Probabilities from bookmaker odds are often used in measures of short-run outcome uncertainty. We analyzed the most commonly used methods for deriving probability forecasts from odds and found that basic normalization (BN) produces biased probabilities. Furthermore, differences between probabilities produced with BN, regression models, or Shin probabilities are large enough to lead to contradictory conclusions when used to measure outcome uncertainty. We also provide evidence against the reported bias of bookmakers favoring better supported teams and show how past evidence of such a bias is possibly only due to a misinterpretation of the results.