R package to get price and stats of FIFA Ultimate Team players in Futbin.
This package is available only on GitHub. To install it, use the
devtools package:
library(devtools)
install_github("danielredondo/rfutbin")
library(rfutbin)futbin_search searchs players in Futbin. It has the following
parameters:
-
name. Optional. Vector with the names of the players. If not specified, it will report the 30 highest-rated players of the game. -
version. Optional. Version of the cards. Some options are “Rare”, “Non-Rare”, “IF” (In-Form), “SIF” (Second In-Form), … -
verbose. Optional. To show additional messages (webpage scraped and number of players found).
The output of the function is a dataframe with all the players found
searching for name and version.
futbin_scrap extracts all players of a Futbin URL. It has the
following parameters:
-
url. Futbin URL to web scrap. Futbin webpage (https://www.futbin.com/players) can be used to make customised filters, and then copy the URL here. All the players found in the URL (and the next pages) will be automatically detected and downloaded. -
sleep_time. Time (in seconds) ellapsed between scraping one page and the next one. Please respect Futbin API. -
verbose. Optional. To show additional verbose about webpage used and number of players found.
The output of the function is a dataframe with all the players found at the URL.
futbin_plot makes an interactive radar plot of the stats of the
players. It has the following parameters:
dfdataframe generated with columnspac,sho,pas,dri,def,phy. This dataframe can be obtained from functionfutbin_search.gkOptional. IfTRUE, the labels of the plot are the main stats for goalkeepers: diving, handling, kicking, reflexes, speed and position.
The output of the function is an interactive radar plot of the stats.
library(rfutbin)futbin_search(name = "Lionel Messi")
#> name rating position version price skills weak_foot pac sho pas dri
#> 1 Lionel Messi 95 CF TOTGS 1470000 4 4 88 95 94 97
#> 2 Lionel Messi 94 CF IF 948000 4 4 86 94 93 96
#> 3 Lionel Messi 93 RW Rare 414000 4 4 85 92 91 95
#> 4 Lionel Messi 93 RW CL 414000 4 4 85 92 91 95
#> def phy hei popularity base_stats in_game_stats wr_attack wr_defense wei
#> 1 40 68 170 861 482 2348 M L 72
#> 2 39 66 170 3932 474 2315 M L 72
#> 3 38 65 170 3308 466 2273 M L 72
#> 4 38 65 170 347 466 2273 M L 72futbin_search(name = c("Lionel Messi", "Cristiano Ronaldo"))
#> name rating position version price skills weak_foot pac sho
#> 1 Lionel Messi 95 CF TOTGS 1470000 4 4 88 95
#> 2 Lionel Messi 94 CF IF 948000 4 4 86 94
#> 3 Lionel Messi 93 RW Rare 414000 4 4 85 92
#> 4 Lionel Messi 93 RW CL 414000 4 4 85 92
#> 5 Cristiano Ronaldo 93 ST IF 2650000 5 4 90 94
#> 6 Cristiano Ronaldo 92 ST Rare 1290000 5 4 89 93
#> 7 Cristiano Ronaldo 92 ST CL 1300000 5 4 89 93
#> pas dri def phy hei popularity base_stats in_game_stats wr_attack wr_defense
#> 1 94 97 40 68 170 861 482 2348 M L
#> 2 93 96 39 66 170 3932 474 2315 M L
#> 3 91 95 38 65 170 3308 466 2273 M L
#> 4 91 95 38 65 170 347 466 2273 M L
#> 5 83 91 36 78 187 4216 472 2301 H L
#> 6 81 89 35 77 187 5985 464 2258 H L
#> 7 81 89 35 77 187 685 464 2258 H L
#> wei
#> 1 72
#> 2 72
#> 3 72
#> 4 72
#> 5 83
#> 6 83
#> 7 83# Lewandowski rare card
futbin_search(name = "Lewandowski", version = "Rare")
#> name rating position version price skills weak_foot pac sho pas
#> 3 Robert Lewandowski 91 ST Rare 70000 4 4 78 91 78
#> dri def phy hei popularity base_stats in_game_stats wr_attack wr_defense wei
#> 3 86 43 82 184 1672 458 2232 H M 80# Luis Suarez One to watch (OTW)
