NFL Visualization

nfl_standings <- read.csv("C:/Users/Adam Deuber/OneDrive/UC/BANA Masters/Data Wrangling/Data Wrangling/Week 5/standings.csv")
library(ggplot2)
ggplot(data = nfl_standings, mapping = aes(x = points_for, y = margin_of_victory, col = playoffs)) + geom_point(size = 1.5) + ggtitle("NFL Data") + theme(plot.title = element_text(hjust = 0.5)) + theme(plot.title = element_text(face = "bold")) + labs(x = "Total Points Scored", y = "Average Margin of Victory (Loss)")

The data used for the above visualization was the nfl_standings dataset that is available for my Final Project. This dataset gives many variables that cover NFL teams’ data each year for the past 20 years. The specific variables I wanted to use were points_for, margin_of_victory, and playoffs.

• points_for- Total points the team scored per season
• margin_of_victory - The difference between the total points for the team and against the team divided by the total number of games per season
• playoffs - a binary variable that shows if the team made the playoffs (Playoffs) or if they did not make the Playoffs (No Playoffs)

The goal of the visualization was to prove that the more points a team scored in a year, the higher the average margin of victory would be for that team’s season. As the scatter plot shows, these variables have a positive correlation which proves my theory to be correct. Additionally, I added the playoffs variable to see what type of teams make the playoffs. As expected, teams with a high total points and margin of victory were playoff teams. This scatter plot provides a great represenation of the importance of scoring points and winning in the NFL.