Untitled

This is my First Heading

This is how I went about doing my assignment #2. blah, blah, blah

This is the 2nd paragraph.

• Hi
• How
• are
• you?

1. Hi
2. How
3. are
4. you?

my_path <- "C:/Users/pptallon/Dropbox/G/Teaching/Loyola College/IS470 Sports Analytics/"
setwd(my_path)

library(data.table)
library(ggplot2)
library(dplyr)
library(tidytext)
library(RColorBrewer)

df <- fread("GamesGithub.csv")

cols_to_use <- c("season", "away_team", "away_score", "home_team", "home_score")

df <- subset(df, select = cols_to_use)

df$winner <- ifelse(df$away_score > df$ home_score, df$away_team, df$home_team)
df$loser  <- ifelse(df$away_score > df$ home_score, df$home_team, df$away_team)

df <- na.omit(df)

df$score_diff <- abs(df$away_score - df$home_score)

winners <- df %>%
  mutate(team = winner) %>%
  group_by(season, team) %>%
  summarise(win_count = n(), .groups = "keep") %>%
  data.frame() 

losers <- df %>%
  mutate(team = loser) %>%
  group_by(season, team) %>%
  summarise(lose_count = n(), .groups = "keep") %>%
  data.frame() 

df1 <- merge(x = winners, y = losers, by=c("season", "team"), all=TRUE)

df1[is.na(df1)] <- 0

df2 <- df1 %>%
  mutate(team = recode(team, 'OAK' = 'LV', 'SD' = 'LAC', 'STL' = 'LA') ) %>%
  group_by(team) %>%
  summarise(wins = sum(win_count), losses = sum(lose_count), .groups = 'keep') %>%
  mutate(total_games = wins + losses,
         win_pc  = round(100*wins/total_games,0),
         loss_pc = round(100*losses/total_games,0)) %>%
  data.frame()

ggplot(df2, aes(x = reorder(team, -wins), y = wins, fill = win_pc)) +
  geom_bar(stat="identity") +
  labs(x = "Team", y = "Win Count", title = "Wins by Team", fill = "Win Percentage") +
  geom_text(aes(label = paste0(win_pc,"%")), vjust = -0.5 ) +
  scale_fill_continuous( 
    limits = c(31, 80),
    labels=paste0(seq(30, 80, 10), "%"),
    breaks = seq(30, 80, 10),
    low = "red",
    high = "dark green") +
  theme(plot.title = element_text(hjust=0.5))

This is my 2nd heading

More paragraphs of text.

Etc.

df2 <- df1 %>%
  filter(season >= 2019 & season <= 2021) %>%
  mutate(team = recode(team, 'OAK' = 'LV', 'SD' = 'LAC', 'STL' = 'LA') ) %>%
  group_by(season) %>%
  mutate( total = win_count + lose_count,
          win_pc  = round(100*win_count/total,0),
          loss_pc = round(100*lose_count/total,0),
          team = reorder_within(team, win_count, season),
          team_abbr = substr(team, 0, nchar(as.character(team))-7),
          rank = rank(-win_pc, ties.method = "random" )) %>%
  data.frame()

ggplot(df2, aes(x = reorder(team, -win_count), y = win_count, fill = win_pc)) +
  geom_bar(stat="identity") +
  geom_text(aes(label = paste0(win_pc,"%")), vjust = -0.5, size = 3 ) +
  labs(x = "Team", y = "Win Count", title = "Wins by Team", fill = "Win Percentage") +
  scale_y_continuous(limits = c(0, max(df2$win_count)*1.1   )  ) +
  scale_x_reordered() +
  scale_fill_continuous( 
    limits = c(1, 90),
    labels=paste0(seq(0, 90, 10), "%"),
    breaks = seq(0, 90, 10),
    low = "red",
    high = "dark green") +
  facet_wrap(ncol = 1, nrow = 8, ~season, scales='free') +
  theme(plot.title = element_text(hjust=0.5))

cols <- colorRampPalette( brewer.pal(8, "Set2")   )  
myPal <- cols(32)

ggplot(df2, aes(x = season, y = rank, group = team_abbr)) +
  geom_line(aes(color = team_abbr), size = 2  ) +
  geom_point(shape = 21, size = 4, fill = "white") +
  scale_y_reverse( breaks = seq(max(df2$rank), 1, -1)) +
  geom_text(data = df2 %>% filter(season == min(season)),
            aes(x = season - 0.05,
                y = rank,
                label = team_abbr),
            size=3,
            hjust=1) +
  geom_text(data = df2 %>% filter(season == max(season)),
            aes(x = season + 0.05,
                y = rank,
                label = team_abbr),
            size=3,
            hjust=0) +
  scale_x_continuous( breaks = min(df2$season):max(df2$season),
                      labels = as.character(min(df2$season):max(df2$season))) +
  scale_color_manual(values = myPal) +
  labs( title = "Bump Chart for Teams by Win Percentage",
        x = "Season",
        y = "Rank",
        colour = "Teams") +
  theme(plot.title = element_text(hjust=0.5))

More stuff goes here if u want it.

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Note

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