died in the Twin Towers.

Our experiences trump everything else, but mostly, those experiences are incredibly skewed: they teach us, but they don’t teach us well. It’s why disentangling chance from skill is so difficult in everyday decisions: it’s a statistical undertaking, and one we are not normally equipped to deal with. Which brings me to poker: Used in the right way, experience can be a powerful ally in helping to understand probabilistic scenarios. The experience just can’t be a one-off, haphazard event. It has to be a systematic learning process—much like the environment you encounter at the table. And the correct systematic learning process can help you unravel chance from everything else in a way that no amount of cramming numbers or studying theory ever will.

Several years after I left academia, the problem of skill versus chance became more personally pressing. 2015 was not a good year for the Konnikova clan. The first week of January, my mother—my role model in most every way—lost her job of almost twenty years, summarily downsized in a private equity acquisition. Her coworkers cried. Her boss cried. They petitioned to hire her back. She was good at what she did: computer programming. I thought she’d be back on her feet in no time. Instead, she hit upon a harsh reality of Silicon Valley: ageism is alive and thriving, especially for women. She’s in her fifties—too old for the young set, not old enough to retire. A year later, she was still jobless. Life is so unfair was my first thought—but if there’s anything Mom taught me, it’s that life has no concept of fairness. It’s just tough luck. Deal with it.

A few months later, my vivacious, healthy, living‑on‑her-own grandmother slipped in the night. The edge of a metal bed frame. Hard linoleum floor. No extra pair of ears to hear anything amiss. The neighbors found her in the morning, alerted by a light that shouldn’t have been turned on. Two days later, she was dead. We never said goodbye. I don’t even remember our last conversation—it was that banal, the same phrases, the same intonations, no, nothing new to report on either end. She probably asked when the first copies of my new book would be ready. She wouldn’t be able to read it—she’d have to wait for the Russian translation—but she couldn’t wait to hold it. It’s a safe bet that question came up. She asked me that every time we spoke. And every time, I’d berate her: stop asking; I’ll let you know when. I’d grow frustrated. She’d raise her voice and inform me that she was never going to ask me anything about anything ever again. I should have been kinder. But hindsight always sees most clearly. To the end, she signed off her voicemails to me with a short phrase: “This is Grandma.” As if there could be some confusion. And to the end, I never called back quite quickly enough. She’d been through World War II, survived Stalin, Khrushchev, Gorbachev, and was defeated by a slippery floor and one misplaced foot. Unfair. Or rather, unlucky. One surer step and she’d still be here.

My husband lost his job next. The startup he’d joined failed to start up as planned, and with that, I momentarily found myself in a position I hadn’t been in for years: supporting my family on a freelance writer’s income. We left our beautiful West Village apartment. We changed our habits. We did our best to adjust. And on top of it all, I found my health suddenly failing. I’d recently been diagnosed with a bizarre autoimmune condition. No one knew quite what it was, but my hormone levels had declared insanity, and I was suddenly allergic to just about everything. Sometimes, I couldn’t even leave the apartment: my skin broke out in hives whenever anything touched it, and it was winter outside. I sat huddled with my laptop, draped in an old, loose T‑shirt, hoping for the best. I went from expert to expert, steroid regime to steroid regime, only to be told the same thing: idiopathic. Doctor speak for “We don’t have a clue.” That idiopathy (root word: idiocy) was expensive. Unfair. Bum luck. But was it? Maybe it had been my fault for failing to listen to my mother and sneaking out to play on the balcony so many years ago. I was born in Russia, after all, and was there for Chernobyl; her admonition to stay inside had its reasons. Maybe my two-year-old self was to blame. I sat reading James Salter—“We cannot imagine these diseases, they are called idiopathic, spontaneous in origin, but we know instinctively there must be something more, some invisible weakness they are exploiting. It is impossible to think they fall at random, it is unbearable to think it”—and I found myself nodding in recognition. Whether it was pure chance or not, it sucked.

It’s a familiar pattern of thought. Luck surrounds us, everywhere—from something as mundane as walking to work and getting there safely to the other extreme, like surviving a war or a terrorist attack when others mere inches away weren’t as fortunate. But we only notice it when things don’t go our way. We don’t often question the role of chance in the moments it protects us from others and ourselves. When chance is on our side, we disregard it: it is invisible. But when it breaks against us, we wake to its power. We begin to reason about its whys and hows.

Some of us find comfort in pure numbers. We call it what it is: pure, high-school-math chance. As Sir Ronald Aylmer Fisher, a twentieth-century statistician and geneticist, pointed out in 1966, “The ‘one chance in a million’ will undoubtedly occur with no less and no more than its appropriate frequency, however surprised we may be that it should occur to us.” Consider the 7.5 billion people who currently make up the world’s population and you can be sure that the highly improbable is happening with regular frequency. The “one chance in a million” takes place every second. Someone close to you will die in a freak accident. Someone will lose a job. Someone will fall ill with a mysterious disease. Someone will win the lottery. It is probability, it is pure statistics, and it is part of life, neither good nor bad. If bizarre coincidences and one-off events didn’t happen—well, that would be the truly remarkable thing.

