Modeling population-level evolutionary dynamics is one of the oldest, and most enduring forms of mathematical biology. Key to many of these models is the notion of different strains having different ''fitnesses,'' which represents their net competitive advantages in the environment. For example, in lymph nodes, we know that B cells have a competitive advantage when they can successfully neutralize pathogens. However, reducing this advantage to a singular 1D fitness is misleading, since there may be multiple mechanisms that lead to this advantage. Three simple, potential selection methods include encouraging the reproduction of high affinity cells (''birth selection''), encouraging cell death in low affinity cells (''death selection''), and adjusting the mutation rate based on cell affinity (''mutational selection''). Moreover, multiple methods can be active at the same time, and while all three forms of selection would lead to a net increase in affinity, different selection methods lead to distinct statistical outcomes. We discuss ramifications of different evolutionary models, and encourage thinking about evolutionary fitness as more than a singular number.