I was looking for something like baseball, where there’s a lot of data and the competition was pretty low. That’s when I discovered politics.

Silver is describing the strategic logic behind his move from sports analytics into election forecasting. He frames politics as an arena with abundant quantitative information—polls, demographics, fundraising, historical voting patterns—yet, at the time, relatively few practitioners applying rigorous statistical modeling. The comparison to baseball evokes the sabermetrics revolution: when data is plentiful and analytical methods are underused, a skilled modeler can gain an outsized edge. The line also carries a mild provocation—“competition was pretty low”—suggesting that political punditry often relied more on narrative and intuition than on disciplined probabilistic reasoning, creating an opening for data-driven forecasting.