Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper explores the classic beauty premium paradigm in the eSports Overwatch League. Using two-step probit selection models and unsupervised machine learning algorithms, we find that professional gamers rated as more attractive are more likely to receive a contract in the following year, controlling for productivity and other factors. However, there is no apparent lifetime earnings premium. Regression and cluster analyses reveal that it is not enough to be a good player – the inter-relatedness of productivity, attractiveness, and popularity on social media dictates employability. Looking at the league's wealthiest, most successful, and most appealing teams, we find that attractiveness on its own is a negative predictor of getting hired.