Happens All the Time
I understand that solvers multiway are not definitive, so I welcome all opinions as I seek +EV range estimates. Please don’t be shy, because I believe answering these questions could be helpful. I feel kinda lost here and need your perspectives. Thanks
Hero opens $15 on the button in 1/3 and the bb and all 3 limpers call. Happens all the time.
What range is better off limping behind when nobody is likely to fold?
What range is better off opening standard anyway?
And, the flip side - if we increase the bet. Now villain opens $40 and most players will fold.
What range is better off opening large in this scenario, even when everyone is likely to fold?
1 Reply
There just aren't fantastic "theoretical answers" to this question. You'll probably get better responses in the Live Cash forum.
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A useful beginner heuristic to simplify your strategy is to use the "one seat back" rule. If you're facing a limp in the BTN, isolate as if you were opening the CO. If you're in the CO, isolate as if you were opening the HJ, and so on.
Here's a limping range from actual hand history data:
Limps are not completely devoid of value. People will limp AA. But they also call too wide vs an iso. Nodelocking both the limping range, and their overcall vs the iso, we can solve for "optimal" iso range:
CO vs UTG Iso:
BTN vs HJ Iso
Now, there are a bunch of shortcomings to this approach. Namely that it's too simple, that you probably want some mixture of overlimps, and of course you can modulate your sizing to take advantage of inelastic calling ranges a bit. Moreover these ranges assume perfect play on future streets, and they are solved for one limper not 3 limpers (which should push you tighter). This is why I say there just isn't a great theory answer to this question.
Regardless, the "one seat back rule" seems to work well in practice. And hopefully the population data gives you some idea of what realistic limping ranges look like.
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If you're lookng for a detailed article on how to play vs limpers, I'd reccomend this one by Andrew Brokos:
