FIVB ranking: misstep in the right direction

This work presents and evaluates the ranking algorithm that has been used by Fédération Internationale de Volleyball (FIVB) since 2020. The prominent feature of the FIVB ranking is the use of the probabilistic model, which explicitly calculates the probabilities of the future matches results using the estimated teams' strengths. Such explicit modeling is new in the context of official sport rankings, especially for multi-level outcomes, and we study the optimality of its parameters using both analytical and numerical methods. We conclude that from the modeling perspective, the current thresholds fit well the data but adding the home-field advantage (HFA) would be beneficial. Regarding the algorithm itself, we explain the rationale behind the approximations currently used and show a simple method to find new parameters (numerical score) which improve the performance. We also show that the weighting of the match results is counterproductive.

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Institutions

Publication Details

Journal
Journal of Quantitative Analysis in Sports
Published
2025-04-29
DOI
https://doi.org/10.1515/jqas-2024-0128
Citations
1
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
3.13

Funders

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article

FIVB ranking: misstep in the right direction

Daniel Gomes de Pinho Zanco, Leszek Szczeciński, Salma Tenni
1 citations
Journal of Quantitative Analysis in Sports
Sports Analytics and Performance
3.13
article

FIVB ranking: misstep in the right direction

Daniel Gomes de Pinho Zanco, Leszek Szczeciński, Salma Tenni
article en
1 citations

Abstract

This work presents and evaluates the ranking algorithm that has been used by Fédération Internationale de Volleyball (FIVB) since 2020. The prominent feature of the FIVB ranking is the use of the probabilistic model, which explicitly calculates the probabilities of the future matches results using the estimated teams' strengths. Such explicit modeling is new in the context of official sport rankings, especially for multi-level outcomes, and we study the optimality of its parameters using both analytical and numerical methods. We conclude that from the modeling perspective, the current thresholds fit well the data but adding the home-field advantage (HFA) would be beneficial. Regarding the algorithm itself, we explain the rationale behind the approximations currently used and show a simple method to find new parameters (numerical score) which improve the performance. We also show that the weighting of the match results is counterproductive.

Journal of Quantitative Analysis in SportsVol. 21(3)
Institut National de la Recherche Scientifique (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 9%
Sports Analytics and Performance
3.13
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FIVB ranking: misstep in the right direction — Daniel Gomes de Pinho Zanco, Leszek Szczeciński, et al. · Journal of Quantitative Analysis in Sports (2025) | TGRS Research Map | TGRS