futbin_search(name = "Luis Suarez", version = "OTW")
#> name rating position version price skills weak_foot pac sho pas dri
#> 2 Luis Suárez 88 ST OTW 84000 3 4 72 91 84 84
#> def phy hei popularity base_stats in_game_stats wr_attack wr_defense wei
#> 2 52 84 182 560 467 2272 H M 86# Grealish In-Form (IF) showing verbose
futbin_search(name = "Grealish", version = "IF", verbose = TRUE)
#> [1] "Reading... https://www.futbin.com/21/players?page=1&search=grealish"
#> [1] "Player(s) found: 1"
#> name rating position version price skills weak_foot pac sho pas dri
#> 1 Jack Grealish 83 LM IF 25000 4 3 80 77 84 87
#> def phy hei popularity base_stats in_game_stats wr_attack wr_defense wei
#> 1 49 64 180 443 441 2066 M M 68# All Aston Villa players -> To get the URL, go to futbin.com/players and filter
aston_villa <- futbin_scrap(url = "https://www.futbin.com/players?page=1&club=2")
#> [1] "Reading... https://www.futbin.com/players?page=1&club=2"
#> [1] "Player(s) found: 30"
#> [1] "Reading... https://www.futbin.com/players?page=2&club=2"
#> [1] "Player(s) found: 38"
#> [1] "Reading... https://www.futbin.com/players?page=3&club=2"
#> [1] "Player(s) found: 38"
head(aston_villa)
#> name rating position version price skills weak_foot pac sho pas
#> 1 Ollie Watkins 84 ST IF 65000 3 4 90 84 77
#> 2 Jack Grealish 83 LM IF 25000 4 3 80 77 84
#> 3 Emiliano Martínez 82 GK IF 10500 1 3 82 84 82
#> 4 Ollie Watkins 81 ST IF 13750 3 4 88 79 73
#> 5 Jack Grealish 80 LW Rare 1800 4 3 76 74 80
#> 6 Tom Heaton 78 GK Non-Rare 600 1 3 78 77 74
#> dri def phy hei popularity base_stats in_game_stats wr_attack wr_defense wei
#> 1 82 54 76 180 3303 463 2188 H H 70
#> 2 87 49 64 180 443 441 2066 M M 68
#> 3 83 62 82 195 109 475 1072 M M
#> 4 78 51 73 180 773 442 2068 H H 70
#> 5 84 46 61 180 166 421 1989 M M 68
#> 6 79 56 78 187 11 442 980 M M 92# All English players in Bundesliga -> To get the URL, go to futbin.com/players and filter
futbin_scrap(url = "https://www.futbin.com/21/players?page=1&league=19&nation=14")
#> [1] "Reading... https://www.futbin.com/21/players?page=1&league=19&nation=14"
#> [1] "Player(s) found: 9"
#> [1] "Reading... https://www.futbin.com/21/players?page=2&league=19&nation=14"
#> [1] "Player(s) found: 9"
#> name rating position version price skills weak_foot pac
#> 1 Jadon Sancho 88 RM Record Breaker 243000 5 3 87
#> 2 Jadon Sancho 87 RM Rare 30000 5 3 83
#> 3 Jadon Sancho 87 RM CL 30000 5 3 83
#> 4 Ryan Sessegnon 75 LM non-rare 1300 4 3 86
#> 5 Ademola Lookman 74 RM Rare 25250 3 4 82
#> 6 Jude Bellingham 69 CM Non-Rare 1600 3 4 77
#> 7 Reece Oxford 66 CB Non-Rare 900 2 3 67
#> 8 Clinton Mola 66 LB Non-Rare 700 2 3 68
#> 9 Keanan Bennetts 63 LM Rare 0 2 4 75
#> sho pas dri def phy hei popularity base_stats in_game_stats wr_attack
#> 1 83 82 91 38 65 180 1365 446 2092 H
#> 2 74 81 91 37 64 180 -328 430 2015 H
#> 3 74 81 91 37 64 180 33 430 2015 H
#> 4 67 69 75 65 62 178 38 424 1978 H
#> 5 72 66 80 27 60 174 45 387 1828 H
#> 6 65 64 73 55 66 180 161 400 1837 H
#> 7 33 52 56 66 69 191 6 343 1591 M
#> 8 40 63 64 62 63 183 5 360 1670 H
#> 9 59 58 66 41 55 183 7 354 1641 H
#> wr_defense wei
#> 1 M 76
#> 2 M 76
#> 3 M 76
#> 4 M 71
#> 5 M 71
#> 6 M 72
#> 7 M 78
#> 8 L 78
#> 9 M 73players <- futbin_search(name = c("Van Dijk", "Lionel Messi"), version = "Rare")
futbin_plot(players)
some_goalkeepers <- futbin_search(name = c("De Gea", "Kepa", "Hugo Lloris"), version = "Rare")
futbin_plot(some_goalkeepers, gk = TRUE)
If you use this package, you can cite it as:
Redondo-Sanchez, Daniel (2020). rfutbin: R package to get price and stats of FIFA Ultimate Team players in Futbin