Package: footBayes
Type: Package
Title: Fitting Bayesian and MLE Football Models
Version: 2.1.0
Date: 2026-09-07
Authors@R: c(person(given = "Leonardo",
                      family = "Egidi",
                      role = c("aut", "cre"),
                      email = "legidi@units.it"),
               person(given = "Roberto",
                      family = "Macrì Demartino",
                      role = "aut"),
               person(given = "Vasilis",
                      family = "Palaskas",
                      role = "aut"))
Maintainer: Leonardo Egidi <legidi@units.it>
License: GPL-2
Description: This is the first package allowing for the estimation,
             visualization and prediction of the most well-known
             football models: double Poisson, bivariate Poisson, Dixon-Coles,
             negative binomial, Skellam, student_t, diagonal-inflated bivariate
             Poisson, and zero-inflated Skellam. It supports both maximum likelihood
             estimation (MLE, for 'static' models only) and Bayesian inference.
             Team abilities can be static or dynamic over weeks or seasons, with
             alternative specifications of the evolution variance: a common variance
             (Owen, 2011), variance inflation after the summer break
             (Koopman and Lit, 2015) <doi:10.1111/rssa.12042>, and weighted dynamic
             models with commensurate priors
             (Macrì-Demartino, Egidi and Torelli, 2026) <doi:10.1093/jrsssc/qlag032>.
             Historical team strengths can be estimated through a Bayesian
             Bradley-Terry-Davidson model and used as a covariate.
             For Bayesian methods, it incorporates several techniques:
             MCMC sampling with Hamiltonian Monte Carlo, variational inference using
             either the Pathfinder algorithm or Automatic Differentiation Variational
             Inference (ADVI), and the Laplace approximation.
             The package compiles all the 'CmdStan' models once during installation
             using the 'instantiate' package.
             The model construction relies on the most well-known football references, such as
             Dixon and Coles (1997) <doi:10.1111/1467-9876.00065>,
             Karlis and Ntzoufras (2003) <doi:10.1111/1467-9884.00366> and
             Egidi, Pauli and Torelli (2018) <doi:10.1177/1471082X18798414>.
URL: https://github.com/leoegidi/footbayes
BugReports: https://github.com/leoegidi/footbayes/issues
Encoding: UTF-8
SystemRequirements: CmdStan
        (https://mc-stan.org/users/interfaces/cmdstan), pandoc (>=
        1.12.3), pandoc-citeproc
Depends: R (>= 4.2.0)
Imports: rstan (>= 2.18.1), instantiate, reshape2, ggplot2, ggridges,
        matrixStats, extraDistr, metRology, dplyr, tidyr, numDeriv,
        magrittr, rlang, posterior
Suggests: testthat (>= 3.0.0), knitr (>= 1.37), rmarkdown (>= 2.10),
        loo, bayesplot, cmdstanr (>= 0.6.0)
Additional_repositories: https://stan-dev.r-universe.dev/
VignetteBuilder: knitr
LazyData: true
BuildManual: yes
Config/testthat/edition: 3
Config/roxygen2/version: 8.1.0
NeedsCompilation: yes
Packaged: 2026-10-07 09:50:48 UTC; robertomacridemartino
Author: Leonardo Egidi [aut, cre],
  Roberto Macrì Demartino [aut],
  Vasilis Palaskas [aut]
Repository: CRAN
Date/Publication: 2026-10-07 12:50:28 UTC
Built: R 4.5.3; x86_64-w64-mingw32; 2026-10-07 14:19:17 UTC; windows
Archs: x64
