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Make season-based calculations

Source: R/seasons.R
uss_make_seasons_cumulative.Rd

Given a teams-matches data frame (returned by uss_make_teams_matches()), return return a data frame on wins, losses, points, etc.:

  • cumulative, over the course of each season: uss_make_seasons_cumulative()

Usage

uss_make_seasons_cumulative(
  data_teams_matches,
  fn_points_per_win = uss_points_per_win
)

uss_make_seasons_final(
  data_teams_matches,
  fn_points_per_win = uss_points_per_win
)

Arguments

data_teams_matches

data frame created using uss_make_teams_matches()

fn_points_per_win

function with vectorized arguments country, season, that returns a integer indicating points-per-win. A default function is provided, uss_points_per_win(), which includes the countries in uss_countries().

Value

tibble with columns country, tier, season, team, date, matches, wins, draws, losses, points, goals_for, goals_against.

Examples

italy <- uss_get_matches("italy") |> uss_make_teams_matches()
uss_make_seasons_cumulative(italy)
#> # A tibble: 50,808 × 12
#> # Groups:   country, tier, season, team [1,516]
#>    country  tier season team     date       matches  wins draws losses points
#>    <chr>   <int>  <int> <chr>    <date>       <int> <int> <int>  <int>  <int>
#>  1 Italy       1   1929 AC Milan 1929-10-06       1     1     0      0      2
#>  2 Italy       1   1929 AC Milan 1929-10-13       2     2     0      0      4
#>  3 Italy       1   1929 AC Milan 1929-10-20       3     2     0      1      4
#>  4 Italy       1   1929 AC Milan 1929-10-27       4     3     0      1      6
#>  5 Italy       1   1929 AC Milan 1929-11-03       5     3     1      1      7
#>  6 Italy       1   1929 AC Milan 1929-11-10       6     3     1      2      7
#>  7 Italy       1   1929 AC Milan 1929-11-17       7     3     1      3      7
#>  8 Italy       1   1929 AC Milan 1929-11-24       8     4     1      3      9
#>  9 Italy       1   1929 AC Milan 1929-12-08       9     4     1      4      9
#> 10 Italy       1   1929 AC Milan 1929-12-15      10     5     1      4     11
#> # … with 50,798 more rows, and 2 more variables: goals_for <int>,
#> #   goals_against <int>