Can Moneyball statistics be used to beat Jeopardy?
NPR covers the fascinating story of Roger Craig, a PhD in computer science, who used data-mining and statistics to make hundreds of thousands of dollars on Jeopardy:
Using data-mining and text-clustering techniques, Craig grouped questions by category to figure out which topics were statistically common — and which weren’t.
“Obviously it’s impossible to know everything,” Jones says. “So he was trying to decide: What things did he need to know? He prepared himself in a way that I think is probably more rigorous than any other contestant.”
Once he’d calculated the odds a category would come up, Craig quizzed himself on a variety of questions to find the gaps in his own knowledge.
But Craig says it’s a fallacy for game-show candidates to think they need to know everything.
“They want to learn every capital of every county in the world. And you really don’t need to,” he says. “Instead, you need to know the 80 percent people have heard of.”
That’s because the show, he says, isn’t written for the contestants. It’s written for the people playing along at home, who need to feel they have a fighting chance to keep up.
Craig won $250,000 in the Tournament of Champions. He later told his fellow Tournament of Champion contestants about his system. One playfully ribbed him for cheating. Craig is quick to attack anyone who levels the accusation seriously.
“Everybody that wants to succeed at a game is going to practice at the game,” he says. “You can practice haphazardly, or you can practice efficiently. And that’s what I did.”
He discusses his system here:
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