tennis {hyper2}

Match outcomes from repeated doubles tennis matches

Description

Match outcomes from repeated doubles tennis matches

Usage

data(tennis)

Format

A hyper2 object corresponding to the match outcomes listed below.

Details

There are four players, p_1 to p_4. These players play doubles tennis matches with the following results:

match	score
\lbrace p_1,p_2\rbrace vs \lbrace p_3,p_4\rbrace	9-2
\lbrace p_1,p_3\rbrace vs \lbrace p_2,p_4\rbrace	4-4
\lbrace p_1,p_4\rbrace vs \lbrace p_2,p_3\rbrace	6-7
\lbrace p_1\rbrace vs \lbrace p_3\rbrace	10-14
\lbrace p_2\rbrace vs \lbrace p_3\rbrace	12-14
\lbrace p_1\rbrace vs \lbrace p_4\rbrace	10-14
\lbrace p_2\rbrace vs \lbrace p_4\rbrace	11-10
\lbrace p_3\rbrace vs \lbrace p_4\rbrace	13-13

It is suspected that p_1 and p_2 have some form of team cohesion and play better when paired than when either solo or with other players. As the scores show, each player and, apart from p1-p2, each doubles partnership, is of approximately the same strength.

Dataset tennis gives the appropriate likelihood function for the players' strengths; and dataset tennis_ghost gives the appropriate likelihood function if the extra strength due to team cohesion of \lbrace p_1,p_2\rbrace is represented by a ghost player.

These objects can be generated by running script inst/tennis.Rmd, which includes some further discussion and technical documentation and creates file tennis.rda which resides in the data/ directory.

Source

Doubles tennis matches at NOCS, Jan-May 2008

References

Robin K. S. Hankin (2010). “A Generalization of the Dirichlet Distribution”, Journal of Statistical Software, 33(11), 1-18

Examples

summary(tennis)

tennis |> psubs(c("Federer","Laver","Graf","Navratilova"))

## Following line commented out because it takes too long:
# specificp.gt.test(tennis_ghost,"G",0)