Some of us imbue probability with emotion. It becomes luck: chance that has suddenly acquired a valence, positive or negative, fortuitous or unfortunate. Good or bad luck. A lucky or unlucky break. Some of us invest luck with meaning, direction, and intent. It becomes fate, karma, kismet—chance with an agenda. It was meant to be. Some even go a step further: predestination. It was always meant to be, and any sense of control or free will we may think we have is pure illusion.

So how exactly does poker fit into all this? Until I began this journey, I’d never been a card player. I’d never played poker in my life. I’d never even seen a real game. Poker was a nonentity in my mind. But faced with event after event breaking the wrong way, I did what I always do when I try to understand something. I read. Anything that could help shed light on what was happening, that would allow me to regain some semblance of control. And in my reading frenzy, I came across John von Neumann’s Theory of Games and Economic Behavior.

Von Neumann was one of the greatest mathematical and strategic minds of the twentieth century: he invented that little machine we all carry around with us, the computer (back then, it wasn’t so little), crafted the technology behind the hydrogen bomb, and is the father of game theory. Theory of Games is his foundational text, and here’s what I learned within its pages: the entire theory was inspired by a single game—poker. “Real life consists of bluffing, of little tactics of deception, of asking yourself what is the other man going to think I mean to do,” von Neumann wrote. “And that is what games are about in my theory.”

Von Neumann did not care for most card games. They were, he thought, as boring as the people who wasted their lives playing them, trying to coax mastery—impossibly—out of pure chance. Games of pure chance, though, were to his mind not much worse than those at the opposite end: games like chess, where all the information could theoretically be gleaned, where every move could be mathematically accounted for in advance. There was one exception to his distrust of gaming: poker. He loved it. To him, it represented that ineffable balance between skill and chance that governs life—enough skill to make playing worthwhile, enough chance that the challenge was there for the taking. He was a god-awful player by every account, but that never stopped him. Poker was the ultimate puzzle: he wanted to understand it, to unravel it—to, in the end, beat it. If he could figure out how to disentangle the chance from the skill, how to maximize the role of the latter and learn to minimize the malice of the former, he believed he would hold the solution to some of life’s greatest decision challenges.

For poker, unlike quite any other game, mirrors life. It isn’t the roulette wheel of pure chance, nor is it the chess of mathematical elegance and perfect information. Like the world we inhabit, it consists of an inextricable joining of the two. Poker stands at the fulcrum that balances two oppositional forces in our lives—chance and control. Anyone can get lucky—or unlucky—at a single hand, a single game, a single tournament. One turn and you’re on top of the world—another, you are cast out, no matter your skill, training, preparation, aptitude. In the end, though, luck is a short-term friend or foe. Skill shines through over the longer time horizon.

Poker has a mathematical foundation, but with a dose of human intention, interaction, psychology—nuance, deception, little tricks that don’t quite reflect reality but help you gain an edge over others. Humans aren’t rational. Information isn’t open to all. There are no “rules” of behavior, only norms and suggestions—and within certain broad constraints, anyone might break those norms at any point. The games that interested von Neumann are the ones that, like life, can’t ever be mapped cleanly. Real life is based on making the best decisions you can from information that can never be complete: you never know someone else’s mind, just like you can never know any poker hand but your own. Real life is not just about modeling the mathematically optimal decisions. It’s about discerning the hidden, the uniquely human. It’s about realizing that no amount of formal modeling will ever be able to capture the vagaries and surprises of human nature.

When I read von Neumann’s rationale for choosing poker above all else to explore the most important strategic decisions in the world—he was advising the US military, after all—something clicked. Poker wasn’t theoretical, the way the research I’d done and the studies I’d run had been. Poker was practical. Poker was experiential. Poker embodied the way the human mind learns best, and it wasn’t a one-off event: it was a systematic process. It was, in other words, perfect for what I had in mind.

Poker isn’t a homogeneous game; there are multiple varieties of play, with names like Stud, Omaha, Razz, Badugi, and HORSE. Each has its own unique set of rules, but in any style of poker, the basic parameters are essentially the same: Some cards are dealt faceup, visible to all—these are the community cards—and some facedown, so that only the person to whom they are dealt can see them. You make bets based on how strong your hand is and how strong you think others’ hands are. Because the only other cards you know for sure are your own, you are in a game of incomplete information: you must make the best decision you can, given the little you know. The last player left standing at the end of the final round of betting takes the pot, or the sum of money that has been bet up to now.

