Review of Nate Silver’s The Signal and The Noise

Nate’s book, The Signal and The Noise, immediately goes into the pantheon of great books about risk and prediction.

Any illusions that this book will put the reader on the path to quickly copy the success of Nate or his varied protagonists are dispelled in the early pages. Nate writes:

That is why this book shies away from promoting quick-fix solutions that imply you can just go about your business in a slightly different way and outpredict the competition. Good innovations typically think very big and they think very small. New ideas are sometimes found in the granular details of a problem where few others bother to look. And they are sometimes found when you are doing the most abstract and philosophical thinking, considering why the world is the way that it is and whether there might be an alternative to the dominant paradigm. Rarely can they be found in the temperate latitudes between these two spaces, where we spend 99 percent of our lives.

In Nate’s brilliant chapter on poker, he references the “Pareto principle of prediction in competitive environments,” which hypothesizes that 80% of predictive accuracy is achieved with the first 20% of effort. This level of effort, in poker or any other field, takes one only up to “water level”, well short of the standard required to make a living. Nate’s view is that, to succeed in any predictive field, one must work very hard, perhaps 60 hours a week, but all the value relative to the competition comes in hours fifty through sixty.

Nate’s careful tone, familiar to readers of his blog (, is partly temperamental, but partly, I suspect, related to his poker experience. Poker has a way of beating certainty out of people. I don’t think it’s an accident that two of the best books on risk written in the past couple of years, Nate’s The Signal and The Noise, and Aaron Brown’s Red-Blooded Risk, were written by poker players.

You would think that our best writing about risk would come from guys who run hedge funds, but this is emphatically not the case. It could be that hedge fund managers value their time and knowledge highly and don’t want to share, but it might also have to do with selection. Every intelligent poker player has gone through periods where they’ve run insanely poorly, and has also, more painfully, played in games where they started off assuming they were a winner but then ultimately had to conclude that they likely were not. Many hedge fund managers simply haven’t had the painful lessons; the fact that we observe them currently managing a lot of money means that if they are, like most humans, overconfident in their beliefs, they’ve yet to pay the price for it. Victor Neiderhoffer wrote a pretty good on speculation back in 1998, when he was on top (The Education of a Speculator); he would probably write a damn good one now, having been broke two times since, but there’s no market for busted hedge fund managers who want to write books and so few get the benefit of their experience. The consensus Wall Street pick for the best book on speculation, Reminiscences of a Stock Operator, was the rare Wall Street book narrated by someone who lost his fortune several times over.

Nate’s book covers statistical prediction as it relates to the mortgage crisis, political prognostication, baseball, weather, earthquakes, macroeconomic forecasting, infectious disease, basketball, chess (Deep Blue vs Kasparov), poker, money management, climate change, and terrorism. I suspect that the areas I know the least about (terrorism, climate change, infectious disease, earthquakes, and weather) were also the weakest chapters in the book. His chapters on poker, basketball, and money management, the areas I know the most about, struck me as nearly perfect, getting nearly every detail correct. I think the classic books in economics are defined by the little choices about what to include or not to include; a classic book, for example, Thomas Schelling’s Micromotives and Macrobehavior, will make the tradeoffs so perfectly as to inspire and teach newcomers and masters in the field equally, meeting Hilary Putnam’s test for a philosophical classic: “The smarter you get, the smarter it gets.”

In the three-plus years Nate spent writing this book, he clearly borrowed a bit of the best from every field. Those seeking a summary of the current state of the literature on market efficiency could hardly to better than Nate’s chapter, “If You Can’t Beat Them…” I can see the thumbprints of the genius Richard Thaler all over that chapter, and indeed the influence of another book from the pantheon — Richard Thaler’s The Winner’s Curse – is evident throughout Nate’s book.

I cheated and did not read this book straight through. I immediately jumped to see what Nate had written about my buddies Tom Dwan and Haralabob Voulgaris. Haralabob was clearly a bit gun shy with Nate, sparing him the details of his analytical methods or at least not allowing Nate to write about them. The chapter is nonetheless immensely entertaining. The exact backstory of how Haralabob came to risk all of his money on a 6.5-to-1 shot was not known to me, and it provides some context for our first meeting, when Haralabob and I played heads up $25-50 poker all night in the Bellagio around 2003. I was hoping he’d go off for the $100k cash stack he had in front of him; he was hoping to bust me quickly and go to bed.

Both Tom’s poker tactics and Haralabob’s basketball analytics are a bit more dazzling than Nate’s chapters convey. Tom’s a tough one to write a book chapter about because about two-thirds of what he says is pure genius and about one-third is complete madness, and you don’t know how to make the determination until about two years after the fact. He’s probably the most naturally gifted poker player I’ve ever seen (most evident to me when we’ve played Liar’s Poker with recycled dollar bills). A better fit for Nate’s book could have been someone with a more workmanlike approach — Ben Sulsky, perhaps, who crushes opponents through a relentless application of game theory and Bayesian inference.

The Signal and The Noise is a must read for those interested in sports analytics and sports gambling, but it has limited direct application. For a practical guide to implementing the kind of data analysis that Nate preaches, I would recommend Sam Savage’s Decision Making with Insight.xla. Sam and Nate have similar approaches to data, emphasizing simulation, probabilistic forecasts, and Baynesian techniques. Sam’s book, The Flaw of Averages, covers a lot of the same ground, but doesn’t serve as a guide to implementation. A detailed guide to the Baynesian approach as applied to sports forecasting can be found in William Mallios’ Forecasting in Financial and Sports Gambling Markets.

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