Models for preferences, established through the ranking of the options according to isolated factors, are developed here. Randomization of ranks allows us to compute the probability of each option be raised to the position of best choice. It is verified that, in horses races, measures of preference built through odds of the options to hold the first position according to some criterion or to a combination of criteria are more correlated with the measure of preference given by the final betting distribution than those given directly by the ranks.
random ranks; modeling preferences; multicriteria decision analysis
