Biz whiz: Bettor up!

Joe Peta, a former hedge-f
und trader, is the author of a new book, “Trading Bases: A Story About Wall Street, Gambling, and Baseball” (Dutton). Here he explains why his new job, wagering on baseball, may be a better bet than buying stocks.

Having spent nearly 15 years on the trading floors of Wall Street’s biggest investment banks, I know that the only person more popular than the intern who delivers lunch is the local bookie.

For the past two weeks, betting on March Madness has consumed the desk of every Wall Street bank, just as betting on the NFL and college football does in the fall.

And yet, even though there is no shortage of baseball fans in the industry, once April rolls around betting talk dries up until NFL teams report to training camp. This is a pretty common attitude. Of the $3.17 billion wagered on sports in Nevada in 2011, just 18 percent was on baseball — compared to 42 percent for football.

That’s a mistake.

Prior to 2011, I fell into the same pattern. However, after an accident curtailed my 15-year career as an equities trader, I threw myself into the baseball season. Instead of trading stocks on a daily basis, over the last two years I bet on roughly 75 percent of the games played, including a move to Las Vegas in 2012 to run a baseball-centric hedge fund.

I came away convinced of the following: Betting on football and basketball is fun, but, in the long run, it falls into the category of “gambling as entertainment.”

Betting on baseball, however, provides the opportunity to reclassify the activity as “gambling as an investment.”

The house advantage in baseball is, at worst, only half of what it is in basketball and football. That’s because football and basketball bets involve a point spread, but baseball bets are governed by the money line. Most bettors don’t know it, but across an entire baseball season, the house edge, or “juice,” is only about 35 percent of what it is betting on other sports.

Further, baseball can be modeled more accurately because a baseball game, at its core, is simply about 70 one-on-one confrontations between pitcher and batter. I can model Justin Verlander’s strikeout rate with extreme confidence, and it wouldn’t vary significantly if he changed teams, leagues, stadiums, etc.

The ability to model an outcome that confidently is not possible in football. Tom Brady is just as much of an elite quarterback as Justin Verlander is a pitcher (right down to spending quality time with supermodels), but if you move Tom Brady to Kansas City, there is no way his statistics in New England would follow. With a different set of receivers, a different offensive line, a different offensive scheme, Tom Brady’s results would look very different.

With a tip of the hat to the pioneers, particularly stat guru Bill James, I built my own model, based on such factors as how often teams scored with hitters on base, pitching efficiency and other statistics.

For example, let’s turn to Opening Day in The Bronx, where the Red Sox face the Yankees. It’s CC Sabathia’s fifth straight Opening Day start for the team, but this year he takes the mound with, by far, the weakest lineup supporting him. Every Yankee team he’s pitched for has been top three in slugging percentage, scoring at least 200 home runs and 800 runs each year. Based on statistics, tomorrow’s lineup would be lucky to hit 150 home runs and score 700 runs — offensive levels that Yankees fans haven’t seen since 1991, when Steve Sax and Kevin Maas were Opening Day starters.

This year’s Yankees starting lineup, with Sabathia on the mound, looks like a 90-win team.

This year’s Red Sox lineup projects to be just mildly above league average. He may have the better offense supporting him, but Jon Lester’s ability to strike out batters dropped for the third year in a row in 2012 — a trend that doesn’t project well for 2013. With Lester on the mound, I see the Red Sox as an 87-win team.

A lot of it comes down to home-field advantage, which I calculate as 4 percent in baseball — meaning if two evenly matched teams take the field, the home team wins 54 percent of the time. Thanks entirely to the superiority of Sabathia over Lester, that increases by 2 percent — the Yankees win tomorrow’s game 56 percent of the time.

Not really a sure bet, but from a money-line perspective, I’d bet the Yankees at „¦125 or better or the Red Sox at +130 or better. That means you would need to bet $125 on the favored Yankees to win $100 or wager $100 on the underdog Sox to win $130.

And that’s part of what makes gambling on baseball less heartbreaking than football. If the win expectancy of the model differs from the price that Las Vegas set, a bet is made.

There are no point spreads, where you’re, say, paying for the New York Giants to score a meaningless field goal in the final minutes to be up by more than 10. When you bet on a baseball team to win, your interests are aligned perfectly with the players on the field.

The manager in the dugout will be doing everything possible to help his team triumph and, by extension, you win your bet.

Finally, a well-constructed model can give the bettor a small edge, akin to the house advantage in, say, roulette. If you were offered ownership of a casino’s roulette wheel for a set period of time, would you rather own it for 30 minutes or a little more than 4 1/2 hours?

Funny things can happen in a half-hour; even with a small edge, there is no guarantee of a profit. But over nine times as long, the variance will smooth out and the advantage will almost certainly accrue to you, the owner.

There are only 256 regular-season games in an NFL season, but 2,430 games in the MLB season — about 9 1/2 times as many games.

In 2011, I started a “hedge fund” for baseball betting and ended up 41 percent for the season. In 2012, I actually moved to Vegas from July until the end of the season. Owing to the vagaries of betting and baseball, the first month was brutal, but I ended the season up 14 percent.

This year, I’m hoping to do even better. Is baseball a surer bet than Wall Street? I hope so. It’s certainly more fun.