FIVB ranking: Misstep in the right direction

TL;DR

This paper analyzes the FIVB volleyball ranking algorithm, highlighting its probabilistic modeling approach, evaluating its parameters, and proposing improvements such as incorporating home-field advantage and adjusting match result weighting.

Contribution

It introduces a probabilistic model for sports rankings, evaluates its parameters, and suggests enhancements like including home-field advantage and optimizing match result weighting.

Findings

Current thresholds fit data well

Adding home-field advantage improves model

Weighting match results may be counterproductive

Abstract

This work presents and evaluates the ranking algorithm that has been used by Federation 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.