Update app.py

app.py

@@ -30,26 +30,66 @@ def get_player_stats(player_id):
 def prediction_section():
     st.header("🧠 Prospect Potential Prediction")
     
-    # Get available teams
-    schedule = get_schedule()
-    teams = {team['team']['id']: team['team']['name'] 
-             for game in schedule['dates'][0]['games'] 
-             for team in [game['teams']['home']['team'], game['teams']['away']['team']]}
-    
-    col1, col2 = st.columns(2)
-    with col1:
-        team_id = st.selectbox("Select Team", options=teams.keys(), format_func=lambda x: teams[x])
-    
-    with col2:
-        roster = get_roster(team_id)['roster']
-        players = {p['person']['id']: p['person']['fullName'] for p in roster}
-        player_id = st.selectbox("Select Prospect", options=players.keys(), format_func=lambda x: players[x])
-    
-    if st.button("Analyze Prospect"):
-        stats = get_player_stats(player_id)
-        # Add your ML model here (placeholder example)
-        st.success(f"Predicted WAR in 3 years: 4.2 (Sample Output)")
-        st.json(stats)  # Show raw data for inspection
+    try:
+        # Get available teams with error handling
+        schedule = get_schedule()
+        teams = {}
+        
+        # Safely navigate through possible missing keys
+        if 'dates' in schedule and len(schedule['dates']) > 0:
+            for date in schedule['dates']:
+                if 'games' in date:
+                    for game in date['games']:
+                        for team_type in ['home', 'away']:
+                            team = game['teams'][team_type].get('team', {})
+                            team_id = team.get('id')
+                            team_name = team.get('name')
+                            if team_id and team_name:
+                                teams[team_id] = team_name
+        
+        if not teams:
+            st.warning("No team data available. Using default teams.")
+            teams = {119: "Los Angeles Dodgers"}  # Fallback
+            
+        col1, col2 = st.columns(2)
+        with col1:
+            team_id = st.selectbox("Select Team", options=teams.keys(), format_func=lambda x: teams[x])
+        
+        with col2:
+            try:
+                roster = get_roster(team_id).get('roster', [])
+                players = {}
+                for p in roster:
+                    person = p.get('person', {})
+                    players[person.get('id')] = person.get('fullName', 'Unknown Player')
+                
+                if not players:
+                    st.error("No players found for this team")
+                    return
+                    
+                player_id = st.selectbox("Select Prospect", options=players.keys(), format_func=lambda x: players[x])
+            
+            except Exception as e:
+                st.error(f"Error loading roster: {str(e)}")
+                return
+
+        if st.button("Analyze Prospect"):
+            try:
+                stats = get_player_stats(player_id)
+                # Add proper error handling for stats data
+                if not stats:
+                    st.error("No player stats available")
+                    return
+                
+                # Placeholder for actual model prediction
+                st.success(f"Predicted WAR in 3 years: 4.2 (Sample Output)")
+                st.json(stats)  # Show raw data for inspection
+                
+            except Exception as e:
+                st.error(f"Analysis failed: {str(e)}")
+
+    except Exception as e:
+        st.error(f"Failed to load schedule data: {str(e)}")
 
 
 def comparison_tool():