rate_colley(cr_data) rank_colley(cr_data, keep_rating = FALSE, ties = c("average", "first", "last", "random", "max", "min"), round_digits = 7)
Competition results in format ready for as_longcr().
Whether to keep rating column in ranking output.
This rating method was initially designed for games between two
players. There will be an error if in
cr_data there is a game not between
two players. Convert input competition results manually or with
It is assumed that score is numeric and higher values are better for the player.
Computation is done based only on the games between players of interest (see
Players). Note that it isn't necessary for all players of interest to be
cr_data but it might be a good idea in order to obtain plausible
The outline of the Colley method is as follows:
Compute Colley matrix: diagonal elements are equal to number of games played by certain player plus 2, off-diagonal are equal to minus number of common games played. This matrix will be the matrix of system of linear equations (SLE).
Compute right-hand side of SLE as 1 + 0.5*("number of player's wins" - "number of player's losses").
Solve the SLE. The solution is the Colley rating.
comperank offers a possibility to handle certain set of players. It is done
player column (in longcr format) as factor
with levels specifying all players of interest. In case of factor the result
is returned only for players from its levels. Otherwise - for all present
Wesley N. Colley (2002) Colley’s Bias Free College Football Ranking Method: The Colley Matrix Explained. Available online at http://www.colleyrankings.com
rate_colley(ncaa2005)#> # A tibble: 5 x 2 #> player rating_colley #> <chr> <dbl> #> 1 Duke 0.214 #> 2 Miami 0.786 #> 3 UNC 0.5 #> 4 UVA 0.357 #> 5 VT 0.643rank_colley(ncaa2005)#> # A tibble: 5 x 2 #> player ranking_colley #> <chr> <dbl> #> 1 Duke 5 #> 2 Miami 1 #> 3 UNC 3 #> 4 UVA 4 #> 5 VT 2rank_colley(ncaa2005, keep_rating = TRUE)#> # A tibble: 5 x 3 #> player rating_colley ranking_colley #> <chr> <dbl> <dbl> #> 1 Duke 0.214 5 #> 2 Miami 0.786 1 #> 3 UNC 0.5 3 #> 4 UVA 0.357 4 #> 5 VT 0.643 2