Competition results with games between two players

Source: R/pairgames.R

Functions for competition results with games between two players.

to_pairgames(cr_data)

is_pairgames(cr_data)

Arguments

cr_data

Competition results in format ready for as_longcr().

Value

to_pairgames() returns a competition results of pairwise games as widecr object with two players.

is_pairgames() returns a boolean value of whether cr_data contains only games between two players.

Details

Pairgames is a term for competition results with games between two players.

to_pairgames() is a function that converts competition results into pairwise games: it drops games with one player and for every game with 3 and more players this function transforms it into set of separate games between unordered pairs of players. In other words the result is a set of unordered matchups (as different games) between different players.

Important notes:

  • New game identifiers are integers, order of which respects order of games stored in cr_data (based on first occurrence in long format). There is no particular order in subgames of games with 3 and more players.

  • Order in which players are assigned to player1 or player2 column in general shouldn't agree with any order in cr_data.

  • Any column except game, player and score will be dropped after conversion to longcr.

  • NA and NaN in players are allowed. They are treated as different players.

  • to_pairgames() is rather compute-intensive and can take much time for competition results with many games.

Examples

cr_data <- data.frame(
  game = c(rep(1:5, each = 3), 6),
  player = c(rep(1:5, times = 3), 1),
  score = 101:116,
  extraCol = -(1:16)
)

to_pairgames(cr_data)

#> # A widecr object:
#> # A tibble: 15 x 5
#>     game player1 score1 player2 score2
#>    <int>   <dbl>  <int>   <dbl>  <int>
#>  1     1       1    101       2    102
#>  2     2       1    101       3    103
#>  3     3       2    102       3    103
#>  4     4       4    104       5    105
#>  5     5       4    104       1    106
#>  6     6       5    105       1    106
#>  7     7       2    107       3    108
#>  8     8       2    107       4    109
#>  9     9       3    108       4    109
#> 10    10       5    110       1    111
#> 11    11       5    110       2    112
#> 12    12       1    111       2    112
#> 13    13       3    113       4    114
#> 14    14       3    113       5    115
#> 15    15       4    114       5    115

# Missing values
cr_data_na <- data.frame(
  game = rep(1L, 3),
  player = c(1, NA, NA),
  score = 1:3
)
to_pairgames(cr_data_na)

#> # A widecr object:
#> # A tibble: 3 x 5
#>    game player1 score1 player2 score2
#>   <int>   <dbl>  <int>   <dbl>  <int>
#> 1     1       1      1      NA      2
#> 2     2       1      1      NA      3
#> 3     3      NA      2      NA      3

# Checks
is_pairgames(cr_data)

#> [1] FALSE
is_pairgames(to_pairgames(cr_data))

#> [1] TRUE