Treat Your Poker Like a Business by Dusty Schmidt
Dusty Schmidt is a highly regarded professional online poker player, renowned for putting in a truly staggering number of hours at the virtual tables, hence his nickname, "Leatherass". In 2009, he self-published his book, Treat Your Poker Like a Business, and sold it for $39.99. In 2012, Cardoza Publishing reprinted it and sells it for $24.95. It is the Cardoza Publishing copy that I have read and am reviewing here.
Schmidt made his name as a poker grinder, someone who plays loads of hours and hands, making his money off of a small edge over an enormous number of trials. Very little of his book is devoted to strategy and playing hands. Most of it is about the mentality of being a poker grinder. Schmidt makes it sound like all one needs to achieve the same results as he has is to want it badly enough and follow his dictates regarding game discipline. I think he undersells some of his skills that are less easy to teach, but certainly, following his advice will help a poker student. I'm just not sure that such a work ethic is sufficient to achieve his level of success. Schmidt uses track legend Steve Prefontaine as an example of what one can accomplish with enough dedication. The problem is that no matter how much most people dedicated themselves to the task, very few are physically capable of reproducing his achievements. It's not always just about desire.
That said, Schmidt's work ethic is well known in the online poker world, and it's the cornerstone of the advice he provides in Treat Your Poker Like a Business. He emphasizes hard work, concentration, dedication, and data driven decision making. This is not all that dissimilar to what other authors have proposed, but there are a couple of areas where Schmidt blazes his own trail.
Schmidt advocates an 80/20 split for playing vs. studying poker. I think this is fine for a player with win graphs that look like the author's. Personally, I recommend a 33/67 split for players who have not yet hit career black ink or who are under 100,000 career hands. Note that Schmidt does recommend that players on a losing streak back down to a 50/50 ratio until they make their way out of their current rut.
I understand, and agree with, Schmidt's emphasis on cash game vs. tournament poker. However, single table events provide a way to considerably lower the variance of play, and shouldn't be lumped in the same category of the large field events. Second, even though large field tournaments do provide a much larger degree of volatility than cash games, they still allow a player to exercise a comparable level of skill, although it can take much longer to accumulate enough data to feel confident in one's long term results. Again, I think Schmidt is correct about his preference for cash game play, I just think he states his case a little too strongly.
The last section of the book covers recommendations regarding game play. While brief and less quantitative than many contemporary approaches to the game, I found his advice here to be extremely valuable, especially his "5 Effective Plays That Are Underutilized". Even if you don't want to use these plays yourself, the book is worth reading just to familiarize yourself with them, because poker players will see these plays used against them. I also appreciate that Schmidt considers counter-strategies against the strategies he mentions.
I wouldn't rate Treat Your Poker Like a Business as one of the top books on poker I've ever read, but it is certainly strong enough to be worth reading for the $25 that Cardoza Press is charging. For me, understanding the proper work ethic is an area that doesn't need as much work as other factors of my game, so, while useful, the majority of the book just isn't as valuable to me as his strategic considerations. However, there are certainly an enormous number of skilled poker players in the world who are missing merely good work habits to become successful players, and for them, Schmidt's advice could be a difference maker. In any case, I recommend this book to serious poker students.
The Signal and the Noise by Nate Silver
Nate Silver is best known these days as the author of the FiveThirtyEight blog at the New York Times where he synthesizes data, primarily polls, in an attempt to predict the outcome of the U.S. Presidential election. His ability to accurately predict election results in both the 2008 and 2012 elections have brought him a great deal of fame, but this is not the only field of endeavor in which he has excelled. He has also contributed to the statistical analysis of baseball, what folks call sabermetrics, and, of interest to this audience, has been a professional online poker player.
The title of the book is The Signal and the Noise and the subtitle is about predictions. The book deals with these topics, but a more descriptive title, if obscure and clumsy, might be, Why You Should Approach Things In a Bayesian Manner, referring to Bayes' Theorem from statistics. What this means is that there are many ways to fool yourself or others by making predictions, and Silver does a pretty comprehensive job of describing the ways predictions can go wrong. Overfitting, correlation vs. causation, and prognosticators who aren't held responsible for their records are some of the ways we can be fooled into accepting predictions that are unlikely to be, well, predictive.
On the other hand, there are two sources of predictive error that I don't think Silver discusses in sufficient detail. The first is the need to separate data used to form hypotheses from that used to test them. The second, which is discussed just not in as much detail as I believe the topic warrants, is the fact that in some predictive systems we expect that past behavior and future behavior to be identical, and in others we strongly suspect that this will not be the case. For example, we should expect that data we accumulate about seismic activity from the past to apply to earthquakes we experience going forward. On the other hand, we should be concerned that data we collect about arbitrage opportunities in the stock market will not be applicable going forward. By the time we can become certain that such an opportunity exists, we have to acknowledge the chance, perhaps even the likelihood that someone else will have noticed and moved to exploit it.
Silver demonstrates his points through a number of different approaches in The Signal and the Noise. These examples demonstrate the good and bad surrounding the people and methodologies of various types of predictions. Specifically, he looks at earthquake and weather prediction, baseball statistics, the stock market, macroeconomics, computer chess, and climate change. Track records of researchers in some of these fields have improved greatly over time, and in others they are abysmal. Which of these topics fall in each category might be surprising.
Two problem domains are of specific interest to gamblers. The first is the online poker boom and marketplace. Silver played professionally through the boom, but got out as he realized that post-UIGEA the quality of play online was improving faster than his own skill. The second is an exploration of the results of basketball bettor Bob Voulgaris. Both of these are interesting, but while I didn't expect Silver to discuss how to play AQ under the gun or for Voulgaris to divulge what key handicapping criteria the market isn't taking into account, most of my reading audience probably would have enjoyed more detail. I would have.
Again, surprising nobody who has read very many of my reviews, I would have generally enjoyed a more detailed and mathematical approach in The Signal and the Noise. It would be unfair for me to be too critical, though, as that's just not the book that Silver intended to write. Successful gamblers are exactly the demographic most likely to already apply the ideas that the author is trying to instill in those reading this book. Overall, I think it does a good job exposing people to the risks and rewards that come with thinking about events probabilistically. The world would be a better place the more people take Silver's lessons to heart.
Thematically, the book is a little clumsy. I get the feeling the author couldn't quite decide if predictions, logical fallacies, probabilistic thinking, or Bayesian analysis should be his central message. Nonetheless, I broadly agree with his various approaches and his recommendations. There are a lot of people who would do well to read this book, and I recommend it to a wide audience.
