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In this video you will see how your decisions in a given spot may influence your future situations, and you will learn how to take advantage of that knowledge.
Future Game Simulation (1): Introduction
In this video you will learn how your decisions may influence your future game situation why the ICM is limited when it comes to the future game and what Future Game Simulation is and why you should use it.
By now you should have a general idea on how the chip counts correspond to monetary stack values and how to use this knowledge to make informed decisions. In this lesson you will learn how to tweak the resulting model in line with your reads and how to deal with its inherent limitations. Most of all, however, you will see how your decisions in a given spot may influence your future situations, and you will learn how to take advantage of that knowledge.
As most applications of stack valuation models involve preflop pushing or folding dilemmas, it is further assumed that this is the kind of spot in question. Push or fold decisions in a SNG are usually assessed using the ICM model. The standard procedure is therefore to employ dedicated software, such as HoldemResources Calculator, to calculate Nash calling and pushing ranges based on stack sizes and payout structure. Results encompass the expected value of pushing or calling with every possible holding. Of course, this calculation assumes that your opponents are playing Nash ranges as well. There is a twofold problem resulting from this assumption. Firstly, in most cases at least some of your opponents are either not knowledgeable enough to play close to the Nash solution or have decided to deviate from it for some reason, for example due to assumptions about your game. That could be a relatively minor problem in a cash game, as every deviation from the equilibrium by one of your opponents increases your EV. In a SNG however – and that is the second part of the problem – an opponent playing too loose in certain spots can decrease both his equity as well as yours, effectively transferring it to all the other players at the table. To deal with that, you need to adjust the Nash ranges as best you can, according to your reads. A recalculation in the software with the ranges manually adjusted should provide you with results that are impervious to limitations of the Nash equilibrium part of the model. However, the inherent limitations of the Independent Chip Model itself still influence the calculations. Let’s have a look at them now.
The limitations of the Independent Chip Model can be summarized in a short statement: the model does not take into account what happens in the future. It simply assumes that all the stacks are equally playable and that the finishing order will be determined in unbiased all-in confrontations. This is however not the case, and the playability of the stacks differs depending on numerous factors. That in turn causes the expected ICM values of stacks in the future to diverge from the static calculation based on present stack sizes. Take a look at the factors which influence playability but are not taken into account by a static ICM calculation.
First and foremost, there is the stack setup. Short stack sizes (especially in a low risk premium environment) can have an inherent advantage as deeper stacked players need to employ a different strategy between themselves compared to a single optimal one against a short stack. On the other hand, in higher risk premium environments a big stack is at an advantage as his risk premiums are lower than these of his opponents, which helps to apply pressure effectively. Besides, there are certain stack sizes which are more playable as they offer a broader spectrum of possible moves, such as a raise/fold, open push, or a small 3-bet. Of course, all stacks need to be considered relative to the blinds. Here comes another factor – the blind increases. The first player who faces the newly increased blinds is at a disadvantage and his true EV is lower than otherwise calculated. It is often not possible to foresee the number of hands per blind level, but it is something to have in mind and to influence when possible for one’s own benefit. Then there is position. If the next pay-jump is likely to come very soon, it is much better not to have to pay the blinds until then. It is also better to sit behind the loose, big stacked players and have tight players to act after you. The position relative to the blinds can also determine who is forced to make a move first, which can change EV dramatically, especially in a satellite. Last but not least, there are your reads on players. Is the big stack willing to take advantage of the stack setup by attacking shorter stacks relentlessly, or is he rather the type to ladder up passively by not risking his chip lead? Are the short stacks aggressive and willing to risk their tournament lives if need be, or are they holding onto their “chip and chair”? The more the big stack is capable of applying pressure and short stacks willing to blind down, the more the true stack values deviate from what the ICM dictates. As a matter of fact, in such cases the stack values are closer to the chip chop numbers.
Reads on players and the problem of blind increases are hard to translate into numbers, thus you should address these limitations by manually adjusting the ICM-based Nash ranges. The rest, however, can be accounted for by using a more advanced model called the Future Game Simulation (FGS). What FGS does is simply run a Nash-based simulation involving a number of hands subsequent to the current one. Many of the factors which influence the EV of the future hands are therefore included. Exactly how many hands are simulated can be set up. Obviously, in terms of the quality of the results, the more the better. There are, however, serious computational limitations as the calculation time increases exponentially with depth. Again, you can run such a simulation using, for example, HoldemResources Calculator. There are several kinds of spots where using FGS results instead of simple ICM seems particularly favourable. You should be aware of this if you find yourself in one of the following situations: You are shortstacked and afraid of losing playability if you don’t act before your big blind (especially important in early positions). You are willing to take a decision which, according to the ICM, is slightly minus EV, in order to be able to abuse the resulting stack setup - rather than be abused. You could pass on a plus EV calling spot in order to preserve the shortstack and be able to abuse the situation further. Finally, you could pass on a slightly plus EV spot as the stack setup dictates that there is a good chance of someone busting soon. In such cases, in order to get reliable results, you are better off running FGS calculations in order to take into account these additional factors.
In this lesson you have learned that: Using Nash equilibrium to determine ranges has its limitations. Using ICM for stack valuation has its limitations. Most of these problems can be addressed using a model called Future Game Simulation.