This package uses time dependent Poisson regression and a record of goals scored in matches to rank teams via estimated attack and defense strengths. The statistical model is based on Dixon and Coles (1997) Modeling Association Football Scores and Inefficiencies in the Football Betting Market, Applied Statistics, Volume 46, Issue 2, 265280. The package has a some webscrapers to assist in the development and updating of a match database. If the match database contains unconnected clusters (i.e. sets of teams that have only played each other and not played teams from other sets), each cluster is ranked separately relative to the median team strength in the cluster. The package contains functions for predicting and simulating tournaments and leagues from estimated models. The package allows fitting via the glm(), speedglm(), and glmnet() functions. The latter allows fast and efficient fitting of very large numbers of teams. The fitting algorithm will analyze the match data and determine which teams form a cluster (a set of teams where there is a path of matches connecting every team) and fit each cluster separately.
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Author  Eli Holmes 
Date of publication  20131023 07:59:42 
Maintainer  E Holmes <eeholmes@u.washington.edu> 
License  GPL2 
Version  2.0 
URL  http://www.lastplanetranking.blogspot.com/ 
Package repository  View on CRAN 
Installation  Install the latest version of this package by entering the following in R:

Functions  

B00.founders  Man page 
B00.scores  Man page 
B00.teams  Man page 
coef  Man page 
coef.fbRanks  Man page Source code 
construct.team.file  Man page Source code 
create.fbRanks.dataframes  Man page Source code 
create.newdata.dataframe  Man page Source code 
detect.normality.outliers  Man page Source code 
edit_team_data  Man page Source code 
fbRanks  Man page 
plot  Man page 
plot.fbRanks  Man page Source code 
predict  Man page 
predict.fbRanks  Man page Source code 
Man page  
print.fbRanks  Man page Source code 
rank.teams  Man page Source code 
residuals  Man page 
residuals.fbRanks  Man page Source code 
resolve.team.names  Man page Source code 
scale.for.ranks  Man page Source code 
scrape.custom1  Man page Source code 
scrape.custom2  Man page Source code 
scrape.custom3  Man page Source code 
scrape.custom4  Man page Source code 
scrape.demosphere  Man page Source code 
scrape.demosphere.main  Man page Source code 
scrape.gotsport  Man page Source code 
scrape.gotsport.main  Man page Source code 
scrape.json1  Man page Source code 
scrape.korrio  Man page Source code 
scrape.matches  Man page 
scrape.scoreboard  Man page Source code 
scrape.sportaffinity  Man page Source code 
scrape.sportaffinity.brackets  Man page Source code 
scrape.sportaffinity.main  Man page Source code 
scrape.usclub  Man page Source code 
simulate  Man page 
simulate.fbRanks  Man page Source code 
str_proper  Man page Source code 
str_remove  Man page Source code 
str_remove.nonascii  Man page Source code 
str_remove.nonascii.2  Source code 
str_strip.white  Man page Source code 
team.and.score.filters  Man page Source code 
team.name.select  Man page Source code 
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