Momentum matters: Investigating high-pressure situations in the NBA through scoring probability

One of the defining characteristics of real basketball stars, and even great role players, is how well they perform under immense mental pressure. In this paper, we present a method to identify high-pressure situations during a basketball game through shooting success. In order to calculate the amount of pressure a team is facing going into a game, we use a prediction model to determine the importance of the given game for that team to reach their end-of-season goal. The model relies on features referring to game context, recent form, and pre-season aspirations. We then investigate the impact of our pre-game pressure metric, along with other factors, on the shooting performance of NBA players on six seasons` worth of data. We find that shotmaking in the NBA is mainly impacted by the so-called momentum, i.e., when a team outscores their opponent significantly over a short period of time.
© Copyright 2024 Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science. Published by Springer. All rights reserved.

Bibliographic Details
Subjects:
Notations:sport games social sciences
Published in:Machine Learning and Data Mining for Sports Analytics. MLSA 2023. Communications in Computer and Information Science
Language:English
Published: Cham Springer 2024
Series:Communications in Computer and Information Science, 2035
Online Access:https://doi.org/10.1007/978-3-031-53833-9_7
Pages:77-90
Document types:article
Level:advanced