Scraping a specific stat for this match. Inspiration here. You can get other player stats in a similar fashion.
library(httr)
library(tibble)
library(tidyr)
library(dplyr)
library(purrr)
library(janitor)
stats_resp <- GET('https://fdh-api.fifa.com/v1/stats/match/128084/players.json')
stats <- stats_resp |>
content() |>
enframe('player_id', 'values') |>
unnest_longer(values) |>
hoist(
values,
'stat' = 1,
'value' = 2
) |>
select(-values) |>
mutate(
across(player_id, as.integer)
) |>
pivot_wider(
names_from = stat,
values_from = value
) |>
clean_names()
squad_resp <- GET('https://play.fifa.com/json/fantasy/squads_fifa.json')
player_resp <- GET('https://play.fifa.com/json/fantasy/players.json')
squad_cont <- content(squad_resp)
player_cont <- content(player_resp)
squads <- tibble(
squad_id = squad_cont |> map_int(~pluck(.x, 'id')),
country = squad_cont |> map_chr(~pluck(.x, 'name'))
)
players <- tibble(
player_id = player_cont |> map_int(~pluck(.x, 'id')),
squad_id = player_cont |> map_int(~pluck(.x, 'squadId')),
player = player_cont |> map_chr(~pluck(.x, 'name')),
position = player_cont |> map_chr(~pluck(.x, 'position'))
)
stats |>
inner_join(players, by = 'player_id') |>
inner_join(squads, by = 'squad_id') |>
select(player, country, linebreaks_attempted_completed) |>
arrange(desc(linebreaks_attempted_completed)) |>
slice_max(linebreaks_attempted_completed, n = 10)
#> # A tibble: 10 × 3
#> player country linebreaks_attempted_completed
#> <chr> <chr> <dbl>
#> 1 Bassam Hisham Qatar 23
#> 2 Abdelkarim Hassan Qatar 21
#> 3 Angelo Preciado Ecuador 16
#> 4 Pervis Estupinan Ecuador 14
#> 5 Jhegson Mendez Ecuador 14
#> 6 Moises Caicedo Ecuador 14
#> 7 Karim Boudiaf Qatar 13
#> 8 Felix Torres Ecuador 9
#> 9 Piero Hincapie Ecuador 9
#> 10 Akram Afif Qatar 8You can functionalize the above code by result_id so that you can retrieve the same data for other completed matches.
matches_resp <- GET('https://api.fifa.com/api/v3/calendar/matches?language=en&count=500&idSeason=255711')
results <- content(matches_resp) |> pluck('Results')
## for incomplete matches (anything beyond the group stage at the moment), there will be `NULL`s
## which causes `pluck()` to throw an error. using a `.default` of `NA` fixes the issue.
pluck2 <- partial(pluck, .default = NA_character_, ... = )
map_pluck_chr <- function(x, ...) {
map_chr(x, pluck2, ...)
}
map_pluck_results_chr <- function(...) {
results |> map_pluck_chr(...)
}
matches <- tibble(
## this won't join with the match stats, but it seems to be Fifa's "true" match ID
match_id = map_pluck_results_chr('IdMatch') |> as.integer(),
## use this to join with the match stats
results_id = map_pluck_results_chr('Properties', 'IdIFES') |> as.integer(),
home_abbr = map_pluck_results_chr('Home', 'IdCountry'),
away_abbr = map_pluck_results_chr('Away', 'IdCountry')
)
#> # A tibble: 64 × 4
#> match_id results_id home_abbr away_abbr
#> <int> <int> <chr> <chr>
#> 1 400128082 128084 QAT ECU
#> 2 400235458 132997 ENG IRN
#> 3 400235449 132996 SEN NED
#> 4 400235455 132995 USA WAL
#> 5 400235461 133001 ARG KSA
#> 6 400235466 132999 DEN TUN
#> 7 400235463 133000 MEX POL
#> 8 400235470 132998 FRA AUS
#> 9 400235481 133003 MAR CRO
#> 10 400235476 133005 GER JPN
#> # … with 54 more rows