Modern Poker Theory

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A book that discusses the basics of modern poker theory by online poker professional Michael Acevedo

Since 2000, the game of poker has evolved so much that we have new theories being laid down for the game! The Money Maker effect certainly quadrupled the popularity of the game in 2003, followed by the explosion of online poker that only made the game more accessible to everyone.

During its yesteryears, a basic understanding of poker would see money flowing in. However, as more and more people gained access to the game, the chances of winning was no sure-shot and hence players had to up their game with advanced strategies.

The Game Theory Optimal strategy was christened at this juncture and it steadily made its way to the masses. In 2019, poker pro-Michael Acevedo attempted breaking down these theories into relatable nuggets for those who had never heard of this theory.

What makes Michael’s read different? For starters, he is a former mathematician and if that’s not validation enough, he was also part of the team that developed one of the most advanced GTO solvers on the planet.  In his interviews he explains, in the poker world, GTO is synonymous with the mathematical concept of Nash Equilibrium. The easiest way to think of GTO is that it is a strategy that cannot be beaten. So if all players at the table played GTO, they would break-even and the only winner would be the casino due to the rake.

He further elucidates that unfortunately, no one can play perfect GTO. The reason being, the full solution of the game hasn’t been found yet and might never be found due to its complexity and secondly because it is very difficult to always play in such a balanced way. While computers can achieve it by playing every single combo on its range with mathematical precision, it’s impossible for humans too.

Back in the day, most poker players played exploitable styles without paying much heed to their own leaks. But as the average pool of players became more skilled, the ratio of good to bad players is constantly increased. This lead to smaller edges because they were trying to exploit us at the same time as we are trying to exploit them and we no longer have the luxury of being able to ignore our own game.

 

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