# FIFA ranking: Evaluation and path forward

arXiv: https://arxiv.org/abs/2201.00691 · HTML: https://mlsanity.com/paper/2201.00691/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 41 references that are in the map.
- First posted on arXiv 20 Dec 2021.

## Builds on (most cited first, 4 of 4)

- [Understanding predictive information criteria for Bayesian models](https://mlsanity.com/paper/1307.5928/) (2013)
- [G-Elo: Generalization of the Elo algorithm by modelling the discretized margin of victory](https://mlsanity.com/paper/2010.11187/) (2020)
- [Simplified Kalman filter for online rating: one-fits-all approach](https://mlsanity.com/paper/2104.14012/) (2021)
- [Optimizing Approximate Leave-one-out Cross-validation to Tune Hyperparameters](https://mlsanity.com/paper/2011.10218/) (2020)

## Built on by (most cited first, 2 of 2)

- [Stochastic analysis of the Elo rating algorithm in round-robin tournaments](https://mlsanity.com/paper/2212.12015/) (2022)
- [FIVB ranking: Misstep in the right direction](https://mlsanity.com/paper/2408.01603/) (2024)

## Abstract (arXiv)

In this work we study the ranking algorithm used by F'ed'eration Internationale de Football Association (FIFA); we analyze the parameters it currently uses, show the formal probabilistic model from which it can be derived, and optimize the latter. In particular, analyzing the games since the introduction of the algorithm in 2018, we conclude that the game's "importance" (as defined by FIFA) used in the algorithm is counterproductive from the point of view of the predictive capability of the algorithm. We also postulate the algorithm to be rooted in the formal modelling principle, where the Davidson model proposed in 1970 seems to be an excellent candidate, preserving the form of the algorithm currently used. The results indicate that the predictive capability of the algorithm is notably improved by using the home-field advantage and the explicit model for the draws in the game. Moderate, but notable improvement may be attained by introducing the weighting of the results with the goal differential, which although not rooted in a formal modelling principle, is compatible with the current algorithm and can be tuned to the characteristics of the football competition.