Statistical control of extraneous (i.e., third) variables is a common analytic tool among leadership researchers. While such a strategy is typically assumed to prove beneficial, it can actually introduce various complications that are underestimated or even ignored. This study investigates and summarizes the current state of control variable usage in leadership research by qualitatively and quantitatively examining the use of statistical control variables in 10 highly regarded management and applied psychology journals. Despite available “best practices,” our results indicate that control variable usage in existing leadership studies is rarely grounded in theory but instead frequently relies on outdated misconceptions. Moreover, a meta-analysis of the relationships between popular control variables and leadership constructs finds nearly universal weak effect sizes, suggesting that many studies may not only be losing valuable degrees of freedom but also making inferences based on biased parameter estimates. To address these issues, we put forth a number of recommendations to assist leadership scholars with determining whether potential third variables should be controlled for in their leadership research.