The Poker Zoo 57: Mind Blown

The year-ending edition of the Zoo. Suitably, I talk with The Back Room standby Jason Burge, author of the JamBasket series of videos. We go over his year in poker, and hit some highlights of the greater poker scene as well. (Apparently I already forgot about Phil Galfond: hey, but what have you done for me lately?) Our piece de resistance for this podcast is, however, Mindblowing Poker, a new book by an English professional player. In it, “Professor Poker” reveals his personal poker philosophy and propounds a way forward for the game at a time when its future is consistently doubted. Is he right or wrong? Is that even the question? We break it down and even get some queries directly answered by the otherwise anonymous author.

As mentioned in the podcast, the Poker Zoo community is kicking off a series of deepstack, low-stakes games in Las Vegas soon. To find out more and get a seat at the table, contact me through any channel, including my gmail address, persuadeo@. We need players to get this off the ground!

Classic HSP review mentioned is here.

Mindblowing Poker review starts at 29:00.

Q & A correspondence with the Professor on Mindblowing Poker:

The public wants, in spite of your wishes,  a little more detail on your life in poker: what stakes, what sites, how would you describe your pool, any known crushers/poseurs you play against? Give us something.

Firstly, thanks very much for inviting me to take part in this podcast – appreciate it’s strange not to have me there speaking! As you’re aware – I’m very keen to keep my identity under wraps. Let me give a bit of an introduction. A big part of my philosophy is about keeping moving, staying elusive, allowing you to move around and play in a misleading way and move on before the pool will catch on and exploit you. I appreciate that those committed to the pursuit of perfection and GTO aren’t concerned by such players, but in practice I find this a much superior way to extract profits from poker if you can learn about others quicker than they can learn about you, which is my skill. I’m concerned that as we arrive at situations where everyone at the table is playing a near perfect strategy (over the spots they commonly see), then they will eventually all expect to lose to the house. Therefore I move around a lot, finding the ‘low hanging fruit’ first, but this is increasingly hard to find. What I propose players do next is to ‘shake the trees’ rather than spending time plotting how to get the fruit from higher up in the tree. 

To answer your question then – I have played an incredibly varied set of games since c.2007. I built a bankroll on Pokerstars and 888. Once I had a significant bankroll, I became a live player – I’ve been at WSOPs, WPTs and EPTs and have had strong results there. I’ve cut this down over the last couple of years (partly because I like playing at home online, partly because of Covid).

I’d describe myself as a maths nerd but someone who has made a conscious effort to see the bigger picture. You have some very clever people in poker, who love game theory. But the irony for me, is that they can’t see the theory of the bigger game they exist in. They all have an incentive to refine a GTO strategy, but once all players have refined it, the game will die as nobody can win. 

In terms of who I am, I’ve had Vanessa Selbst, Charlie Carrell, Brad from Chasing Poker Greatness and Will Kassouff all incorrectly suggested recently. The clue I will give is that I grew up in the UK.

Questions from the Mindblowing Poker Twoplustwo thread

First, Mason seems to very much want to stick to the abstract definition of GTO, while you are arguing, essentially, that players can’t perform at that level of practicality. How we talk about this is essentially the “EV Loss” of our real game strategy vs optimal. Have you tested any of your own strategies in the solver using the limitations of what you see employed, via node locking and real range inputs? Are you talking about theory or actual, demonstrable line development? Are you really talking about player pool adjustments, but just in a different language?

It’s important to understand that first and foremost my book is an idea, a philosophy. A lot of the plays I’m promoting aren’t intended to stack up in a solver, unless you were to calibrate for an enhanced EV loss from a villain. If I write a hand example, anyone can run off and put it in a solver and find a solution, but the real test is – how far away were they without using the solver?

The point is to push the villain into a spot they wont have seen before, and wont have tested themselves in a solver. In short, we all know what solvers can do, but what my plays do is to focus on misleading the inputs to the solver. If you put ‘garbage in’, you get ‘garbage out’. That’s the underpin to these plays.

Where people have taken things I say to solvers that kind of proves my point – if a player needs to have a solved solution for every spot, then you just need to screw up their inputs to throw them off. I don’t think anyone can argue that upsetting the best players isn’t a useful tool to have – the question is just how often and when to use it.

