Packages used:

library(dplyr)

library(readxl)

library(ggplot2)

Data source: https://fantasydata.com/, uses non-ppr standard fantasy scoring

Read in Alvin Kamara and Mark Ingram 2018 data, both data sets are in same excel sheets but in different tabs. Kamara is on sheet 3 and Ingram on sheet 4. Use readxl package, and read_excel() function.

Kamara <- read_excel(akamara , sheet = 3)
Mark_Ingram <- read_excel(mingram, sheet = 4)

Using dplyr package filter games where A. Kamara had more than 0 rushing attempts and select following columns from dataset: player, week, and points. Do the same for M. Ingram.

Kamara <- Kamara %>% filter(attempt>0) %>% select(player, week, points)
Mark_Ingram <- Mark_Ingram %>% filter(attempt>0) %>% select(player, week)

Use dplyr to join the two data sets using function left_join, then create an additional column where it tells you for each week if M. Ingram played, then remove column “player.y”.

Kamara <- Kamara %>% left_join(Mark_Ingram, by="week") %>% mutate(Ingram_Play= ifelse(is.na(player.y), "Ingram not play", "Ingram played")) %>% select(-player.y)

Summarize the data to display difference in fantasy points

Kamara1 <- Kamara %>% group_by(player.x,Ingram_Play) %>%
  summarize(`total games`= n(),
            `Average points`= mean(points)) %>% mutate(`Average points` = round(`Average points`,2))
Kamara1

## # A tibble: 2 x 4
## # Groups:   player.x [1]
##   player.x Ingram_Play     `total games` `Average points`
##   <chr>    <chr>                   <int>            <dbl>
## 1 Kamara   Ingram not play             4             25.3
## 2 Kamara   Ingram played              11             15.6

Using ggplot2 package display data in bar plot.

Kamara2 <- ggplot(data=Kamara1, aes(x=Ingram_Play, y=`Average points`, title="Even")) +
  geom_bar(stat="identity", fill="steelblue") +
  geom_text(aes(label=`Average points`), vjust=10, color="white", size=7) +
  ggtitle("Kamara 2018 Season")
Kamara2