Fitting Bayesian and MLE Football Models
Bayesian Bradley-Terry-Davidson Model
Compare Football Models using Various Metrics
Plot football abilities from Stan and MLE models
Plot football matches probabilities for out-of-sample football matches...
Rank and points predictions
Round-robin for football leagues
Fit football models with Maximum Likelihood
Plot Posterior Distributions for btdFoot Objects
Plot Rankings for btdFoot Objects
Posterior predictive checks for football models
Print Method for btdFoot Objects
Print method for compareFoot objects
Print Method for stanFoot Objects
Football priors distributions and options
Fit football models using CmdStan
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. It supports both maximum likelihood estimation (MLE, for 'static' models only) and Bayesian inference. 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>.