Common Head-to-Head functions

Source: R/head-to-head.R

List of commonly used functions for computing Head-to-Head values.

h2h_funs

Format

An object of class list of length 9.

Details

h2h_funs is a named list of expressions representing commonly used expressions of Head-to-Head functions for computing Head-to-Head values with h2h_long() or h2h_mat(). Names of the elements will be used as Head-to-Head value names. To use them inside h2h_long() or h2h_mat() use unquoting mechanism from rlang package.

Currently present functions:

  • mean_score_diff - computes mean score difference of player1 compared to player2.

  • mean_score_diff_pos - equivalent to mean_score_diff but returns 0 if result is negative.

  • mean_score - computes mean score of player1.

  • sum_score_diff - computes sum of score differences of player1 compared to player2.

  • sum_score_diff_pos - equivalent to sum_score_diff but returns 0 if result is negative.

  • sum_score - computes sum of scores of player1.

  • num_wins - computes number of matchups player1 scored more than player2. Draws (determined by dplyr::near()) are omitted.

  • num_wins2 - computes number of matchups player1 scored more than player2 plus half the number of matchups where they had draw. Note that for equal player1 and player2 there might be non-zero output.

  • num - computes number of matchups.

Note that it is generally better to subset h2h_funs using names rather than indices because the order of elements might change in future versions.

See also

Long format of Head-to-Head values.

Matrix format of Head-to-Head values.

Examples

ncaa2005 %>% h2h_long(!!!h2h_funs)

#> # A long format of Head-to-Head values:
#> # A tibble: 25 x 11
#>    player1 player2 mean_score_diff mean_score_diff… mean_score sum_score_diff
#>    <chr>   <chr>             <dbl>            <dbl>      <dbl>          <int>
#>  1 Duke    Duke                  0                0       8.75              0
#>  2 Duke    Miami               -45                0       7               -45
#>  3 Duke    UNC                  -3                0      21                -3
#>  4 Duke    UVA                 -31                0       7               -31
#>  5 Duke    VT                  -45                0       0               -45
#>  6 Miami   Duke                 45               45      52                45
#>  7 Miami   Miami                 0                0      34.5               0
#>  8 Miami   UNC                  18               18      34                18
#>  9 Miami   UVA                   8                8      25                 8
#> 10 Miami   VT                   20               20      27                20
#> # … with 15 more rows, and 5 more variables: sum_score_diff_pos <dbl>,
#> #   sum_score <int>, num_wins <dbl>, num_wins2 <dbl>, num <int>

ncaa2005 %>% h2h_mat(!!!h2h_funs["num_wins2"])

#> # A matrix format of Head-to-Head values:
#>       Duke Miami UNC UVA VT
#> Duke     2     0   0   0  0
#> Miami    1     2   1   1  1
#> UNC      1     0   2   1  0
#> UVA      1     0   0   2  0
#> VT       1     0   1   1  2