One of the defining characteristics of real basketball stars, and even great role players, is how well they perform under immense mental pressure. This paper presents a method to identify high-pressure situations during a basketball game through shooting success. Our analysis incorporates a novel feature set that emphasizes both player- and team-level momentum, including scoring streaks. Additionally, we redefine player roles using a clustering-based approach with deep learning techniques, allowing for a more nuanced evaluation of performance under pressure. Using six seasons of NBA data, we find that shotmaking is mainly impacted by the so-called momentum, i.e., when a team outscores their opponent significantly over a short period of time.
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