# Understanding team collapse via probabilistic graphical models

arXiv: https://arxiv.org/abs/2402.10243 · HTML: https://mlsanity.com/paper/2402.10243/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 39 references that are in the map.
- First posted on arXiv 14 Feb 2024.

## Builds on (most cited first, 2 of 2)

- [Actions Speak Louder Than Goals: Valuing Player Actions in Soccer](https://mlsanity.com/paper/1802.07127/) (2018)
- [Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball](https://mlsanity.com/paper/1401.0942/) (2014)

## Abstract (arXiv)

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.