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great Super Bowl squads of the 1980s. (Jeopardy luminaries recite such facts as naturally as the rest of us breathe or sweat. They can hardly help themselves.) Craig went on to win $231,200 over the course of six victories. What distinguished him more than his winnings were his methods. As a computer scientist, he used the tools of his trade to prepare for Jeopardy. He programmed himself, optimizing his own brain for the game. As the Watson team and the two human champions marched toward the matchup, each side busy devising its own strategy, Roger Craig stood at the intersection of the two domains.

Several weeks later, in mid-October, Craig sat at a pub in Newark, Delaware, discussing his methods over multiple refills of iced tea. With his broad face, wire-rimmed glasses, and a hairline in retreat, Craig looked the part of a cognitive warrior. Like many Jeopardy champions, he had spent his high school and college years in Quiz Bowl competitions and stuck with it even for the first couple of years of his graduate schooling at the University of Delaware. He originally studied biology, with the idea of becoming a doctor. But like Ferrucci, he had veered from medicine into computing. “I realized I didn’t like the sight of blood,” he said. After a short stint researching plant genomics at Dupont, he went on to study computational biology at the computer science school at Delaware. When he appeared on Jeopardy, he was within months of finishing his dissertation, which featured models of protein interactions within a cell. This, he hoped, would soon land him a lofty research post in a pharmaceutical lab or academia. But it also provided him with the know-how and the software tools for his hobby, and he easily created software to train himself for Jeopardy. “It’s nice to know how to program. You get some Perlscript,” he said, referring to a popular programming language. “Then it’s just chop, chop, chop, boom!”

Much like the researchers at IBM, Craig divided his personal Jeopardy program into steps. First, he said, he developed the statistical landscape of the game. Using sites like J! Archive, he could calculate the probability that certain categories, from European capitals to anagrams, would pop up. Mapping the Jeopardy canon, as he saw it, was simply a data challenge. “Data is king,” he said. Then, with the exacting style of a Jeopardy champ, he corrected himself. “It should be data are king, since it’s plural. Or I guess if you go to the Latin, Datum is king . . .”

The program he put together tested him on categories, gauged his strengths (sciences, NFL football) and weaknesses (fashion, Broadway shows), and then directed him toward the preparation most likely to pay off in his own match. To patch these holes in his knowledge, Craig used a free online tool called Anki, which provides electronic flash cards for hundreds of fields of study, from Japanese vocabulary to European monarchs. The program, in Craig’s words, is based on psychological research on “the forgetting curve.” It helps people find holes in their knowledge and determines how often they need those areas to be reviewed to keep them in mind. In going over world capitals, for example, the system learns quickly that a user like Craig knows London, Paris, and Rome, so it might spend more time reinforcing the capital of, say, Kazakhstan. (And what would be the Kazakh capital? “Astana,” Craig said in a flash. “It used to be Almaty, but they moved it.”)

At times, the results of Craig’s studies were uncanny. His program, for example, had directed him to polish up on monarchs. One day, looking over a list of Danish kings, he noticed that certain names repeated through the centuries. “I said, ‘OK, file that away,’” he recalled. (Psychologists call such decisions to tag certain bits of information for storage “judgments of learning.” Jeopardy players spend many of their waking hours forming such judgments.) In his third Jeopardy game, aired on September 15, Craig found himself in a tight battle with Kevin Knudson, a math professor from the University of Florida. Going