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A person-centered cluster analysis approach to the study of motivation in IEA’s Trends in International Mathematics and Science Study (TIMSS) mathematics has revealed interesting profiles of students across key motivational constructs. Between four and six different clusters were extracted from each sample analyzed. Unsurprisingly, some clusters had consistent motivation scores, but in almost every jurisdiction, there were clusters of students with inconsistent score distributions between the contributing motivational constructs. The clusters were systematically different on various external variables, such as mean mathematics achievement, gender composition, and the level of home resources available to students. The study also presents a novel way of looking at the relative importance of enjoyment of, confidence in, and value for mathematics, and the association of these motivation variables with achievement and other demographic characteristics at the cluster level. When motivation scores were mixed rather than consistent, there was a uniform achievement advantage enjoyed by the groups of students who had higher scores for confidence in mathematics over enjoyment of, or value for mathematics. This approach revealed that gender and socioeconomic background are not independent of cluster membership. Typically, clusters with high confidence values were comprised of more boys than girls, and students from better resourced homes. The findings can be linked to relevant literature on motivation in mathematics. Educational efforts to develop student motivation need to take into account differential student profiles and prioritize techniques that target skill and competence in mathematics.