Mar

27

 Review of Trading Bases, a story of Wall Street, Gambling, and Baseball by Joe Peta

A timely book here just ahead of opening day, http://tradingbases.squarespace.com/. Peta relates a lifelong love of baseball and statistics, his experiences as an equity desk trader for Lehman Bros. (15 years) and his subsequent battle back from a horrifying injury sustained by being run over in the streets of NY by an ambulance –as if his Lehman experience wasn't enough to endure. He suffered a "Theisman grotesque" leg break that left him depressed and basically rehabbing alone in his NY apartment with wife and family living on the west coast.

His passion for trading snuffed by not being able to work, hopped up on pain meds, and trapped in the apartment leads to him to watching more sports than ever before. A baseball lover at heart and a statistical junkie, Peta finds a reason to wake up in the mornings. He decides to try his hand at making a statistical model that would identify edges for baseball team wins and losses that would provide him with a betting edge over the Vegas Line.

Peta eventually creates a hedge fund that bets baseball games that returns 41% in 2011 with similar daily volatility as the S&P 500. The book outlines Joe's views on gambling. Baseball is his preferred niche since the juice/spread is the smallest in comparison to other sports, the ability to use statistics to get an edge is available, and the natural alignment between the better and the team– rooting for your team to win versus the convolution of winning and beating a point spread.

Joe explains his model with care, logic, and facts–backing up his assertions with anecdotes, experiences and back testing in terms of the body of baseball evidence from the historical stat stockpile. He builds on the pioneer work of Sabermetrics, Bill James, and Nate Silver. In general his system uses time tested relationships of team win/loss records, runs allowed/runs scored, starting pitching assumptions, WAR/PECOTA analysis, and more. He relates his journey on a monthly basis showing his results, the breakdowns of what went right and what went wrong, his acceptance of a "lumpy" higher return than a smooth more accepted rate of return by clinging to the belief that reversion to the mean will occur–eventually. He uses a concept called "cluster luck" to identify "lucky or unlucky" pockets in team's prior records that should be ignored and removed from overall estimates. This is a key to his being able to form an opinion against the betting line of under or over valuation. His model then picks matchups that should be bet on and he uses a very systematic approach to determining the amount of the fund to bet on any one game–essentially using fund manager skill sets.

One notable opinion of his describes his fondness for "skill sets displayed" versus the recording of errors (mistakes committed and sometimes unfairly attributed). He uses SIERA (skill-interactive ERA) for pitcher evaluation and special modeling for playoffs and interleague games. He also walks the reader through his decision making process for when to tweak the model or when to stand pat—. Over tweaking will result in removing the natural capture of mean reversion. Joe has a friendly writing style and comes across as genuine, interesting and likeable.

I think any spec would like this quick reading book–you will learn something here about baseball stats and baseball betting theory; you may well enjoy the woven storyline of his trading career experiences as these snippets and stories move betwixt his model outlining. It is written for an above average mind, but its not too heavy to put someone off who doesn't deal with wall street or modeling on a daily basis. I read ever page, every micro-print footnote, and every end note.

Ken Drees adds: 

I could not find a section or passage by memory or a reference from the index to overall management influence on single game outcomes or win expectations. One chapter deals with playing from behind and how "small ball" played to cut a two run lead to a one run game is a bad practice–playing not to lose instead of playing to win–giving away your upside to get a better feeling that you are "doing something"–almost like a job justification strategy–manufacturing a run, playing to tie instead of win. Peta backs this up with data –pages 204-206. Obviously management is taken into account when overall seasonal expectations are determined. But the managers don't play on the field so they are not highly considered in Peta's analysis. I would think possibly it may come up as a side data point in the playoffs –having more of a weighting than regular season. It may be that widely popular managers may in fact swell a line up for a team and thus give you a better opportunity to make money against–like the NY Yankees as Peta points out are a marquee club who usually get premium priced in certain situations regardless of true odds.

Interestingly –he bets both national and American league games–turns down activity during interleague play since data is less deep for those occasions and also scales back during the playoffs.

In the chapter, "Focusing on the Wrong Data", Peta parts company with "a total lack of regard for management/soft skills mentality" that some of the sabermetric followers employ. He cites a player's manager, Ron Washington of the Rangers who is loved by his players and who makes a critical decision in game 3 of the world series tied one game a piece. He Gives veteran Torrealba –a 2011 95 game starter at catcher, a "deserved" start over the much better performing player at that time during the season, Mike Napoli. He juggled the line-up and in Peta's opinion weakened his team in two ways in order to give one player a "deserved" start over giving the other 24 players there best chance for a world series game 3 victory and series lead.

So maybe Peta does give some weightings in his model –maybe when playoffs and world series are in the prime-time spotlight managers can be exploited by bettors for their traits–both good and bad.

Victor Niederhoffer writes: 

I agree with the excellence of Trading Bases. The author is very brilliant, and very likable. And his discussion of what went wrong at Lehman is the best as well as his college essay on the central funding department, which almost got him fired, and his well deserved hatred of the boxing head at that firm, who gave him a one sentence interview before hiring him.

He assumes you know a reasonable amount about baseball trivia and it's helpful if you read the annual issues of the baseball prospects and are familiar with the pythagorean theorem of Bill James. The author was a star trader of tech stocks at several firms before being hit by a ambulance and turning to his first love after being fired by the Japanese and carried out in his wheel chair. A great book. I second what Mr. Drees said about it. 


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