After fitting a model with mvglmmRank, game.pred uses that model to predict outcomes of future matchups.
Usage
game.pred(res, home, away, neutral.site = FALSE)
Arguments
res
an object of class mvglmmRank
home
a character string for the home team (use quotation marks!)
away
a character string for the away team (use quotation marks!)
neutral.site
logical. If TRUE, uses the neutral site mean score, assuming some of the games in the training data occured at neutral sites.
Value
Prints predicted scores and/or predicted probability of a home team win, depending on the type of model specified by res.
Author(s)
Andrew T. Karl and Jennifer Broatch
References
Karl, A.T., Broatch, J. (2014). mvglmmRank: An R Package Providing Multivariate Generalized Linear Mixed Models for Evaluating Sporting Teams. Submitted.
Karl, A.T., Yang, Y. and Lohr, S. (2013). Efficient Maximum Likelihood Estimation of Multiple Membership Linear Mixed Models, with an Application to
Educational Value-Added Assessments. Computational Statistics and Data Analysis, 59, 13-27.
Karl, A., Yang, Y. and Lohr, S. (2014) Computation of Maximum Likelihood Estimates for Multiresponse Generalized Linear Mixed Models with Non-nested, Correlated Random Effects Computational Statistics & Data Analysis73, 146–162.
Karl, A.T. (2012). The Sensitivity of College Football Rankings to Several Modeling Choices, Journal of Quantitative Analysis in Sports,
Volume 8, Issue 3, DOI 10.1515/1559-0410.1471
Examples
data(nfl2012)
mvglmmRank(nfl2012,method="PB0",first.order=TRUE,verbose=TRUE,max.iter.EM=1)
result <- mvglmmRank(nfl2012,method="PB0",first.order=TRUE,verbose=TRUE)
print(result)
game.pred(result,home="Denver Broncos",away="Green Bay Packers")