But the style I’ve chosen to pursue is one particular variant of the game, which happens to be the most popular. No Limit Texas Hold’em. How no limit hold’em differs from other forms of poker is twofold. The first is in the precise amount of information that is held in common versus in private. Each player is dealt two cards facedown: the hole cards. This is privileged information. I can try to guess what you have based on how you act, but I can’t know for sure. The only information I’ll have is your betting patterns once the public information—the cards dealt to the middle of the table, faceup—is known. In hold’em, there are three stages of dealing the middle cards: the first three cards, called the “flop,” are dealt at the same time; the fourth card, the “turn,” is dealt after another round of betting; and the fifth, the “river,” is dealt after yet another round. In total, then, you have two cards in your hand, known only to you, five cards in the middle, known to everyone, and four “streets,” or betting rounds, in which to make your best guess as to how the cards you can’t see stack up against your own.

Where some forms of poker assume too many unknown variables (one form gives each player five cards facedown, for instance), making skill less of a factor, and others leave too little unknown (one hole card), reducing the guesswork too greatly, the amount of incomplete information in Texas hold’em creates a particularly useful balance between skill and chance. Two hole cards is just about as practical a ratio as you can have: enough unknown to make the game a good simulation of life, but not so much that it becomes a total crapshoot.

The second thing that distinguishes this particular playing style is the concept of no limit—von Neumann’s own preferred style. “The power of the pure bluff is restricted in a game of limit,” explains Amarillo Slim, one of the best poker players of his day, who, in 1972, won the third ever WSOP title. When there’s a limit, it means that the exact amount you bet has a ceiling on it. Sometimes, the ceiling is set by the house rules—an arbitrary number above which you can’t go. Sometimes, in what’s known as “pot limit,” it’s set by the total amount in play: your bet cannot exceed what’s in the pot. Either way, your range of action is artificially restricted. In no limit, you can bet everything you have, at any point. You can “shove” or “jam”—that is, make an all‑in bet, placing every chip you have into the pot. And that’s when the game gets really interesting. Limit is for people who have “the guts of an earthworm or make [their] living as an accountant,” Slim says. “If you can’t ‘move in’ on someone—meaning bet everything you’ve got in front of you—then it’s not real poker.”

And that’s what makes this game a particularly strong metaphor for our daily decision making. Because in life, there is never a limit: there’s no external restriction to betting everything you have on any given decision. What’s to stop you from risking all your money, your reputation, your heart, even your life at any point you choose? Nothing. There are no rules, at the end of the day, save some internal calculus that only you are privy to. And everyone around you has to know that when they make their decisions: knowing you can go all the way, how much should they themselves invest? It’s the endless game of brinkmanship, popularized by another giant of game theory, the Nobel-winning economist Thomas Schelling, that plays out everywhere in our lives. Who will say “I love you” first, moving “all in” in the relationship—and if you say it, will you be left out, so to speak? Who will walk away from the business negotiation? Who will wage war? The ability to go all in—and the knowledge that going all in is an option for everyone around us—is the crucial variable that makes so many decisions so very difficult.

And, of course, there’s the emotional element. Be it at the poker table or out in the real world, there is no risk quite like the risk of the shove: at its best, it can let you “double through”—that is, win the maximum amount possible, doubling your stack—but it can also end your game. You can emerge with the deal of a lifetime, or a life partner—or you can find yourself bankrupt or emotionally devastated. Like life, no limit poker is high risk and high reward. It’s no coincidence that the WSOP champion is determined by No Limit Texas Hold’em. And it’s no coincidence that that is the style of play I have chosen to learn. If you’re trying to make the best decisions, you might as well go with the best proxy.

Once you’ve chosen your game, there’s one more choice to make: cash or tournament? In a cash game, every chip has a cash value. You buy in to a game for a certain amount, say, $100, and you get that exact amount in chips placed in front of you. At any point, you can choose to add more money to your stack by paying the requisite amount in cash. At any point, you can get up and walk away. And if you ever go bust, you can always choose to rebuy and start over for another shot. What’s more, the structure will remain constant. If you bought in to a $1/$2 game—a game where the blinds, or forced bets that you have to post into the pot before seeing your cards, are one dollar for the small blind and two dollars for the big blind—it will always be a $1/$2 game. You won’t turn around and find you’re suddenly forced to pay five dollars when it’s your turn in the big blind.

In a tournament, chips have value only relative to other players’: they are a way of keeping score. A $100 buy‑in might get you ten thousand chips or two hundred; it doesn’t really matter. Everyone gets the same amount, and your goal is to accumulate as many of them as possible, with the eventual winner holding all the chips. If you start losing, that’s too bad; there’s no option to call someone over and pay another $100 for another stack of chips. And once you bust, you’re out of there. You’re playing for your tournament life. As for the blinds, those go up on a predetermined schedule. So, while you might start at 1/2, you will find that in a half hour or forty-five minutes or whatever the structure says, they rise to 2/4, 4/8, and so on. Suddenly, your chips aren’t worth as much as they were and the pressure is on to start winning more pots. Otherwise, in short order you’ll blind out—that is, spend all your chips paying the forced bets, or blinds—and find yourself with nothing.