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FIVB ranking: misstep in the right direction.
Salma Tenni1, Daniel Gomes de Pinho Zanco2, Leszek Szczecinski2
1INRS and McGill, Quebec, Canada.
Journal of Quantitative Analysis in Sports
|August 8, 2025
Summary
The Fédération Internationale de Volleyball (FIVB) ranking algorithm uses a novel probabilistic model. While current parameters are adequate, incorporating home-field advantage and refining the numerical score could enhance its performance for FIVB volleyball rankings.
Area of Science:
- Sports Analytics
- Probabilistic Modeling
- Ranking Systems
Background:
- Official sports rankings often lack sophisticated probabilistic models.
- The Fédération Internationale de Volleyball (FIVB) introduced a new ranking algorithm in 2020.
- Existing models may not fully capture the complexities of multi-level match outcomes.
Purpose of the Study:
- To evaluate the performance and parameters of the FIVB's 2020 ranking algorithm.
- To explore potential improvements for the FIVB ranking system.
- To analyze the effectiveness of probabilistic modeling in sports rankings.
Main Methods:
- Analytical and numerical methods were employed to study parameter optimality.
- The study assessed the existing FIVB ranking algorithm's probabilistic model.
- Investigated the impact of home-field advantage and alternative parameterization.
Main Results:
- The current thresholds in the FIVB model demonstrate a good fit with the data.
- Adding a home-field advantage (HFA) parameter is recommended for model improvement.
- A simple method for finding new parameters (numerical score) can enhance algorithm performance.
- Weighting match results was found to be counterproductive.
Conclusions:
- The FIVB ranking algorithm's probabilistic approach is innovative for sports.
- Model enhancements, such as including HFA and optimizing parameters, are suggested.
- The current weighting strategy for match results should be reconsidered.
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