Create Fantasy-Football.R

Fantasy-Football.R

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+library('ggplot2')
+#-------------------------------------------------------
+#------- Data Incubator Challenge: Question 3 ----------
+#-------- Fantasy Football and Data Science ------------
+#-------------------------------------------------------
+rm(list = ls())
+gc(verbose = FALSE)
+
+# Load the data into a dataframe -----------------------
+ff_data <- read.csv("FF.csv", header = TRUE)
+str(ff_data)
+
+# Scatterplot of players fantasy points vs cost --------
+qplot(Cost, FP, data = ff_data, shape = Position, color = Position,
+      ylab = "Fantasy Points", xlab = "Cost", main = "Fantasy Points vs Cost")
+
+# Boxplot showing points distributions across----------- 
+# Plot 1 -----------------------------------------------
+qplot(Position, FP, data = ff_data, geom = "boxplot", fill = Position,
+      ylab = "Fantasy Points", xlab = "Position", 
+      main = "Fantasy Points Distributions Across Positions")
+
+# Retrieve QB data  ------------------------------------
+QB_data <- ff_data[ff_data$Position == "QB", c('Player', 'FP', 'Cost')]
+str(QB_data)
+
+# Compute QB average fantasy points and average cost ---
+QB_avg <- apply(QB_data[,c("FP", "Cost")],2,'mean')
+
+# Determine possible QB sleepers using averages---------
+QB_data$Sleeper <- QB_data$FP > QB_avg["FP"] & QB_data$Cost < QB_avg["Cost"]
+str(QB_data)
+
+# Plot of possible QB sleepers comparing them to rest --
+# Plot 2 -----------------------------------------------
+qplot(Cost, FP, data = QB_data, shape = Sleeper, color = Sleeper,
+      ylab = "Fantasy Points", xlab = "Cost ($)", main = "Potential Quaterback Sleepers")