library(ussie)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, unionussie let’s you work with european football data from the engsoccerdata package by making standard tibles for each country
spain <- uss_make_matches(engsoccerdata::spain, "Spain")
glimpse(spain)
#> Rows: 23,915
#> Columns: 8
#> $ country <chr> "Spain", "Spain", "Spain", "Spain", "Spain", "Spain", "S…
#> $ tier <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ season <int> 1928, 1928, 1928, 1928, 1928, 1928, 1928, 1928, 1928, 19…
#> $ date <date> 1929-02-10, 1929-02-10, 1929-02-10, 1929-02-10, 1929-02…
#> $ home <chr> "Arenas de Getxo", "Espanyol Barcelona", "Real Madrid", …
#> $ visitor <chr> "Atletico Madrid", "Real Union", "CE Europa", "Athletic …
#> $ goals_home <int> 2, 3, 5, 1, 0, 1, 9, 0, 3, 5, 3, 3, 1, 0, 2, 1, 2, 3, 2,…
#> $ goals_visitor <int> 3, 2, 0, 1, 2, 2, 0, 3, 1, 2, 0, 1, 1, 4, 1, 2, 1, 0, 2,…We can add filtering conditions:
uss_get_matches("england", season == 1966) |>
glimpse()
#> Rows: 2,028
#> Columns: 8
#> $ country <chr> "England", "England", "England", "England", "England", "…
#> $ tier <fct> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
#> $ season <int> 1966, 1966, 1966, 1966, 1966, 1966, 1966, 1966, 1966, 19…
#> $ date <date> 1966-08-27, 1966-09-17, 1966-12-03, 1967-02-04, 1967-04…
#> $ home <chr> "Arsenal", "Arsenal", "Arsenal", "Arsenal", "Arsenal", "…
#> $ visitor <chr> "Aston Villa", "Blackpool", "Burnley", "Chelsea", "Evert…
#> $ goals_home <int> 1, 1, 0, 2, 3, 1, 0, 2, 1, 1, 1, 2, 1, 2, 1, 4, 3, 2, 0,…
#> $ goals_visitor <int> 0, 1, 0, 1, 1, 0, 1, 4, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 2,…We can accumulate seasons:
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> <fct> <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>
uss_make_seasons_final(italy)
#> # A tibble: 1,516 × 12
#> # Groups: country, season, tier [85]
#> country tier season team date matches wins draws losses points
#> <chr> <fct> <int> <chr> <date> <int> <int> <int> <int> <int>
#> 1 Italy 1 1929 Inter 1930-07-06 34 22 6 6 50
#> 2 Italy 1 1929 Genova 189… 1930-07-06 34 20 8 6 48
#> 3 Italy 1 1929 Juventus 1930-07-06 34 19 7 8 45
#> 4 Italy 1 1929 Torino FC 1930-07-06 34 16 7 11 39
#> 5 Italy 1 1929 SSC Napoli 1930-07-06 34 14 9 11 37
#> 6 Italy 1 1929 AS Roma 1930-07-06 34 15 6 13 36
#> 7 Italy 1 1929 Bologna FC 1930-07-06 34 14 8 12 36
#> 8 Italy 1 1929 US Alessan… 1930-07-06 34 14 8 12 36
#> 9 Italy 1 1929 Pro Vercel… 1930-07-06 34 12 9 13 33
#> 10 Italy 1 1929 Brescia Ca… 1930-07-06 34 13 7 14 33
#> # … with 1,506 more rows, and 2 more variables: goals_for <int>,
#> # goals_against <int>