footBayes 0.1.0 is on CRAN! The goal of the package is to propose a complete workflow to:

– fit the most well-known football (soccer) models: double Poisson, bivariate Poisson, Skellam, student t through the maximum likelihood approach and HMC Bayesian methods using Stan;

– visualize the teams’ abilities, the model pp checks, the rank-league reconstruction;

– predict out-of-sample matches via the pp distribution.

Here a super quick use of the package for the Italian Serie A. For any detail, check out the vignette and enjoy!

p.s. the vignette has been compiled without plot rendering to save time during the CRAN submission

library(footBayes)
require(engsoccerdata)
require(dplyr)

# dataset for Italian serie A

italy <- as_tibble(italy)
italy_2000_2002<- italy %>%
   dplyr::select(Season, home, visitor, hgoal, vgoal) %>%
   dplyr::filter(Season=="2000" | Season=="2001" | Season =="2002")

fit1 <- stan_foot(data = italy_2000_2002,
                  model="double_pois",
                  predict = 36) # double poisson fit (predict last 4 match-days)
foot_abilities(fit1, italy_2000_2002) # plot teams abilities
pp_foot(italy_2000_2002, fit1)   # pp checks
foot_rank(italy_2000_2002, fit1) # rank league reconstruction
foot_prob(fit1, italy_2000_2002) # out-of-sample posterior pred. probabilities