High Chances and Close Margins: How Equivalent Forecasts Yield Different Beliefs

Abstract

Statistical forecasts are increasingly prevalent. How do forecasts affect people’s beliefs about corresponding future events? This research proposes that the format in which the forecast is communicated biases its interpretation. We contrast two common forecast formats: chance (e.g., the forecasted probability that a political candidate or a sports team will win) versus margin (e.g., by how many points a political candidate or a sportsteam is forecasted to win). Across five studies(total N=2,486; plus nine replications with an additional total N=2,420), we find a robust chance-margin discrepancy: chance forecasts lead to more extreme beliefs about outcome occurrence than margin forecasts. This discrepancy persists over time in interpreting real-world forecasts (e.g., the 2016 U.S. presidential election), replicates even when the forecasts are strictly statistically equivalent, and has downstream consequences for attitudes toward election candidates and sports betting decisions. Lastly, we discuss the implications for mass communications and gerrymandered redistricting.