Upload app.py

app.py

@@ -40,8 +40,13 @@ if 'Contract_Years_Left' in df.columns:
     df['Contract_Years_Left'] = df['Contract_Years_Left'].clip(0.5, 6.0)
 if 'Injury_Days_Total_24m' in df.columns:
     df['Injury_Days_Total_24m'] = df['Injury_Days_Total_24m'].clip(0, 500)
-if 'market_value_in_eur_x' in df.columns:
-    df['market_value_in_eur_x'] = df['market_value_in_eur_x'].clip(0, 300_000_000)
+# Standardize market value column name for the model
+for col in ['market_value_in_eur_x', 'market_value_in_eur_y']:
+    if col in df.columns:
+        df.rename(columns={col: 'market_value_in_eur'}, inplace=True)
+
+if 'market_value_in_eur' in df.columns:
+    df['market_value_in_eur'] = df['market_value_in_eur'].clip(0, 300_000_000)
 
 # ======= Sidebar =======
 st.sidebar.header("Player Transfer Profile")
@@ -91,9 +96,9 @@ else:
     injuries = st.sidebar.number_input("Injury missed days (24m)", 0, 500, 10)
     
     # Can let them modify other numerical features as well
-    if 'market_value_in_eur_x' in player_data.columns:
+    if 'market_value_in_eur' in player_data.columns:
         m_val = st.sidebar.number_input("Current Market Value Estimation (£m)", 1.0, 150.0, 20.0)
-        player_data['market_value_in_eur_x'] = (m_val * 1_000_000) / 0.85
+        player_data['market_value_in_eur'] = (m_val * 1_000_000) / 0.85
 
 asking_price = st.sidebar.number_input("Selling Club Asking Price (£m)", 1.0, 200.0, 45.0)
 
@@ -206,5 +211,5 @@ st.markdown("---")
 st.subheader("Model Performance Assessment")
 st.markdown(f"**Training Set Size:** `{len(df):,}` verified transfers")
 st.markdown(f"**Features Engined:** `{len(model.feature_names_in_)}` columns")
-st.markdown("**Validation MAE (Mean Absolute Error):** `~£5,400,000` *(Error Margin)*")
-st.caption("Training occurred utilizing a 3-Folds GridSearch with learning rate iteration.")
+st.markdown("**Validation MAE (Mean Absolute Error):** `~£23,980,000` *(Statistical Range)*")
+st.caption("Training occurred utilizing a 5-Folds RandomizedSearchCV across 40 hyperparameter iterations.")