How did statistics let a poor baseball team take on the rich?

Statistics changed baseball by showing that the numbers everyone trusted were measuring the wrong thing. For a century, teams judged hitters mainly by batting average: hits divided by at-bats. But games are won by runs, not hits, and a player's value to run-scoring tracks closely how often he gets on base at all, including walks. A hitter who draws lots of walks reaches base far more often than his batting average shows. Because the market priced players by the old numbers, players like that came cheap.

Much of this thinking began with a man doing night shifts as a security guard at a pork and beans cannery. Bill James's articles were so unusual that editors wouldn't run them, so in 1977 he self-published a Baseball Abstract full of statistics. He named the approach sabermetrics, after the Society for American Baseball Research. He even gave teams a formula, the Pythagorean expectation, that predicts how often a team should win from just the runs it scores and allows.

The Oakland Athletics turned the idea into a business plan. In 2002, with a payroll of $44 million, they competed with the New York Yankees, who spent more than $125 million, by hunting players who were undervalued in the market. Michael Lewis told the story in Moneyball in 2003. The twist is that the book helped kill the advantage: once rival teams adopted the same methods, Oakland's edge shrank. And critics note that the 2002 A's also relied on stars found by old-fashioned scouts.