This has essentially the same as the matches data; here, a row is returned
for every combination of team and match. Thus there are two rows returned
for each row in the data_matches tibble: one for each team.
Arguments
- data_matches
data.framecreated usinguss_get_matches()oruss_make_matches()
Value
tibble with columns country, tier,
season, team, date, opponent, at_home,
goals_for, goals_against; ordered by country, tier,
season, team, date.
Examples
uss_get_matches("england") |>
uss_make_teams_matches() |>
dplyr::filter(team == "Leeds United") |>
tail()
#> # A tibble: 6 × 9
#> country tier season team date at_home opponent goals…¹ goals…²
#> <chr> <fct> <int> <chr> <date> <lgl> <chr> <int> <int>
#> 1 England 3 2009 Leeds United 2010-04-10 TRUE Southend… 2 0
#> 2 England 3 2009 Leeds United 2010-04-13 FALSE Carlisle… 3 1
#> 3 England 3 2009 Leeds United 2010-04-17 FALSE Gillingh… 2 3
#> 4 England 3 2009 Leeds United 2010-04-24 TRUE Milton K… 4 1
#> 5 England 3 2009 Leeds United 2010-05-01 FALSE Charlton… 0 1
#> 6 England 3 2009 Leeds United 2010-05-08 TRUE Bristol … 2 1
#> # … with abbreviated variable names ¹goals_for, ²goals_against