vignettes/topperformers.Rmd
topperformers.Rmd
Suppose we are interested in listing the top FPL performers by FPL goals and assists? Again, we take the first 25 gameweeks of the 18/19 season as an example.
First we fetch the gameweek-by-gameweek details of ALL players using get_player_details:
library(fplscrapR) df <- get_player_details(season=18) # this may take a while to load as it fetches ALL player details
Next we use dplyr and ggplot2 to transform and plot the data, showing the top performers:
df %>% filter(round %in% 1:25) %>% # filtering for the GWs we are interested in select(playername,goals_scored,assists) %>% # selecting the relevant columns group_by(playername) %>% # transformation to group and summarize the performance at the 'playername' variable level summarize_all(sum) %>% mutate("involvements"=goals_scored+assists) %>% # adding a new variable that sums the goals scored and assists arrange(-involvements) %>% # ordering (arranging) the table by top involvements slice(1:20) # showing the top20 only
## # A tibble: 20 x 4
## playername goals_scored assists involvements
## <chr> <int> <int> <int>
## 1 Mohamed Salah 16 8 24
## 2 Eden Hazard 12 10 22
## 3 Raheem Sterling 10 12 22
## 4 Sergio Agüero 14 8 22
## 5 Pierre-Emerick Aubameyang 15 6 21
## 6 Harry Kane 14 6 20
## 7 Leroy Sané 8 11 19
## 8 Callum Wilson 10 8 18
## 9 Paul Pogba 9 9 18
## 10 Alexandre Lacazette 9 8 17
## 11 Heung-Min Son 10 7 17
## 12 Marcus Rashford 9 7 16
## 13 Raúl Jiménez 9 7 16
## 14 Roberto Firmino 9 5 14
## 15 Ryan Fraser 5 9 14
## 16 Aleksandar Mitrovic 10 3 13
## 17 Sadio Mané 11 2 13
## 18 Christian Eriksen 4 8 12
## 19 Felipe Anderson Pereira Gomes 8 4 12
## 20 Gylfi Sigurdsson 9 3 12