library(data.table)
library(dplyr)
library(ggplot2)
library(ggthemes)
library(scales)
library(viridis)
library(ggalt)

Get the data:

URL <- "https://juliogarcia.github.io/fanduel_upload.csv"
fil <- basename(URL)
if (!file.exists(fil)) download.file(URL, fil)

dat <- tbl_df(fread(fil))

Get the local density of each point in the scatterplot pairs. Use Viridis as the color palette. Add this new color value as a column in the data frame.

dat$dens_col <- densCols(dat$CombinedSalary, dat$FPPG, colramp=viridis_pal())

Make the scatterplot:

gg <- ggplot()
gg <- gg + geom_point(data=dat, 
                      aes(x=CombinedSalary, y=FPPG, color=dens_col),
                      size=0.6, alpha=1/4)
gg <- gg + scale_color_identity()
gg <- gg + theme_tufte(base_family="Helvetica")
gg <- gg + labs(x='Salary', y='Lineup Total Fantasy Points Per Game',
                title=sprintf("%s Ramdomly Created FanDuel Lineups", comma(nrow(dat))))
gg

Alternate way of showing the densities:

gg <- ggplot()
gg <- gg + stat_bkde2d(data=dat, 
                       aes(x=CombinedSalary, y=FPPG, fill=..level..), 
                       geom="polygon")
gg <- gg + scale_fill_viridis()
gg <- gg + theme_tufte(base_family="Helvetica")
gg <- gg + labs(x='Salary', y='Lineup Total Fantasy Points Per Game',
                title=sprintf("%s Ramdomly Created FanDuel Lineups", comma(nrow(dat))))
gg

Rmd source available in this gist