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from others, had created a system of perverse incentives for anyone who trotted out onto a baseball field. The fetish made of “runs batted in” was another good example of the general madness. RBI had come to be treated by baseball people as an individual achievement—free agents were paid for their reputation as RBI machines when clearly they were not. Big league players routinely swung at pitches they shouldn’t to lard their RBI count. Why did they get so much credit for this? To knock runners in, runners needed to be on base when you came to bat. There was a huge element of luck in even having the opportunity, and what wasn’t luck was, partly, the achievement of others. “The problem,” wrote James, “is that baseball statistics are not pure accomplishments of men against other men, which is what we are in the habit of seeing them as. They are accomplishments of men in combination with their circumstances.”

The failure of baseball people to acknowledge that fact in their statistics led to exactly the sort of moral corruption Henry Chadwick, in creating them, had sought to eliminate. The many little injustices and misunderstandings embedded in the game’s records spawned exotic inefficiencies. Baseball strategies were often wrongheaded and baseball players were systematically misunderstood. Chadwick succeeded in creating a central role for statistics in baseball, but in doing it he created the greatest accounting scandal in professional sports.

Between Chadwick and James there had been fitful efforts to rethink old prejudices. The legendary GM Branch Rickey employed a professional statistician named Allan Roth who helped to compose an article under Rickey’s byline in Life magazine in 1954 that argued for the importance of on-base and slugging percentages over batting average. A professor of mechanical engineering at Johns Hopkins, Earnshaw Cook, wrote two pompous books, in prose crafted to alienate converts, that argued for the relevance of statistical analysis in baseball. In the early 1960s, a pair of brothers employed by IBM used the company’s computers to analyze baseball strategies and players. But the desire to use statistics to make baseball efficient—to measure and value precisely the events that occur on a baseball field, to give the numbers new powers of language—only became potent when it became practical.

When Bill James published his 1977 Baseball Abstract, two changes were about to occur that would make his questions not only more answerable but also more valuable. First came radical advances in computer technology: this dramatically reduced the cost of compiling and analyzing vast amounts of baseball data. Then came the boom in baseball players’ salaries: this dramatically raised the benefits of having such knowledge. “If we’re going to pay these guys $150,000 a year to do this,” James concluded in his essay on fielding, “we should at least know how good they are—which means knowing how much they allowed in the field just as much as it means knowing how much they created at bat.” If this sounded compelling when baseball players were paid $150,000 a year, it sounded one hundred times more so when they were paid $15 million a year.

James’s first proper essay was the preview to an astonishing literary career. There was but one question he left unasked, and it vibrated between his lines: if gross miscalculations of a person’s value could occur on a baseball field, before a live audience of thirty thousand, and a television audience of millions more, what did that say about the measurement of performance in other lines of work? If professional baseball players could be over-or undervalued, who couldn’t? Bad as they may have been, the statistics used to evaluate baseball players were probably far more accurate than anything used to measure the value of people who didn’t play baseball for a living.

Still, had he left off writing in 1977, James would have been dismissed as just another crank who didn’t know when to shut up about box scores. He didn’t leave off in 1977. It didn’t occur to him to be disappointed by