Eta-squared (?[superscript 2]) and partial eta-squared (?[subscript p][superscript 2]) are effect sizes that express the amount of variance accounted for by one or more independent variables. These indices are generally used in conjunction with ANOVA, the most commonly used statistical test in second language (L2) research (Plonsky, 2013). Consequently, it is critical that these effect sizes are applied and interpreted appropriately. The present study examined the use of these two effect sizes in L2 research. We begin by outlining the statistical and conceptual foundation of and distinction between ?[superscript 2] and ?[subscript p][superscript 2]. We then review the use of these indices in a sample of published L2 research (K = 156). Among other results, we show that ?[subscript p][superscript 2] values are frequently being mislabeled as ?[superscript 2]. We interpret and discuss potential causes and consequences related to the confusion surrounding these related but distinct indices. Within the context of reform efforts in quantitative L2 research, the current study seeks to respond to the recent, pointed calls for improving study quality (Plonsky, 2014) and statistical literacy (Loewen et al., 2014) in the field.