Gets league-play data for each game, from engsoccerdata, returning
a tibble in a standardised format. You can pass in filtering expressions
via the dots (...), these are evaluated using dplyr::filter().
Filtering is the last step; it operates on the returned data.
Usage
uss_get_matches(country = uss_countries(), ...)Arguments
- country
characterscalar, specifies the league.uss_countries()returns choices available from engsoccerdata- ...
<
data-masking> Expressions that return a logical value, and are defined in terms of the variables in.data. If multiple expressions are included, they are combined with the&operator. Only rows for which all conditions evaluate toTRUEare kept.
Value
tibble with columns country, date,
season, tier, home, visitor, goals_home, goals_visitor.
Details
uss_countries() returns the available choices; "england" is
the default.
This function relies on an internal function, uss_make_matches(), to parse
the source data; to speed up the performance, a memoised (caching) version
of this function is used, uss_make_matches_mem().
Examples
uss_get_matches("england")
#> # A tibble: 192,004 × 8
#> country tier season date home visitor goals_home goals_visitor
#> <chr> <fct> <int> <date> <chr> <chr> <int> <int>
#> 1 England 1 1888 1888-12-15 Accrington … Aston … 1 1
#> 2 England 1 1888 1889-01-19 Accrington … Blackb… 0 2
#> 3 England 1 1888 1889-03-23 Accrington … Bolton… 2 3
#> 4 England 1 1888 1888-12-01 Accrington … Burnley 5 1
#> 5 England 1 1888 1888-10-13 Accrington … Derby … 6 2
#> 6 England 1 1888 1888-12-29 Accrington … Everton 3 1
#> 7 England 1 1888 1889-01-26 Accrington … Notts … 1 2
#> 8 England 1 1888 1888-10-20 Accrington … Presto… 0 0
#> 9 England 1 1888 1889-04-20 Accrington … Stoke … 2 0
#> 10 England 1 1888 1888-11-24 Accrington … West B… 2 1
#> # … with 191,994 more rows