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Statistical analysis helped the Oakland Athletics land five playoff appearances in the last eight years, despite working with one of the smallest payrolls in Major League Baseball. Photo: iStock
Ask The Professor
What is sabermetrics and why do baseball teams care so much about it?
Peter Bendix, A08, who taught “The Business of Baseball” at the Ex College and is currently a Tampa Bay Rays baseball operations intern, answers this month’s question:
Sabermetrics is often defined as the objective study of baseball by means of statistics. The term was created by Bill James as homage to the Society of American Baseball Research—SABR. James, who currently works for the Red Sox, began publishing books on the subject in the late 1970s. But sabermetrics didn’t gain mainstream attention until Michael Lewis’ book Moneyball was published in 2003. Lewis chronicled the exploits of Oakland Athletics General Manager Billy Beane, who has used statistical analysis to guide the Athletics to five playoff appearances in the last eight years, despite working with one of the smallest payrolls in Major League Baseball.
Sabermetrics has taken several long-held pieces of conventional wisdom about baseball and turned them on their heads. Take batting averages. For years most people understood the batting average—how many hits a player has in his at bats—to be the best way of evaluating hitters. But statistical research proved it isn’t. That’s because every time a batter steps to the plate, there are two possible outcomes: he makes an out or he gets on base. Batting average is incomplete because it does not address the walk. The game is only over after each team makes 27 outs, so the most important job for any ball player is not to make an out and put runners on base.
The batting average treats every hit as equally valuable. Anyone who has ever watched baseball can you tell you that a double is more valuable than a single, and a home run is more valuable than either. But according to batting average, a player who gets 100 singles is the same as a player with 50 homers and 50 doubles. It’s obvious that the second player has done a lot more to help his team.
Rather than rely on batting average to evaluate hitters, sabermetrics espouses on-base percentage and slugging percentage. On-base percentage is a more complete version of batting average: it measures the rate players avoid making outs—the percentage of time they either get a hit or walk. Slugging percentage weighs every type of hit—home run, triple, double and single—differently, thus allowing players who have more extra base hits to be valued appropriately.
One of the most common new-school ways of evaluating players is a simple combination of on-base percentage and slugging percentage, called on-base plus slugging, or OPS. The higher the OPS, the better the hitter. OPS isn’t perfect, but it is a much better measure of a hitter than a simple batting average.
Different teams use sabermetrics in different ways. Some, like the Oakland Athletics, weigh statistical analysis heavily in all of their decision-making. Other teams, like the Minnesota Twins, put less emphasis on statistics. Still other teams, like the Red Sox, prefer a blend of both old-school scouting analysis and new-school statistical analysis. And, of course, it’s very difficult for an outsider to gauge just how much any team uses statistics in its decision-making process.
There is no one secret to building a winning baseball team. But statistical analysis has gained inroads in baseball front offices, and is another source of important information in an industry in which knowledge translates into a competitive advantage.
