BY BEN NICHOLSON-SMITH
The injuries were too much for the 2001 Oakland Athletics to overcome. They opened the year 2-10, but it was the season-ending setbacks to Jason Giambi, Tim Hudson and Barry Zito that really finished the team off. Six months and 95 losses later, the Athletics convinced Giants GM Brian Sabean to come across the Bay to replace Billy Beane. Any book ideas author Michael Lewis had were shelved, since there’s nothing remarkable about finding new ways to lose.
Of course, it didn’t turn out that way. The 2001 Oakland Athletics recovered from their 2-10 start to win 102 games on their way to the second of four consecutive playoff appearances. They made for a great story, not only because the players themselves were a colourful bunch, but because the team had been assembled on a tiny budget. Beane had a knack for finding market inefficiencies that old-school teams lacked.
Oakland’s ’02 season became the focal point of Moneyball, Lewis’s bestseller that simultaneously agitated and excited the baseball world. By the time the book became a Hollywood movie in 2011, analytics were commonplace in front offices, on-base percentage appeared on scoreboards everywhere and young, sabermetrically savvy GM candidates seemed to emerge as front-runners every time a job opened up.
But what if the Athletics had played poorly and the Moneyball phenomenon had never happened? The analytical push itself, so often associated with Moneyball, would have occurred anyway—by 2002, it was too late to stop the momentum. But the next decade and a half would surely have unfolded differently for the A’s, who remain one of baseball’s top teams today with Beane still in place as GM. And one of several other teams who were already employing similar ideas might have become our go-to for discussions of using statistics to better calculate success.
Led by baseball analyst Bill James, new ways of assessing players were already emerging, and front-office executives around baseball were starting to look at the game with a more businesslike approach focused on data, rather than long-held assumptions. “Oakland has received a lot of notoriety about what they did,” says Gord Ash, Milwaukee Brewers vice-president and assistant GM, who was GM of the Toronto Blue Jays from 1994–2001. “But there were a number of clubs doing it, probably a lot more quietly, around that same time.”
It was more than just a couple of teams. Of the 30 GMs in office on Opening Day 2014, 28 were employed by MLB teams during the Moneyball year of 2002 (only Houston’s Jeff Luhnow and Tampa’s Andrew Friedman had yet to join the industry, working in management consulting and finance, respectively). In other words, the current crop of young, analytically inclined GMs didn’t need the book to get their start; they had broken in before it went to press. The Boston Red Sox—who embraced analytics under owner John Henry, a long-time reader of sabermetrician James—had Theo Epstein, Jed Hoyer and Ben Cherington in their front office in ’02, and Josh Byrnes and Jerry Dipoto joined a year later. All have since served as GMs.
Many execs, Ash included, point to Cleveland as an industry leader. Chris Antonetti, the Indians’ current GM, was an assistant with the team in 2002 along with Neal Huntington, who now runs the Pittsburgh Pirates.
It’s not as though all of these executives were following Beane’s lead. Some of the strategies now favoured by the likes of Hoyer and Huntington were first implemented as far back as two decades ago. It’s now common for small-market teams to pursue long-term deals with young stars, an approach that was first popularized when GM John Hart determined that he could expand Cleveland’s competitive window by locking up promising players to lengthy deals in the early 1990s. “We were running an entire crop through that were all going to hit arbitration within one or two years of each other and we never could have afforded it,” Hart said. When Beane took a similar approach, he only appeared to be on the cutting edge—he was actually following Hart’s example.
While casual fans may not have heard of advanced stats before Moneyball, some decision makers within the baseball industry were thinking critically about the game long before WAR, weighted on-base average and leverage index entered baseball’s lexicon. “There were a number of clubs that bought into that,” Ash says. “And that had to be late 1980s, early 1990s.” Bruce Manno, now an assistant GM in Atlanta, worked independently on a high-tech performance-evaluation system in the 1990s before being hired by Orioles GM Frank Wren. “We’re not doing this just for the sake of technology,” Wren said. “We’re doing it because, from an organizational standpoint, the tools are there to make you better.” Wren isn’t exactly viewed as a new-age GM, yet there he was in 1999—three years before the Moneyball A’s took the field—striving to find an edge.
Back in 1984, when Michael Lewis was still studying economics and Billy Beane was a top outfield prospect with the Mets, Pat Gillick was working closely with Ash, then the Blue Jays’ administrator of player personnel. Though he was no number cruncher, Gillick’s critical thinking helped lead the Blue Jays to five division titles, four of which were won with a red-haired, glasses-wearing platoon third baseman named Rance, who was also an on-base machine. “Pat was a sabermetrician and an analytics-type person without knowing he was,” Ash says. “It was all just naturally in his mind.”
Even in Oakland, the seeds were sown before Beane. Sandy Alderson, Beane’s predecessor with the Athletics (and current GM of the Mets), had a similar approach. The concepts were unrefined at the time, but the importance of seeking undervalued assets—the central message of Moneyball, despite the misconception that it was all about on-base percentage—was not lost on executives at the time. “In scouting conversations that would be part of the discussion,” Ash recalls. “But it just didn’t have a nice name or a title.”
That changed thanks to James, who worked not only to quantify the game but to make it accessible, publishing The Bill James Baseball Abstract as far back as 1977. Within his abstracts, James challenged long-held assumptions, such as the cost of the sacrifice bunt and the value of a walk. By the early 1990s, enterprising readers and writers started to view the game differently because of writers such as James, who has since joined Henry’s Red Sox as an advisor. While individual stats like RBI and pitcher wins can swing wildly with team performance, emerging metrics such as WAR value player contributions in isolation while accounting for home ballpark and league.
You’ll still hear managers describe pitchers as “15-game winners,” but it’s no longer surprising when the 62-year-old Ash brings up WAR in casual conversation. The Brewers even have a proprietary version of the statistic, not that they seek or obtain much recognition for their ever-expanding analytics work. These days it’s the norm for teams to produce internal metrics, initiate special studies and hire data architects in the hopes of obtaining and organizing information better than their rivals.
So when Paul DePodesta says the rise of analytics-driven decision making was “probably inevitable,” the message resonates. DePodesta, a former Indians and Athletics executive who served as the GM of the Los Angeles Dodgers before taking his current job as the Mets’ vice president of player development and scouting, was the loose inspiration for Jonah Hill’s character in the Moneyball film. He has argued that the recent abundance of data has affected just about every industry. “That explosion of information was going to impact our game one way or another,” DePodesta told FOX Sports earlier this year. “Whether we did it or not in Oakland, it was going to happen. It was a tidal wave.”
Give or take an infield shift or two, the game looks and feels the same as it did 25 years ago to a casual fan. But players are now valued differently (to the chagrin of closers and to the delight of defensive specialists).
And give the Moneyball Athletics credit. They were at the forefront of the push toward data-driven decision making and the search for undervalued assets. Without Beane’s open-minded quest for wins and Lewis’s compelling storytelling, the industry might have progressed more slowly, and the push might have taken place out of the public eye.
But it still would have taken place—James’s groundbreaking work in sabermetrics made sure of that. Moneyball or no Moneyball, analytically driven decision-making in baseball was already here to stay.
BEN NICHOLSON-SMITH IS SPORTSNET’S BASEBALL EDITOR AND A FORMER SENIOR WRITER AT MLBTRADERUMORS.COM
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