Baseball fanatics like me love to wallow in cliches such as “baseball is life.” “Baseball is a lot like life,” said Hall of Fame broadcaster Ernie Harwell. “It’s a day-to-day existence, full of ups and downs. You make the most of your opportunities in baseball as you do in life.” Yes, indeed.
Regularly enough, however, a desiccated cliche like “baseball is America” comes alive. Such is the comment of San Francisco sportswriter Henry Schulman upon the announcements that Bryce Harper will get a guaranteed $330 million over 13 years from the Phillies and Mike Trout a guaranteed $430 million over 12 years from the Angels. (Trout will receive annually about 25 times more in real dollars than Babe Ruth ever did. He will make about 800 times as much per year as the median American worker today makes–and he will have a lot more fun making it, too.) “So, if I understand Baseball economics now,” Schulman tweeted, “a few guys at the top earn more than they can spend in 100 lifetimes, a lot of players who used to be paid decently now get scraps, and the group in the middle is shrinking quickly. No, wait, that’s America!” (@hankschulman 3/20/19).
Indeed, the pay disparities developing in major league baseball roughly parallel those that have developed in the general economy. (Mind you, no one need weep for the lowest-paid major leaguers; their minimum wage is about a half-million dollars a year. The real proletarians are average minor leaguers; they effectively earn less than the national minimum wage under difficult working conditions.) Another commonality between baseball and American economics is how massive data-crunching has helped produce growing inequality.
Off-Field Life
Widening economic inequality in the United States since the 1970s has been covered a lot in this blog. Several trends explain it, none more fundamental than political decisions which accelerated rather than resisted destabilizing economic forces such as globalization and automation (see, e.g., here). Both the rise of shareholder value as a legal benchmark and the undercutting of unions are examples of such political decisions. But another contributor is the increasing power and sophistication of data analysis.
You can see that, for example, in the rapid rise of financial institutions and careers. The finance industry depends increasingly on complex and blindingly fast manipulations of numbers. Thus, an increasing premium has gone to businesses and to individuals who can best handle those numbers, who can shave a millisecond off of a trade, who can tailor the trading algorithms which now do most stock transactions to yield a fraction of an extra point. No wonder that Wall Street has gone ferociously after MIT graduates, physicists, and their like. The share of national production going to the financial sector has soared, as have the wages of employees in that sector compared to the rest of American workers, contributing to widening inequality nationwide.
One can also see the consequences of computing power in various online businesses. Not only have legions of internet “techies” prospered, pushing living costs in places like San Francisco to unseen heights, low-price internet sellers–Amazon, etc.–squeeze out middle-range employees and middle-range merchants in favor of low-wage factory workers and low-wage delivery workers (see, e.g., here). Modern mass data crunching facilitates such disruptions at a scale far greater than the old mass marketers (Sears, for example), which also steamrollered local vendors, ever could.
On-Field Life
Computing data power and fine-grained machine measurements have changed baseball, too. The capacity of baseball teams’ and the media’s data analysts to precisely track performance these days–down to the spin rate of a curve ball, the torque of the batter’s swing, the launch angle of the resulting fly ball, and the expected probability of a given outfielder converging with that ball–make Bill James’s hand-calculated statistics and Moneyball calculations absolutely antique.
Beyond affecting how players are trained and how they are deployed in games–for example, using extreme defensive shifts, reducing starting pitchers’ innings, relying on one-inning power relievers, emphasizing swings that lift the ball–the data revolution has empowered management by giving it much richer profiles of individual player performances and much better projections of their future performances (e.g., Nate Silver’s PECOTA). Indeed, players are commonly measured in terms of an estimated WAR, “wins above replacement,” how many extra victories they contributed to their team compared to the contributions of a marginal, next man up from the minor leagues, replacement. Last year, Mike Trout was calculated to be worth 10.2 extra wins for the Angels and is projected to provide 80 extra wins over the next decade. WAR can, in turn, be translated–under current market conditions and contract rules–into the dollar value each player is likely to provide each year. By that calculation, the Angels are getting a terrific bargain in paying Trout about $35 million a year (assuming he stays healthy).
Analyses like these, actually far more complex ones, increasingly underlie the way MLB teams plan their payrolls. The new perspective appears to help explain a dramatic change in the free agent market over the last couple of years. While a few megastars have gotten megacontracts, experienced veterans, major league baseball’s “middle class,” have had trouble landing contracts. The average MLB salary has actually gone down.
Only a few years ago, a successful 30-ish-year-old player could expect a multi-year contract that rewarded him for his proven worth. My team, the Giants, was noted for generously rewarding the core contributors to their three world championships in the early 2010s. (The Dodgers haven’t won one since 1988–just sayin’.) The new data analyses suggest that this policy is a mistake in terms of paying for future performance, although it may keep sentimental season ticket-holders like me happy. The numbers show that after about the age of 28 performance and WAR drop notably for the average player.
The logical implications of these emerging data is that, under the current financial system, it makes sense to disregard solid veteran players and to instead use new, young, interchangeable, and cheap players to fill in around a few highly-paid stars. (The new Giants front office is moving in this direction.) And, so, like America more broadly, we are seeing widening inequality between top and bottom and a hollowing out of baseball’s “middle class.”
The players’ union will try to fix this when the current contract with the owners expires in 2021. There may be a strike. One veteran said, “There’s always kind of been that handshake agreement where we’re still going to value the older guys and not just totally (expletive) on them. And that’s what’s happening. So, I think you’re going to have to burn the whole system down. . . .” And here is a big difference between baseball and America more broadly: Average American workers don’t have strong unions and they can’t realistically threaten to “burn the whole system down.”
