Calculate 17lands win-rate by rank across sets

wr_by_rank.R

# To install magicr
# pak::pkg_install("joelnitta/magicr")

library(tidyverse)
library(magicr)
library(ggrepel)

# Win-rate by rank and set ----

# Define function to calculate win-rate by rank for a particular set
get_wr_by_rank <- function(set_get) {
  cli::cli_inform("Working on {set_get}")
  mr_get_17lands_data(
  set = set_get, "game", "premier", select = c("rank", "won")) %>%
  filter(rank != "") %>%
  filter(rank != "none") %>%
  group_by(rank) %>%
  summarize(
    n_won = sum(won),
    n_total = n()
  ) %>%
  mutate(win_rate = n_won / n_total) %>%
  arrange(desc(win_rate)) %>%
  mutate(rank = as.factor(rank) %>%
    fct_relevel(
      c("bronze", "silver", "gold", "platinum", "diamond", "mythic"))
    ) %>%
  mutate(set = set_get)
}

# Define vector of sets to analyze
sets_to_get <- c(
  "KTK", "LCI", "WOE", "LTR", "MOM",
  "SIR", "ONE", "BRO", "DMU", "HBG",
  "SNC", "NEO"
)

# Calculate win-rank by set
wr_by_rank <- map_df(sets_to_get, get_wr_by_rank)

# Define where to plot set labels
set_labs <- wr_by_rank %>%
  filter(rank == "mythic")

# Make plot
ggplot(wr_by_rank, aes(x = rank, y = win_rate, color = set, group = set)) +
  geom_line() +
  geom_point(aes(size = n_total)) +
  geom_label_repel(
    data = set_labs,
    aes(label = set),
    nudge_x = .5, direction = "y", hjust = "right"
  ) +
  guides(color = "none") +
  scale_size_continuous(label = scales::label_number(big.mark = ",")) +
  scale_y_continuous(label = scales::label_percent()) +
  labs(x = "Rank", y = "Win Rate", size = "Num. games") +
  theme_grey(base_size = 24)

# Win rate by rank and day ----

# Define function to calculate win-rate by rank and add day of the month
get_wr_by_rank_day <- function(set_get) {
  cli::cli_inform("Working on {set_get}")
  game_data <- mr_get_17lands_data(
    set = set_get, "game", "premier", select = c("rank", "won", "draft_time"))
  if (!"draft_time" %in% colnames(game_data)) return(tibble())
  game_data %>%
    filter(rank != "") %>%
    filter(rank != "none") %>%
    mutate(day = lubridate::day(draft_time)) %>%
    group_by(rank, day) %>%
    summarize(
      n_won = sum(won),
      n_total = n(),
      .groups = "drop"
    ) %>%
    mutate(
      win_rate = n_won / n_total,
      set = set_get)
}

# Calculate win-rank by rank and day
wr_by_day <- map_df(sets_to_get, get_wr_by_rank_day)

# Aggregate across sets
wr_by_day_totals <- wr_by_day %>%
  group_by(rank, day) %>%
  summarize(
    n_won = sum(n_won),
    n_total = sum(n_total),
    .groups = "drop"
  ) %>%
  mutate(win_rate = n_won/n_total) %>%
  mutate(rank = as.factor(rank) %>%
    fct_relevel(c("bronze", "silver", "gold", "platinum", "diamond", "mythic")) %>%
    fct_rev()
    )

# Set labels for plot
rank_labs <- wr_by_day_totals %>%
  filter(day == max(day))

# Make plot
ggplot(wr_by_day_totals, aes(x = day, y = win_rate, color = rank, group = rank)) +
  geom_point(aes(size = n_total)) +
  geom_line() +
  geom_label_repel(
    data = rank_labs,
    aes(label = rank),
    nudge_x = 5, direction = "y", hjust = "right", size = 6
  ) +
  theme_grey(base_size = 24) +
  scale_size_continuous(label = scales::label_number(big.mark = ",")) +
  scale_y_continuous(label = scales::label_percent()) +
  guides(color = "none") +
  labs(x = "Day of the Month", y = "Win Rate", size = "Num. games") +
  theme(legend.position = "bottom")