Summary of Fivb Ranking: Misstep in the Right Direction, by Salma Tenni et al.
FIVB ranking: Misstep in the right direction
by Salma Tenni, Daniel Gomes de Pinho Zanco, Leszek Szczecinski
First submitted to arxiv on: 2 Aug 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents an evaluation of the ranking algorithm used by FIVB since 2020, focusing on its probabilistic model that calculates game probabilities explicitly. The authors analyze the algorithm’s parameters using analytical and numerical methods, concluding that incorporating home-field advantage (HFA) would be beneficial. They also propose a simplified implementation and interpretation of the algorithm, improving its performance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how to rank teams in volleyball more accurately. It uses math to understand how the current ranking system works and finds ways to make it better. The team behind the FIVB’s ranking system has been using a special model that predicts game outcomes since 2020. This paper investigates this model and suggests changes to make it even more effective. |
Keywords
* Artificial intelligence * Probabilistic model
