Outline
The Preflop Trainer includes exercises which test your decision processes as well as your familiarity with solver ranges generated for specific game trees.
This article will outline practical use of the preflop trainer as well as explain how to get most from the various exercise types that are featured.
Training Exercises
To start an exercise, navigate to the Preflop Trainer tab and then click Exercises.
You will be taken to a page which enables you to select an exercise from any program which you have an active subscription to.
Tracking with the 'My Scores' tables
To view your scores navigate to the Preflop Trainer tab and then click My Scores.
You will be shown a page with a list of your most recently played exercises and workouts. If you click on one of the result boxes then you will be shown detailed information about your performance for each question in a given exercise/workout.
Training your decision processes
The purpose of Pokermuscle is to build the player's understanding so that he can make decisions in the dynamic environment at the table.
For example:
1) What action do you take if you face a min-raise instead of a pot-sized raise?
2) What if the initial raiser is a weak player? What type of hands improve versus different opponents?
Pokermuscle is designed to hone your decision-making, and so some exercises enable you to calibrate your understanding specifically of the equity factor in pre-flop decisions.
In a very real sense if you try and learn 'The Solver Solution' you blind yourself from ever being able to make accurate decisions at the table.
I encourage you not to think of 'The Solver Solution' as being a real and useful concept for multiplayer games with large SPRs. It is very useful for selling courses to people with attention-grabbing, simplistic marketing jargon. However any one solver simulation at a large stack size has made a set of post-flop assumptions which determine the pre-flop results for THAT set of assumptions.
Training your solver ranges
There is much less subtlety to decision-making in low SPR situations since the number of nodes is dramatically reduced, and the number of obviously dominated strategies increases as a fraction of the total possible strategies.
For low SPR situations familiarity with solver solutions for specific trees becomes far more valuable and so Pokermuscle includes a number of exercises to test you on solver solutions in these cases.
Whilst I do recommend caution in the use of solver solutions for deeper stacks, the demand from users for such solutions has been so high that I have included them also.
If you do train the solver solutions at the deeper stack sizes then I strongly encourage you to also practise other types of exercises so that you remain capable of making good dynamic decisions. Attempting to emulate a robot at deep stacks is not a path to long-term success in complex games.
