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footBayes  

Fitting Bayesian and MLE Football Models
View on CRAN: Click here


Download and install footBayes package within the R console
Install from CRAN:
install.packages("footBayes")

Install from Github:
library("remotes")
install_github("cran/footBayes")

Install by package version:
library("remotes")
install_version("footBayes", "2.0.0")



Attach the package and use:
library("footBayes")
Maintained by
Leonardo Egidi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-02-21
Latest Update: 2025-05-16
Description:
This is the first package allowing for the estimation, visualization and prediction of the most well-known football models: double Poisson, bivariate Poisson, Skellam, student_t, diagonal-inflated bivariate Poisson, and zero-inflated Skellam. The package allows Hamiltonian Monte Carlo (HMC) estimation through the underlying Stan environment and Maximum Likelihood estimation (MLE, for 'static' models only). The model construction relies on the most well-known football references, such as Dixon and Coles (1997) , Karlis and Ntzoufras (2003) and Egidi, Pauli and Torelli (2018) .
How to cite:
Leonardo Egidi (2022). footBayes: Fitting Bayesian and MLE Football Models. R package version 2.0.0, https://cran.r-project.org/web/packages/footBayes. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.1.0 (2022-02-21 09:20), 0.2.0 (2023-08-31 16:50), 1.0.0 (2025-01-09 16:20)
Other packages that cited footBayes R package
View footBayes citation profile
Other R packages that footBayes depends, imports, suggests or enhances
Complete documentation for footBayes
Functions, R codes and Examples using the footBayes R package
Some associated functions: england . foot_abilities . foot_prob . foot_rank . foot_round_robin . italy . mle_foot . pp_foot . priors . stan_foot . 
Some associated R codes: england.R . foot_abilities.R . foot_priors.R . foot_prob.R . foot_rank.R . foot_round_robin.R . globals.R . italy.R . mle_foot.R . pp_foot.R . stan_foot.R .  Full footBayes package functions and examples
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