Second, the DriveHUD creator seemed to not accept your estimations of how much GTO will cripple the market. Can you clarify the contradiction he underlines: either GTO will crush the poker market and we need alternative strategies such as yours to reignite it, or players can’t duplicate GTO and so we don’t need your alternative strategies but simply more study?

To me both are true because there are two categories of spots – “well trodden path” and the “outback”. Every year poker is closer to being solved, and as RTA apps etc become more easily available, you’ll soon find even games like $10 online becoming near perfect (give it 5 years). However, all of this refers to the game as we know it – the “well trodden path”.  I believe there is an enormous number of spots in poker that are not explored – primarily because they haven’t been arrived at by recent strategy, or because they are frighteningly bad or involve an irrational villain. The point is you wont reach this “outback” area of the game trees by accident – you need to do something abnormal to get there – I call this “range shanking” in my book.

Let me give you a good example. If you face a villain 100bb deep, who could somehow commit to 5x donking every turn, do you adjust pre-flop? What do you call with on the flop/turn? If you run this through a solver you could find a way to get an answer,, but who is capable in the moment? What if the villain was in fact only donking 80% in reality? There are millions of parts of the game trees that are unknown – but current poker theory isn’t touching them. So you’ll end up with a perfectly solved 1% of the game and an ignored wilderness.

I’m fine with more study – but the study, as I understand it, of most fellow players is focused on refining strategies within the previously trodden path, rather than moving opponents to unseen game trees.

With “Optimal Sub-optimality” you have reinvigorated the classic idea that we should manipulate our image, even so far as to be seen as the whale or fish. Fair characterization of the concept in Mindblowing Poker, or is it something deeper?

I’ve used some examples like this but I don’t really think they work all that often. Coming across as a bit of a whale works well at say mid stakes online (e.g. play a $60 Sit n Go on Stars and open limp 10 hands at the lowest blind level, and you’ll have tons of regs deviating and playing with junk just to get in pots with you) but I’m not sure its a game-changer. 

Instead what I’m talking about is things a bit more subtle such as players who slightly manipulate elements of their game. For example, you’ve got Phil Hellmuth – who, whatever you think of him, can sit down at a table of recs at the WSOP and play 97off profitably because the recs mis-assign a range for him. 

Another example would be someone like Ian Steinman who folded a set of Kings (second nuts) to Joe Mckeehan (who had somehow back doored a straight) in a well publicised hand in 2018. This was held up by poker community as one of the most stunning folds of all time – and by GTO players as “unbelievably bad”. But the actual optimal sub-optimality in it is that this guy is now known around the poker community as making a super tight fold. He can now call river bets with a higher than optimal frequency, profitably, for the rest of his career, because a few players are going to add more bluffs in certain spots. I think a lot of GTO types dismiss ‘levelling’ as something to avoid – but if you understand it, then its an edge. 

Is it reasonable to assume that opponents will make large enough mistakes such that they offset the EV of a more traditional opening range? (For example, if instead of opening the button 40-50% of the time, you “range swap” and open a traditional UTG range of 10-20%. You’ve now taken several clear +EV hands and folded. So now, to make up their EV loss, you need to regain that EV, plus more in order to declare Range Swapping a superior play. Something similar happens from UTG where you now open many -EV hands in hopes of ALL of the opponents collectively making enough mistakes to completely offset this EV loss, plus more. I realize this may be an extreme scenario for demonstration purposes.)

Good question. This is an area I wanted to test with the poker community. I think the answer is sometimes yes, sometimes no, and my book is just the start. There’s a lot more thinking that needs to be done. I think I said in my book that range swapping in particular is hard to justify mathematically. Maybe there is an element of some of these plays working better where GTO players try to adjust and exploit, rather than sticking perfectly to GTO. 

But the premise is that, for example, if you have a much stronger range than GTO villain thinks, you are profitable in that specific hand. If you have a range of 77+, AK, AQ, AJ on a flop of AQ4 rainbow, but the villain thinks your range is full of 97suited etc, they are not going to make the best decision. The question then is if you lose too much EV from your strategy as a whole from deviating to this range, rather than losing EV in the moment (which is the point Mason didn’t understand on 2+2). I would suggest that given these are short run tools, that it does more to alter the variance of your session, than affecting your EV as a whole. This then tips more reactionary villains into a world where they doubt your game and may either want to avoid you, or play too many pots with you. At that point you can make profits by playing perfectly standard poker strategy. The end game is to try to put villain in spots they haven’t seen, and then they make the bigger mistakes.

