The Metagame #014: Game Theory Optimal vs. Real Life Strategy

Poker, tic-tac-toe, and Hannah Montana have a lot more in common than you think.

Here’s what’s in store for today:

• Game Theory Optimal Poker

• The Human Element

Read time: 4 minutes

Phil Ivey is widely regarded as one of the greatest poker players of all time, with over $38 million in winnings. His uncanny ability to read opponents and make calculated decisions has earned him the nickname “The Tiger Woods of Poker.”

But even legends aren’t perfect.

Here's a video of him busting out of the $250,000 Super High Roller event at the 2024 World Series of Poker:

Watching Ivey lose is a reminder that perfection is a myth—even for the best in the game. So, what can we learn from this?

In poker, there’s a concept known as Game Theory Optimal (GTO) strategy. GTO represents the mathematically “correct” play in any given situation. It tells you when to raise, when to fold, when to bet, and when to go all-in—all based on probability, statistics, and expected value.

But GTO isn’t exclusive to poker.

It's in chess. It’s in Settlers of Catan. It’s even in tic-tac-toe.

The catch?

GTO assumes your opponents are also playing optimally. This is rarely the case in real-life scenarios.

The Human Element

We humans are imperfect by nature. We have emotions, we make mistakes, and we often deviate from optimal play—sometimes intentionally, sometimes not.

This unpredictability adds a layer of complexity that these pure GTO strategies simply can’t account for.

One of the most valuable skills in poker (or in any social interaction) is the ability to read people. Tells—subtle changes in behavior or demeanor—can provide insights into an opponent’s hand strength (or what they’re thinking in general).

Some tells include:

• Physical Tells: Fidgeting, avoiding eye contact, or changes in breathing.

• Timing Tells: Changes in the speed of play or time spent thinking.

• Betting Patterns: Unusual and unexpected bet sizes.

If They Tell You What Their Hand Is, Do You Still Call?

Imagine you’re playing a hand where the GTO strategy is to fold 50% of the time. If your opponent shows you their cards—a low pair—do you still fold?

With new information, the optimal play shifts.

Now, what if you have a decent hand that GTO strategy says is a good hand to raise? You do so, and then your opponent goes all-in. Based on the way they’ve been playing (and maybe some tells you’ve picked up on), you are confident they have pocket aces—the best starting hand in the game.

Do you still call, even if GTO strategy says it’s a good call?

The human element (your reads on the opponent) provides such an important aspect that an “optimal” strategy simply can’t understand. Sometimes, the “perfect” strategy is no longer perfect for the situation you’re in, and you have to deviate from the standard strategy.

Beyond The Math: Adapting to Real-Life Opponents

No one plays perfectly optimally—not even Phil Ivey.

And that’s perfectly fine.

The beauty of games like poker lies in their mathematical complexity combined with their unpredictable human elements.

While GTO provides a great foundation for making decisions, the ability to adapt is what separates good players from great ones. Some of the best skills you can have to break free from a rigid framework are:

• Observability: Pay attention to peoples’ behaviors and adapt your strategies to new information.

• Flexibility: Be willing to deviate from GTO when circumstances warrant it.

• Intuition: Develop a sixth sense for when people are “playing optimally” or making mistakes.

As the wise Hannah Montana once said, “Nobody’s perfect.”

So the next time you’re at the poker table, negotiating a salary, or even playing a board game with friends, remember: the optimal strategy isn’t one that focuses purely on the “mathematically optimal play,” it’s one that blends statistical insights with human intuition.

Embrace the unpredictability.

That’s where the real game begins.

Quote of the week

Thanks for reading!

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

— Sam