R package to get price and stats of FIFA Ultimate Team players in Futbin for all platforms (PS4/XBox One/PC).
This package is available only on GitHub. To install it, use the
devtools
package:
library(devtools)
install_github("danielredondo/rfutbin")
library(rfutbin)
library(rfutbin)
futbin_search(name = "Lionel Messi")
#> # A tibble: 9 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Lione~ 99 RW Summer~ 8.53e5 4 4 96 99 98 99
#> 2 Lione~ 99 CAM Futtie~ 6.85e5 5 4 98 99 99 99
#> 3 Lione~ 98 RW TOTY 7.06e5 4 4 93 98 97 99
#> 4 Lione~ 98 ST TOTS 2.9 e5 4 4 91 99 96 99
#> 5 Lione~ 96 CF LaLiga~ 1.71e6 4 4 90 96 95 98
#> 6 Lione~ 95 CF TOTGS 9.05e4 4 4 88 95 94 97
#> 7 Lione~ 94 CF IF 1.1 e5 4 4 86 94 93 96
#> 8 Lione~ 93 RW Rare 4.58e4 4 4 85 92 91 95
#> 9 Lione~ 93 RW CL 5.2 e4 4 4 85 92 91 95
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
futbin_search(name = "Lionel Messi", platform = "xone")
#> # A tibble: 9 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Lione~ 99 RW Summer~ 8.97e5 4 4 96 99 98 99
#> 2 Lione~ 99 CAM Futtie~ 7.34e5 5 4 98 99 99 99
#> 3 Lione~ 98 RW TOTY 6.45e5 4 4 93 98 97 99
#> 4 Lione~ 98 ST TOTS 3.1 e5 4 4 91 99 96 99
#> 5 Lione~ 96 CF LaLiga~ 1.59e6 4 4 90 96 95 98
#> 6 Lione~ 95 CF TOTGS 1.19e5 4 4 88 95 94 97
#> 7 Lione~ 94 CF IF 1.81e5 4 4 86 94 93 96
#> 8 Lione~ 93 RW Rare 5.1 e4 4 4 85 92 91 95
#> 9 Lione~ 93 RW CL 6.3 e4 4 4 85 92 91 95
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
futbin_search(name = "Lionel Messi", platform = "pc")
#> # A tibble: 9 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Lione~ 99 RW Summer~ 1.5 e6 4 4 96 99 98 99
#> 2 Lione~ 99 CAM Futtie~ 7.67e5 5 4 98 99 99 99
#> 3 Lione~ 98 RW TOTY 1.24e6 4 4 93 98 97 99
#> 4 Lione~ 98 ST TOTS 3.3 e5 4 4 91 99 96 99
#> 5 Lione~ 96 CF LaLiga~ 1.93e6 4 4 90 96 95 98
#> 6 Lione~ 95 CF TOTGS 1.43e5 4 4 88 95 94 97
#> 7 Lione~ 94 CF IF 1.8 e5 4 4 86 94 93 96
#> 8 Lione~ 93 RW Rare 7.35e4 4 4 85 92 91 95
#> 9 Lione~ 93 RW CL 8.4 e4 4 4 85 92 91 95
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
futbin_search(name = c("Lionel Messi", "Cristiano Ronaldo"))
#> # A tibble: 19 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Lion~ 99 RW Summer~ 8.53e5 4 4 96 99 98 99
#> 2 Lion~ 99 CAM Futtie~ 6.85e5 5 4 98 99 99 99
#> 3 Lion~ 98 RW TOTY 7.06e5 4 4 93 98 97 99
#> 4 Lion~ 98 ST TOTS 2.9 e5 4 4 91 99 96 99
#> 5 Lion~ 96 CF LaLiga~ 1.71e6 4 4 90 96 95 98
#> 6 Lion~ 95 CF TOTGS 9.05e4 4 4 88 95 94 97
#> 7 Lion~ 94 CF IF 1.1 e5 4 4 86 94 93 96
#> 8 Lion~ 93 RW Rare 4.58e4 4 4 85 92 91 95
#> 9 Lion~ 93 RW CL 5.2 e4 4 4 85 92 91 95
#> 10 Cris~ 99 ST Summer~ 7 e5 5 4 96 99 92 98
#> 11 Cris~ 99 ST Premiu~ 1.01e6 5 5 98 99 95 99
#> 12 Cris~ 98 ST TOTY 4.45e5 5 4 96 98 89 96
#> 13 Cris~ 98 ST TOTS 4.15e5 5 4 95 99 90 95
#> 14 Cris~ 95 ST TIF 3.1 e5 5 4 92 96 87 93
#> 15 Cris~ 94 ST SIF 9.5 e5 5 4 91 95 85 92
#> 16 Cris~ 93 ST IF 2.34e5 5 4 90 94 83 91
#> 17 Cris~ 92 ST Rare 6.15e4 5 4 89 93 81 89
#> 18 Cris~ 92 ST CL 5.9 e4 5 4 89 93 81 89
#> 19 Cris~ 87 RW Flashb~ 3.34e5 5 3 91 79 75 86
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
# Lewandowski rare card
futbin_search(name = "Lewandowski", version = "Rare")
#> # A tibble: 1 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Robert~ 91 ST Rare 25250 4 4 78 91 78 86
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
# Luis Suarez One to watch (OTW)
futbin_search(name = "Luis Suarez", version = "OTW")
