R package animation comparing nfl combine stats over the years. BMI forty yard dash idea Idea from https://medium.com/@slackjack314/bmi-speed-and-nfl-positions-11f90b407551 as I know nothing about NFL. data fromhttp://www.nflsavant.com/dump/combine.csv this type of graph i learned at https://www.r-bloggers.com/ggplot2-easy-way-to-mix-multiple-gr…

NFLCombine.r

library(ggplot2)
library(dplyr)
library(animation)
library(ggpubr)
library(stringr)

#read website
#Run this only once to not take too much out of nflsavant's server
#I found this website in this article https://medium.com/@slackjack314/bmi-speed-and-nfl-positions-11f90b407551
URL <- "http://www.nflsavant.com/dump/combine.csv"
download.file(URL, destfile = "combine2.csv", method="curl")

#This can be run each time you overwrite or whatever the dataframe
football <- read.csv("combine2.csv")

#just WR and DE is not enough of a sample so I have divided positions into what I guess are those that run about and those that don't
football <- football %>% 
  mutate(type = str_replace_all(position, c("DE"= "line", "DT"= "line", 
                                                 "OG"= "line", "OT"= "line", 
                                                 "CB"= "run", "WR"= "run", 
                                                 "SS"= "run","RB"= "run")))
                                                 
#Clean up data a bit by removing people elss than a foot tall and such
  football<-filter(football, heightinchestotal > 40 )#%>%  na.omit()

#football<- filter(football,position == "DE" |position == "WR")
football<- filter(football,type == "run" |type == "line")
#football2<- filter(football2,year == 2015)
#change name of a column
names(football)[names(football) == "heightinchestotal"] <- "height"

#fortyyd in less then a second seems unlikely
football<- filter(football,fortyyd >1)
#get bmi
football<-football %>% 
  mutate(bmi = (703*weight)/(height*height))
  
#Now make the animation
saveGIF({
    
    for(i in 1999:2015){
        
          football2<- filter(football,year == i)
          #BMI graph on top
            xplot<-ggdensity(football2, "bmi",fill = "type",palette = "jco")+coord_cartesian(xlim = c(25,45), ylim = c(0,.25))
            #forty yard dash on side
            yplot<-ggdensity(football2, "fortyyd",fill = "type",palette = "jco")+coord_cartesian(xlim = c(4.2,6), ylim = c(0,5))
            yplot <- yplot + clean_theme() 
            xplot <- xplot + clean_theme()
            #scatter plot at bottom left
            sp <- ggscatter(football2, x = "bmi", y = "fortyyd",
                color = "type", palette = "jco",
                size = 3, alpha = 0.6)+annotate(x=24, y=4, geom="text", label=i, size= 11)+coord_cartesian(xlim = c(22,45), ylim = c(4,6))
           #combine these three graphs
           figure<-ggarrange(xplot, NULL, sp, yplot, 
          ncol = 2, nrow = 2,  align = "hv", 
          widths = c(2, 1), heights = c(1, 2),
          common.legend = TRUE)
            figure<-annotate_figure(figure,
                top = text_grob("BMI vs. 40 Yard Dash in NFL Scouting Combine", color = "Black", face = "bold", size = 20),
                bottom = text_grob("data: nflsavant.com", color = "blue",
                                   hjust = 1, x = 1, face = "italic", size = 10))
            print(figure
            )
            #last frame should go on longer so i print it three extra times.
            if(i == 2015){
              print(figure)
              print(figure)
              print(figure)}
              
              }
}, interval=0.4,ani.width = 900, ani.height = 600)