Update app.R

app.R

@@ -2871,14 +2871,25 @@ create_count_usage_plot <- function(data, pitcher_name, pitch_colors) {
       pct_label  = ifelse(percentage >= 2, paste0(round(percentage), "%"), "")
     ) %>%
     dplyr::filter(total > 0)
+
+  plot_df <- plot_df %>%
+  group_by(count, BatterSide) %>%
+  arrange(TaggedPitchType) %>%
+  mutate(
+    ymax = cumsum(percentage),
+    ymin = ymax - percentage,
+    label_pos = (ymin + ymax) / 2
+  ) %>%
+  ungroup()
   
   plot_df$count <- factor(plot_df$count, levels = c("0-0", "Ahead", "Behind", "2 Strikes"))
   plot_df$BatterSide <- factor(plot_df$BatterSide, levels = c("Vs Left", "Vs Right"))
-  
-  ggplot(plot_df, aes(x = "", y = percentage, fill = TaggedPitchType)) +
-    geom_bar(width = 1, stat = "identity", color = "white") +
-    geom_text(aes(label = pct_label), position = position_stack(vjust = 0.5), size = 3) +
-    coord_polar("y", start = 0) +
+
+
+ggplot(plot_df, aes(x = 1, y = percentage, fill = TaggedPitchType)) +
+  geom_bar(width = 1, stat = "identity", color = "white") +
+  geom_text(aes(y = label_pos, label = pct_label), size = 3) +
+  coord_polar(theta = "y", start = 0) +
     facet_grid(BatterSide ~ count, labeller = label_value, drop = FALSE) +
     ggtitle("Count Usage") +
     scale_fill_manual(values = pitch_colors, na.translate = FALSE) +