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Out on the Data Frontier
Tom Verducci
April 05, 2004
Where will the numbers game go in the future? Beyond hitting and pitching
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April 05, 2004

Out On The Data Frontier

Where will the numbers game go in the future? Beyond hitting and pitching

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In the winter of 2002-03, his first shopping season as general manager of the Red Sox, Theo Epstein found himself competing against Athletics G.M. Billy Beane for the services of an injury-prone first baseman who was about to turn 28, who still had not reached 50 RBIs or 250 at bats in a major league season, and whom the Diamondbacks were eager to dump. Erubiel Durazo hardly seemed a prized commodity. Both G.M.'s, however, coveted him because of his efficiency statistics—a .390 career on-base percentage and a .528 career slugging percentage—not to mention his affordability. (He earned $375,000 in 2002 and $1,065 million last year.)

Beane beat out Epstein for Durazo, constructing a four-team trade with the help of his friend, former assistant and statistically like-minded general manager J.P Ricciardi of Toronto. ( Beane gave the Blue Jays a pitching prospect, Jason Arnold, in the deal. Durazo, in his first full season, hit .259 with 21 homers and 77 RBIs, and had a .374 OBP and a .430 slugging percentage.) "All of us," Beane says of himself, Epstein and Ricciardi, "are swimming in the same waters."

Those sabermetric waters will only become more crowded this season, as teams such as the Dodgers, Mets, Indians and Cardinals begin to rely more on quantitative analysis. As additional teams take the plunge and once obscure statistics become mainstream, where will G.M.'s mine next?

"You can keep looking deeper and deeper into [hitting and pitching] statistics," Toronto assistant G.M. Keith Law says, "until you start to bump against the wall in terms of what is really useful. We're just about there. But I do think we can be better in other areas as opposed to going deeper into what we already know."

According to executives, these are the new frontiers of quantitative analysis:

?DEFENSE
Several statistical models already are in use to quantify defensive ability, though none has gained universal acceptance. "I'm working on one of my own," Law says. "The others are O.K., but I haven't seen anything yet that really hits the mark. I don't believe, for instance, that defense fluctuates wildly from one year to the next, so I have a hard time believing that Rich Aurilia can come up in one model as a minus-20 one year and plus-five the next. A lot of it depends on the input data being flawed. The base hit just out of the reach of the shortstop, for instance. Was it hit hard, a single all the way, or was it a three-hopper?"

?CHARACTER

"There are probably some things we can learn from the NFL," Ricciardi says. For instance, the pro football league has long relied on personal interviews and the Wonderlic test—a measure of intelligence, cognitive ability and problem-solving skills—to evaluate prospective draft picks. The Rockies, Indians and Orioles are among teams trying to identify high-character players. Colorado, for instance, put together an exhaustive report on high school third baseman Ian Stewart, which included personality exams and lengthy interviews with his amateur coaches, before taking him in the first round of the 2003 draft. "We talk all the time in baseball about a player's ability to handle failure," Rockies G.M. Dan O'Dowd says, "when a lot of times in the big leagues you need to be more concerned with how a player handles success."

Says Dodgers G.M. Paul DePodesta, "We have more than a thousand players to consider for the draft. We're not going to run psychological profiles on all, but we could do it with the top 50 or so."

?INJURIES
At what point in their careers do catchers begin to wear down? Do shortstops and centerfielders become less productive in their mid-30s than players at corner positions? Are pitchers who throw sliders more at risk of injury? Those and many other questions related to managing injury-related investment risk could be addressed by a kind of actuarial table created from a database of injury information. "What's going on now, especially when it comes to keeping pitchers healthy, is a lot of guesswork," Law says. "We still don't know whether it's worse for a pitcher to throw 130 pitches in a complete game or 100 pitches over five innings."

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