Update app.py

app.py

@@ -645,46 +645,47 @@ def server(input, output, session):
                     }
                 levelt = {
                     11:1,
-                    14:4
+                    14:4,
+                    
                     }
 
-
-                fg_api = f'https://www.fangraphs.com/api/leaders/minor-league/data?pos=all&level={levelt[sport_id]}&lg={lg_dict[sport_id]}&stats=pit&qual=0&type=2&team=&season=2024&seasonEnd=2024&org=&ind=0&splitTeam=false'
-                response = requests.get(fg_api)
-                data = response.json()
-                df_fg = pl.DataFrame(data)
-                if pitcher_id not in dict_mlb_fg.keys():
-                    #ax_fv_table.text(x=0.5, y=0.5, s='No Scouting Data', style='italic', ha='center', va='center', fontsize=20, bbox=dict(facecolor='white', alpha=1, pad=10))
-                    metrics_data = {
-                        "Pitches": new_player_metrics['pitches'][0],
-                        "PA": new_player_metrics['pa'][0],
-                        "BIP": new_player_metrics['bip'][0],
-                        "HR": f"{new_player_metrics['home_run'][0]:.0f}",
-                        "K": f"{new_player_metrics['k'][0]:.0f}",
-                        "BB": f"{new_player_metrics['bb'][0]:.0f}",
-                    }
-                else:
-                    df_fg_filter = df_fg.filter(pl.col('minormasterid') == dict_mlb_fg[pitcher_id])
-                    # Metrics data table
-                    metrics_data = {
-                        "G": f"{df_fg_filter['G'][0]:.0f}",
-                        "IP": f"{df_fg_filter['IP'][0]:.1f}",
-                        "Pitches": f"{new_player_metrics['pitches'][0]:.0f}",
-                        "PA": f"{df_fg_filter['TBF'][0]:.0f}",
-                        "BIP": new_player_metrics['bip'][0],
-                        "ERA": f"{df_fg_filter['ERA'][0]:.2f}",
-                        "FIP": f"{df_fg_filter['FIP'][0]:.2f}",
-                        "WHIP": f"{df_fg_filter['WHIP'][0]:.2f}",
-                    }
-                df_table = pd.DataFrame(metrics_data, index=[0])
-                ax_table.axis('off')
-                table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
-                for key, cell in table.get_celld().items():
-                    if key[0] == 0:
-                        cell.set_text_props(fontweight='bold')
-                table.auto_set_font_size(False)
-                table.set_fontsize(12)
-                table.scale(1, 1.5)
+                if sport_id != 17:
+                    fg_api = f'https://www.fangraphs.com/api/leaders/minor-league/data?pos=all&level={levelt[sport_id]}&lg={lg_dict[sport_id]}&stats=pit&qual=0&type=2&team=&season=2024&seasonEnd=2024&org=&ind=0&splitTeam=false'
+                    response = requests.get(fg_api)
+                    data = response.json()
+                    df_fg = pl.DataFrame(data)
+                    if pitcher_id not in dict_mlb_fg.keys():
+                        #ax_fv_table.text(x=0.5, y=0.5, s='No Scouting Data', style='italic', ha='center', va='center', fontsize=20, bbox=dict(facecolor='white', alpha=1, pad=10))
+                        metrics_data = {
+                            "Pitches": new_player_metrics['pitches'][0],
+                            "PA": new_player_metrics['pa'][0],
+                            "BIP": new_player_metrics['bip'][0],
+                            "HR": f"{new_player_metrics['home_run'][0]:.0f}",
+                            "K": f"{new_player_metrics['k'][0]:.0f}",
+                            "BB": f"{new_player_metrics['bb'][0]:.0f}",
+                        }
+                    else:
+                        df_fg_filter = df_fg.filter(pl.col('minormasterid') == dict_mlb_fg[pitcher_id])
+                        # Metrics data table
+                        metrics_data = {
+                            "G": f"{df_fg_filter['G'][0]:.0f}",
+                            "IP": f"{df_fg_filter['IP'][0]:.1f}",
+                            "Pitches": f"{new_player_metrics['pitches'][0]:.0f}",
+                            "PA": f"{df_fg_filter['TBF'][0]:.0f}",
+                            "BIP": new_player_metrics['bip'][0],
+                            "ERA": f"{df_fg_filter['ERA'][0]:.2f}",
+                            "FIP": f"{df_fg_filter['FIP'][0]:.2f}",
+                            "WHIP": f"{df_fg_filter['WHIP'][0]:.2f}",
+                        }
+                    df_table = pd.DataFrame(metrics_data, index=[0])
+                    ax_table.axis('off')
+                    table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
+                    for key, cell in table.get_celld().items():
+                        if key[0] == 0:
+                            cell.set_text_props(fontweight='bold')
+                    table.auto_set_font_size(False)
+                    table.set_fontsize(12)
+                    table.scale(1, 1.5)
 
                 # Additional subplots for spacing
                 ax_top = fig.add_subplot(gs[0, :])