#> # A tibble: 1 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Luis S~ 90 ST OTW 31000 3 4 75 94 87 88
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
# 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"
#> # A tibble: 1 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Jack G~ 83 LM IF 29750 4 3 80 77 84 87
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
# 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: 45"
#> [1] "Reading... https://www.futbin.com/players?page=3&club=2"
#> [1] "Player(s) found: 45"
head(aston_villa)
#> # A tibble: 6 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Jack ~ 95 LW FOF PT~ 246500 4 3 97 94 97 99
#> 2 Jack ~ 87 CAM TOTY H~ 0 4 3 85 83 89 91
#> 3 Ollie~ 84 ST SIF 35000 3 4 90 84 77 82
#> 4 Emili~ 84 GK SIF 136000 1 3 85 86 84 86
#> 5 Jack ~ 83 LM IF 29750 4 3 80 77 84 87
#> 6 Emili~ 82 GK IF 0 1 3 82 84 82 83
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
# 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: 17"
#> [1] "Reading... https://www.futbin.com/21/players?page=2&league=19&nation=14"
#> [1] "Player(s) found: 17"
#> # A tibble: 17 x 23
#> name rating position version price skills weak_foot pac sho pas dri
#> <chr> <int> <chr> <chr> <dbl> <int> <int> <int> <int> <int> <int>
#> 1 Jado~ 96 RM TOTS 23500 5 4 96 94 93 98
#> 2 Jado~ 92 RM What If 20000 5 3 91 87 86 95
#> 3 Jude~ 91 CM TOTS M~ 219900 4 4 88 87 89 89
#> 4 Dema~ 90 LW ShowDo~ 199850 4 4 96 89 86 96
#> 5 Jado~ 89 LM Bundes~ 134500 5 3 87 78 83 93
#> 6 Jado~ 88 RM Record~ 71000 5 3 87 83 82 91
#> 7 Jado~ 87 RM Rare 23000 5 3 83 74 81 91
#> 8 Jado~ 87 RM CL 24500 5 3 83 74 81 91
#> 9 Ryan~ 87 LM Object~ 0 4 4 92 84 84 88
#> 10 Ryan~ 75 LM non-ra~ 8800 4 3 86 67 69 75
#> 11 Dema~ 75 LM non-ra~ 1300 4 3 87 68 67 80
#> 12 Adem~ 74 RM Rare 5000 3 4 82 72 66 80
#> 13 Omar~ 70 LB non-ra~ 8900 3 3 82 45 55 68
#> 14 Jude~ 69 CM Non-Ra~ 2500 3 4 77 65 64 73
#> 15 Reec~ 66 CB Non-Ra~ 700 2 3 67 33 52 56
#> 16 Clin~ 66 LB Non-Ra~ 7400 2 3 68 40 63 64
#> 17 Kean~ 63 LM Rare 4400 2 4 75 59 58 66
#> # ... with 12 more variables: def <int>, phy <int>, hei <chr>,
#> # popularity <int>, base_stats <int>, in_game_stats <int>, wr_attack <chr>,
#> # wr_defense <chr>, wei <chr>, team <chr>, nation <chr>, league <chr>
players <- futbin_search(name = c("Van Dijk", "Lionel Messi"), version = "Rare")
futbin_plot(players)
(Please note that this is a static version. Real plots are interactive.)
some_goalkeepers <- futbin_search(name = c("De Gea", "Kepa", "Hugo Lloris"), version = "Rare")
futbin_plot(some_goalkeepers, gk = TRUE)
(Please note that this is a static version. Real plots are interactive.)
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.
platform
. Platform to get the prices from. Default is ps4
. Other
options are xone
(XBox One) and pc
.
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.
platform
. Platform to get the prices from. Default is ps4
. Other
options are xone
(XBox One) and pc
.
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:
df
dataframe generated with columns pac
, sho
, pas
, dri
,
def
, phy
. This dataframe can be obtained from function
futbin_search
.
gk
Optional. If TRUE
, 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.
If you use this package, you can cite it as:
Redondo-Sanchez, Daniel (2021). rfutbin (v1.0.2): R package to get price and stats of FIFA Ultimate Team players in Futbin. https://github.com/danielredondo/rfutbin