Cleaning data

I am going to determine which games this college football season had the worst score differential

library(tidyverse)

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## ✓ readr   1.4.0     ✓ forcats 0.5.0

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
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badlogs <- read.csv("badfootballlogs19.csv")

I separated the columns to display whether it was a win, a loss and then the score and which team scored how many points.

badlogs <- badlogs %>% separate(Result, into=c("Outcome", "Score"), sep=" ") %>% mutate(Score = gsub(")", "", Score, fixed=TRUE)) %>%  mutate(Score = gsub("(", "", Score, fixed=TRUE)) %>% separate(Score, into=c("TeamScore", "OpponentScore"), sep="-")

Following mutating the data I collected, I mutated the scored to show as a numeric number rather than a character.

badlogs <- badlogs %>% mutate(TeamScore = as.numeric(TeamScore), OpponentScore = as.numeric(OpponentScore))

Now that they were seen as characters, I reated a column for differential between Team Score and Opponent score to see the highest differentials of last season.

badlogs <- badlogs %>% mutate(Differential = TeamScore - OpponentScore)

worstgames <- badlogs %>% filter(Differential > 65)

We now found the worst games in whcih the differential was greater than 65 points.

library(ggalt)

## Registered S3 methods overwritten by 'ggalt':
##   method                  from   
##   grid.draw.absoluteGrob  ggplot2
##   grobHeight.absoluteGrob ggplot2
##   grobWidth.absoluteGrob  ggplot2
##   grobX.absoluteGrob      ggplot2
##   grobY.absoluteGrob      ggplot2

library(ggrepel)

ggplot() + 
  geom_point(
    data=badlogs, 
    aes(x=TeamScore, y=OpponentScore), 
    color="grey", 
    alpha=.5) + 
  geom_point(
    data=worstgames, 
     aes(x=TeamScore, y=OpponentScore), 
    color="red")  +
    geom_encircle(data=worstgames,  aes(x=TeamScore, y=OpponentScore), s_shape=.15, expand=.15, colour="red") +
 labs(x="Team Points per Game", y="Opponent Points per game", title="Some Teams exploded offensively",subtitle = "A couple teams labeled were blown out this season", caption="Source: NCAA | By Alex Kopf") +  
  theme_minimal() +  theme(
    plot.title = element_text(size = 16, face = "bold"),
    axis.title = element_text(size = 8), 
    plot.subtitle = element_text(size=10), 
    panel.grid.minor = element_blank()
    ) +
  geom_text_repel(data=worstgames, aes(x=TeamScore, y=OpponentScore, label=Opponent))