Large bet sizing is becoming more popular in poker today. You’re suggesting Enormous Bet Sizing, which certainly has merit, and should definitely be explored in a no-limit betting game. You write “…if you’re going to go for a big bet, the decision of how much doesn’t really matter.”. Some strong players such as Truteller have stated that bet sizing is one of the most important aspects of poker. Why does it become less important when betting big? Later in this section, you note that the equity needed to call vs a 10x pot bet is 47% while it’s only 33% vs a pot sized, and label the difference as “only a small amount”. Isn’t this a considerable difference in poker?

Don’t get me wrong, bet sizing can be absolutely vital in certain contexts. But I think that say 14% is sometimes a big difference, sometimes it isnt – it’s a big difference where players have wide ranges, but less key when players have very narrow ranges. 

My point is that I’m not sure many players, even the finest, have a perfect ability to nail a villain’s value bet range down enough to reliably determine their win %. Sure they can tell 0%, maybe 25%, 50%, 75% or 100%, but if you’re assigning a villain a range and combo counting, there’s an error rate that can easily be manipulated. I’ve been using these enormous bets, heavily unbalanced and weighted to value, and getting calls from top drawer live players. In fact, a big reason for my anonymity is that they work so well.

There is something of a theme of short term adjustments that invariably force us to retreat to less exploitable play in the long run. How do you square all the deviations advised in Mindblowing Poker with a long term strategy for the game, if what you want is a revolution?

If you think of a pool of players all striving to make short term deviations vs good players and exploiting any weaker players and switching back into a good GTO strategy at the other points, I think the profit rate can be higher for all strong players in the game. Part of that comes from encouraging more players into the game with more diverse strategies. I think poker is much more marketable if more weight that can be placed on psychology, and less placed on maths, and for me, reaching a wider audience is the aim of the revolution. Poker could be modelled, crudely, as a Ponzi scheme – eventually those at the top need to stop being greedy, in order to ensure the bottom keeps filling – otherwise the whole thing topples.

So many concepts in Mindblowing Poker echo Andrew Seidman’s Easy Game. “Range swapping” literally copies “ his “range switching,” the “polarized middle” “shanking” and other concepts are straight from Seidman’s classic text. Describe his influence or the influence of other writers/thinkers on your game.

I’m not actually familiar with this book – I will need to check it out. I would say I’ve been influenced by all of the bad books I’ve read on poker. They’re either out of date, too theoretical, or too specific to a certain game, with an author who clearly doesn’t understand exactly why the plays are working and the specific dynamics that can fall away quite quickly, rendering a play useless. 

I’ve been influenced by a number of players on the circuit. Mustapha Kanit’s style helped refine and reshape a lot of my thinking. I’ve been positively influenced by good Youtubers – although these too can be too trend driven. Doug Polk was good for a while.

But I think where the community went wrong is to shirk away from understanding opponents, levelling and exploitation to hide behind data and maths. This works on average, but it does open the door to someone clever enough to understand the maths, but cunning enough to manipulate that maths and exploit the outcomes.

The “flop evaluation tool”: what is this about? It’s not a tool, to start with.

You’re right – it’s not a tool. You’ll have to remember that I wrote this book to appeal to a wide variety of poker levels. What this does is set out the chance the villain is likely to have a certain absolute hand strength on different kinds of flops. I put it in to help with the limping section. In short – where you have a villain who will call/fold based on their absolute hand strength (either because they are a fish, or because they are a good player in a game tree they don’t understand), you can use these tables to work out where you stand.

Are you satisfied with Mindblowing Poker? What would you change?

Obviously there are things I would change, but overall I’m pretty happy with it. I think it has been tough to get the messages out. I think a lot of people in certain factions don’t want to acknowledge what poker could look like in 5 years without change, probably because they have short term vested interests i.e. selling books on GTO. I haven’t done this for money from book sales (believe me, margins are slim – I can make more in a session than I will in total from the book), or for any reason other than to try and shape a more interesting direction for poker. For this reason I needed to make the book appeal to pros and more recreational players but I think I got the balance ok and it can still all be understood by everyone. I think most of the people who don’t understand the messages are the ones reading about it on forums – in general, I’ve had very good feedback and interesting debates by those who have read it cover to cover.

Thanks very much for the questions. Hope to see you on the tables!


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