A triumph of data: How Ted Cruz engineered his victory in Iowa

Wilson swiftly recalibrated the challenge as a matter of numbers. On his phone, he summoned a report that counted 9,131 individual Iowans whom Wilson’s statistical models had identified as choosing between the two leading candidates. Those people existed at the overlap of likely caucus-goers who were seen as considering both Cruz and Trump; anyone who also ranked Marco Rubio highly was pushed out of the group. “These aren’t people you want to contrast with Trump and push to Rubio,” explained Wilson. (There were, separately, 6,309 voters then choosing between Cruz and Rubio but not Trump.) Those who remained were a remarkably homogeneous group: 91 percent male, two-thirds of them likely to self-associate as evangelical Christians.

For the closing days of the Iowa campaign, Cruz’s campaign had defined such pools for each of his major opponents as part of what was known internally as the Oorlog Project, named by a Cruz data scientist who searched online for “war” translated into different languages and thought the Afrikaner word looked coolest. It was just the latest way that Cruz’s analytics department had tried to slice the Iowa caucus electorate in search of an advantage for its candidate. They had divided voters by faction, self-identified ideology, religious belief, personality type—creating 150 different clusters of Iowa caucus-goers—down to sixty Iowa Republicans its statistical models showed as likely to share Cruz’s desire to end a state ban on fireworks sales.