Update app.py

app.py

@@ -43,7 +43,7 @@ st.markdown('<div class="main-container">', unsafe_allow_html=True)
 markdown_text = """
 ## Catch Probability Lookup Tool
 
-This Streamlit app retrieves catch probability data for a selected fielder from Baseball Savant.
+This Streamlit app retrieves catch probability data for a selected fielder from [Baseball Savant](https://baseballsavant.mlb.com/leaderboard/catch_probability).
 The app displays the fielder's data in a table and allows the user to select a 
 row to view the corresponding catch video.
 
@@ -51,10 +51,12 @@ Catch probability data is only available for outfielders.
 
 #### What is Catch Probability?
 *From MLB:*
+
 **Catch Probability** expresses the likelihood for a ball to be caught by an outfielder based on opportunity time, 
 distance needed, and direction. “Opportunity time” starts when the ball is released by the pitcher, 
 and “distance needed” is the shortest distance needed to make the catch.
-Learn more about how direction is accounted for here. [Read more about the details of how Catch Probability works here](https://www.mlb.com/news/statcast-introduces-catch-probability-for-2017-c217802340).
+[Learn more about how direction is accounted for here](https://www.mlb.com/news/catch-probability-updated-to-include-direction-c232532408). 
+[Read more about the details of how Catch Probability works here](https://www.mlb.com/news/statcast-introduces-catch-probability-for-2017-c217802340).
 
 *Columns:*
 - **Batter Name**: Name of the batter
@@ -63,9 +65,9 @@ Learn more about how direction is accounted for here. [Read more about the detai
 - **Position**: Position of the fielder
 - **Event**: Type of play
 - **Out**: Was the ball caught?
-- **Wall**: Did the fielder catch the ball at the wall?
-- **Back**: Did the fielder catch the ball while moving back?
-- **Stars**: Number of stars assigned to the play (1-5)
+- **Wall**: [Did the fielder catch the ball at the wall?](https://www.mlb.com/news/catch-probability-updated-to-account-for-walls-c269814542)
+- **Back**: [Did the fielder catch the ball while moving back?](https://www.mlb.com/news/catch-probability-updated-to-include-direction-c232532408)
+- **Stars**: [Number of stars assigned to the play (1-5)](https://baseballsavant.mlb.com/leaderboard/catch_probability)
 - **Distance**: Distance required to make the catch in feet
 - **Hang Time**: Hang time of the ball in seconds
 - **Catch Rate**: Probability of the catch being made
@@ -84,7 +86,7 @@ fielders = df.drop_duplicates(['batter_id']).sort_values(['batter_name']).set_in
 fielders_reversed = {v: k for k, v in fielders.items()}
 
 # Create a selectbox for selecting a key from the dictionary
-selected_fielder = st.selectbox("Select Fielder:", list(fielders_reversed.keys()))
+selected_fielder = st.selectbox("### Select Fielder:", list(fielders_reversed.keys()))
 
 # Retrieve the corresponding pitcher ID
 fielder_select = fielders_reversed[selected_fielder]
@@ -118,7 +120,7 @@ df_merge = df.merge(df_catch, on='play_id', how='right', suffixes=('', '_fielder
 # Format the 'catch_rate' column as a percentage
 df_merge['catch_rate'] = df_merge['catch_rate'].astype(float).apply(lambda x: f"{x:.0%}")
 
-
+df_merge['pos'] = df_merge['pos'].astype(int)
 df_merge['Position'] = df_merge['pos'].map(pos_dict)
 
 column_names = ['game_date','batter_name', 'pitcher_name', 'name_display_first_last', 'Position','event', 'out', 'wall', 'back', 'stars', 'distance', 'hang_time', 'catch_rate']