# Hull. Questioning The 1%,

TheGameKat
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**4,272**-
Doug Hull revisits they key ideas from the frequency-based approach to NLHE described in "Poker's 1%." Using solvers that were not available when this book was first published, Doug explains where modern theory deviates from the original recommendations of Poker's 1%, and reviews where the advice from that book still applies.

Please leave questions and comments on this video below.

Please leave questions and comments on this video below.

Moderation In Moderation

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## Comments

43✭✭Interestingly and maybe coincidental, Adam Wheeler did a video a few months ago looking at ~ 180 different flops and found that a 1/3-pot flop bet was made ~ 70% of the time.

4,272-34✭✭@TheGameKat It always struck me that the continuation percentage is elastic based on bet size. Is that the point you were trying to make, that at a lower bet size would increase the percentages in Doug’s results?

4,272-Yessir, exactly so.

1,876-Roughly this is a five dimensional problem, only one variable is mappable to a single number scale (SPR). The intended bet sizing progression is reasonably small set of expected bet sizes. The flop is a large set of possibilities that can be lumped into a set of smaller representative flops. The ranges are huge (13x13)^2 sets that can roughly be modeled as [0%-100%] ranges with some argument as to the ordering of the 13x13 components.

All this is to say that Miller's book was an attempt to slice through this huge five dimensional hypercube to give us a general look at this single number: c-betting percentage.

It would be surprising if a single number could be a decent approximation for this complicated of a dataset. What we see with GTO+ on the turn is that even when we hold all five of the above variables fixed and just look at different turn cards we get a huge variation in double barrel percentage.

So, 70% is not the right one size fits all percentage. Given modern solvers, I am guessing it is more like 50%, but the truth is there is no one-size fits all c-betting percentage. It depends.

We should not look at this and say "oh, 70% is wrong all my study is useless in this area." We should be saying: "Frequencies are important, that is a huge and important revelation. Let's see if there are patterns that tell me when it should be high, and when it should be low..." Ross is working on a project along these lines and it is really shaping up.

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10✭✭Its been beneficial. I've never worked s closely with my ranges and flopzilla as I have when considering a frequency based approach.

I have said a lot of credit needs to be given to events and the frequencies you choose. I like what was said about the solver and in a 11/90 split the low % action could be used in situations, where it was an option, based on the opponent or other factors of the situation.

Should players be looking more towards meeting their MDF and adjusting that for hand analysis/frequency awareness?

Should we be most concerned with solvers now and figuring out these spots and why the solver suggests certain actions?

34✭✭I didn't finish watching your video and worry that I had just wasted a bunch of time. I am far more motivated by being a part of the 1% number than blindly following the 70% number as some sort of golden ratio. It is clear how a frequency based approach to poker is the best way to win.

I do remain curious and excited about how your findings could influence the work I'm currently doing. It sounds your opinion is:

Thanks for the video and the quick response on a holiday weekend!

4✭✭27✭✭It looks like from your analysis that especially for pot sized bets, 70% is just wrong. Is that fair?

Do you vary the size of your C-Bets much? Also I see one of the variables is opponents range. What about assessing the type of player?

27✭✭1,876-@driller1 In a word, 70% is "wrong." Any single number applied to all situations would also be wrong, so this says nothing bad about the original 70% number.

The 70% was estimated based on a variety of ideas that helped to give upper and lower limits on the percentage. Without the GTO tools that have been developed since publication of 1% this was a very reasonable estimate and pushed the community in the right direction.

In speaking with Ross, who should be credited with heavily influencing my thoughts on all of this, we went through this process.

If I had to pick exactly one number to use all the time, like Miller did. I would choose 50%. This is what an engineer would call a "first order approximation." Not super accurate, but it starts to get us to an answer and we can refine.

Of all the things I listed in my earlier post as factors that influence this c-betting percentage, the variable that changes most from hand to hand and has the biggest influence on the number is the flop. On any given flop, I would want the ability to pick a c-betting percentage from the list of 0%, 50%, 100%. This is what we would call a "second order approximation" The way we think with this is more nuanced, but now we have three possible answers instead of one. We are looking at one more variable though.

Ross' work has helped to identify the poles, the 0% and 100% boards. The rest are 50% boards. Our approximation has gotten even better with this heuristic.

Bet size progression, just like c-betting percentage are mostly a function of the flop texture. 1/3pot through pot sized can be reasonable depending on the texture.

As far as poker Snowie goes, it has many of the same results at GTO+. GTO+ is meant for this work, but you can not play against GTO+. Snowie is meant to be played against. The analysis helps to understand why Snowie agrees or disagrees with your move. The information on the GTO aspects are there in Snowie, but harder to look at systematically.

I would say these two programs are based on similar analysis but have a different front end and user experience. I think there is a place for both of them in your library. I know I got them both.

-Doug

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27✭✭87✭✭882✭✭✭Solvers make use of position, protection, and balance more than the 70% model does. The 70% model is yesteryear and doesn't apply to today's games. Many of the hands that this model has us betting, solvers have us checking so that we keep enough strength in our check calling range. This all ties right into the rest of the 1% series which for the most part is extremely good. Branching and balancing ranges really is the key to extracting value right now. There's a video by Peter Clarke on RIO about checking strong. It's brilliant and again, ties right into a lot of Splitsuit's material on pyramids and balancing ranges, as well as frequencies.

882✭✭✭1,876-In engineering school, they told us "we are lying to you, but each year we lie less."

Is Newtonian physics "yesteryear" because other more complicated theory's are more refined?

Learning is a ladder, to get to cutting edge, the simpler models are a neccisary pre-cursor. In many cases they are also sufficient.

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