The accuracy-based classifier system XCS is currently the most successful learning classifier system. Several recent studies showed that XCS can produce machine-learning competitive results. Nonetheless, until now the evolutionary mechanisms in XCS remained somewhat ill-understood. This study investigates the selectorecombinative capabilities of the current XCS system. We reveal the accuracy dependence of XCS’s evolutionary algorithm and identify a fundamental limitation of the accuracy-based fitness approach in certain problems. Implications and future research directions conclude the paper.