Being a member of the Baseball Bloggers Alliance has a lot of pretty neat perks.
As a fairly avid reader, my favourite one of these perks is the occasional chance to get an advanced copy of an upcoming baseball book. A few months ago I took advantage of this by acquiring “Trading Bases” by Joe Peta. Though the press release contained a synopsis of the book, I didn’t need to read it to know I’d be interested. All I had to do was look at the sub-title: “A Story About Wall Street, Gambling, and Baseball (not necessarily in that order)”.
The main premise of the book is that Joe (a former trader on Wall Street) attempted to make money by betting on Major League Baseball games against the Vegas odds, using a model he created with the risk management practices he gained during his trading days.
As a guy who loves baseball, loves gambling, and works with risk management created models by day, this book was right up my alley.
Without getting too much into the nitty gritty of the book, I’ll just get straight to the happy ending. The model he created worked – he finished the 2011 season with a healthy return. It’s not much of a spoiler – I doubt he’d go through the process of writing a lengthy book if the model failed. But that’s not the interesting part of the story. No, what’s interesting is the model itself.
Peta’s main argument behind why his model was so successful wasn’t that he knew more about baseball than industry experts. In fact, he used existing data that others had created (statistical items such as WAR, Pythagorean Record, Win Expectancy, etc.). It wasn’t that he claimed to be able to correctly predict the outcomes of certain games, like gambling ads you’d see in the paper (“LOCK of the week! 100% Accurate!!”). In fact, he barely finished the season with a winning record, often losing more games than he won in certain months. And it wasn’t as if he had an astronomical amount of money, so he could cover up mistakes with bigger bets (like the Yankees). In fact, he never deviated from his system once.
No – the main reason he claimed his model worked is because of the nature of baseball itself. With so many games each and every day, and with the lack of a traditional spread (like in football or basketball), Vegas money lines are fairly static. If the Cincinnati Reds are favoured to beat the Chicago Cubs, the line will be similar each game of the three-game series, moving slightly based upon starting pitchers and home field
advantage. Since the Vegas lines rarely accounted for daily lineup changes, in-season performance, and injuries (aside from ones to major players), he believed he could gain an edge.
A quick example using current teams: if the Reds play the Cubs, but decide a few hours before game time to sit Joey Votto, Jay Bruce, and Brandon Phillips, and sub in their backups, one would expect the Reds to be fielding a much weaker team. There win expectancy should go down. Since the Vegas lines rarely move, suddenly there is a real advantage to betting the Cubs. They may have moved from a win expectancy of 25% up to 45%, but are still being priced as a 25% underdog.
In a nutshefll, that’s what Peta did every day – re-calculate expected winning percentages based on each team’s daily lineup. The bigger the perceived advantage, the bigger the bet.
The amount of work that he put into his model was outrageous, and is not practical for an every day person to perform, but the premise is interesting none-the-less. I really enjoyed reading the baseball theories behind his judgement, along with baseball stories from his youth, and his monthly tracking sheet that he displayed throughout the chapters to monitor the model’s performance was very interesting. Even though the reader doesn’t know him, and doesn’t have any money invested, you almost feel yourself rooting for him to succeed.
There were a few aspects of the book I could have done without – there were passages where he delved heavily into investment-talk, hedge fund strategy, and stock trading lingo – but that’s just personal preference.
If you’re a person who enjoys the statistical side of the game of baseball, I’d recommend it.
500 Level Fan Rating = 4 Stars