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Understanding team collapse via probabilistic graphical models

2024-02-14Code Available0· sign in to hype

Iasonas Nikolaou, Konstantinos Pelechrinis, Evimaria Terzi

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Abstract

In this work, we develop a graphical model to capture team dynamics. We analyze the model and show how to learn its parameters from data. Using our model we study the phenomenon of team collapse from a computational perspective. We use simulations and real-world experiments to find the main causes of team collapse. We also provide the principles of building resilient teams, i.e., teams that avoid collapsing. Finally, we use our model to analyze the structure of NBA teams and dive deeper into games of interest.

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