Update app.R

app.R

@@ -2095,25 +2095,19 @@ standardize_stuffplus_to_league <- function(data, league_comparison_data) {
   data <- ensure_stuff_inputs(data)
   league_comparison_data <- ensure_stuff_inputs(league_comparison_data)
   
-  # FIX: Convert Date columns to character in both datasets before binding
-  if ("Date" %in% names(data)) data$Date <- as.character(data$Date)
-  if ("Date" %in% names(league_comparison_data)) league_comparison_data$Date <- as.character(league_comparison_data$Date)
-  
-  # Also handle any other potentially mismatched columns
-  convert_to_char <- function(df, cols) {
-    for (col in cols) {
-      if (col %in% names(df)) df[[col]] <- as.character(df[[col]])
+  common_cols <- intersect(names(data), names(league_comparison_data))
+  
+  for (col in common_cols) {
+    type1 <- class(data[[col]])[1]
+    type2 <- class(league_comparison_data[[col]])[1]
+    
+    if (type1 != type2) {
+      message("Converting mismatched column '", col, "': ", type1, " vs ", type2)
+      data[[col]] <- as.character(data[[col]])
+      league_comparison_data[[col]] <- as.character(league_comparison_data[[col]])
     }
-    df
   }
   
-  problem_cols <- c("Date", "Time", "Tilt", "UTCTime" "UTCDate", "UTCDateTime", "LocalDateTime", 
-                    "HomeTeamForeignID", "AwayTeamForeignID", "GameUID", 
-                    "PitchUID", "PlayID")
-  
-  data <- convert_to_char(data, problem_cols)
-  league_comparison_data <- convert_to_char(league_comparison_data, problem_cols)
-  
   data$raw_stuff <- predict(stuffplus_model, data, type = "numeric")$.pred
 
   data <- data %>%