ranked these SLOEs in order of competitiveness based on the SLOE information alone. Consensus was evaluated using cutoffs established a priori, and two prediction models, a point-based system and linear regression model, were tested to determine their ability to predict faculty consensus rankings.Results: We found strong faculty consensus regarding the competitiveness of SLOEs. Within narrow windows of agreement, the majority of faculty demonstrated similar ranking patterns with 83% and 93% agreement for "close" and "loose" agreement, respectively. Predictive models yielded strong correlation with the consensus ranking (point-based system r=0.97, linear regression r=0.97).Conclusions: Faculty displayed strong consensus regarding competitiveness of SLOEs, adding validity evidence to the use of SLOEs for selection and advising. Additionally, two models predicted consensus competitiveness rankings with a high degree of accuracy. These models could potentially be used to inform applicant competitiveness at scale in an effort to curb overapplication and aid future mentorship practices.