Update app.py

app.py

@@ -235,29 +235,60 @@ def main():
     player_name = st.sidebar.selectbox("Select Player", player_list)
 
     if player_name:
+        # Retrieve player details
         player_row = player_data[player_data['player_name'] == player_name]
         team_name = player_row.iloc[0]['team_abbreviation']
         position = player_row.iloc[0]['position']
 
-        stats_columns = ['age', 'player_height', 'player_weight']
-        default_stats = {stat: player_row.iloc[0][stat] for stat in stats_columns}
-
-        for stat in default_stats.keys():
-            default_stats[stat] = st.sidebar.number_input(f"{stat}", value=default_stats[stat])
-
-        injury_type = st.sidebar.selectbox("Select Hypothetical Injury", injury_types)
-        default_days_injured = average_days_injured.get(injury_type, 30)
-        days_injured = st.sidebar.slider("Estimated Days Injured", 0, 365, int(default_days_injured))
-        injury_occurrences = st.sidebar.number_input("Injury Occurrences", min_value=0, value=1)
-
-        input_data = pd.DataFrame([{
-            "days_injured": days_injured,
-            "injury_occurrences": injury_occurrences,
-            "position": position_mapping.get(position, 0),
-            "injury_type": injury_type,
-            **default_stats
-        }])
-        input_data["injury_type"] = pd.factorize(input_data["injury_type"])[0]
+        if not player_row.empty:
+            position = player_row.iloc[0]['position']
+            position_numeric = position_mapping.get(position, 0)
+
+            st.sidebar.write(f"**Position**: {position} (Numeric: {position_numeric})")
+
+            # Default values for features
+            stats_columns = ['age', 'player_height', 'player_weight']
+            default_stats = {
+                stat: player_row.iloc[0][stat] if stat in player_row.columns else 0
+                for stat in stats_columns
+            }
+
+            # Allow manual adjustment of stats
+            for stat in default_stats.keys():
+                default_stats[stat] = st.sidebar.number_input(f"{stat}", value=default_stats[stat])
+
+            # Injury details
+            injury_type = st.sidebar.selectbox("Select Hypothetical Injury", injury_types)
+            # Replace slider with default average based on injury type
+            default_days_injured = average_days_injured[injury_type] or 30  # Use 30 if None
+            days_injured = st.sidebar.slider(
+                "Estimated Days Injured",
+                0,
+                365,
+                int(default_days_injured),
+                help=f"Default days for {injury_type}: {int(default_days_injured) if default_days_injured else 'N/A'}"
+            )            
+            injury_occurrences = st.sidebar.number_input("Injury Occurrences", min_value=0, value=1)
+
+            # Prepare input data
+            input_data = pd.DataFrame([{
+                "days_injured": days_injured,
+                "injury_occurrences": injury_occurrences,
+                "position": position_numeric,
+                "injury_type": injury_type,  # Include the selected injury type
+                **default_stats
+            }])
+
+            # Encode injury type
+            input_data["injury_type"] = pd.factorize(input_data["injury_type"])[0]
+
+            # Load Random Forest model
+            try:
+                rf_model = load_rf_model()
+
+                # Align input data with the model's feature names
+                expected_features = rf_model.feature_names_in_
+                input_data = input_data.reindex(columns=rf_model.feature_names_in_, fill_value=0)
 
         st.divider()
         st.header("Player Overview")