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c644018
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1 Parent(s): cf900c4

Update app.py

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Files changed (1) hide show
  1. app.py +23 -0
app.py CHANGED
@@ -27,6 +27,29 @@ st.markdown(
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  # Wrap the main content in a container with the specified width
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  st.markdown('<div class="main-container">', unsafe_allow_html=True)
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  # Load the data
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  df = pd.read_csv("2024_regular_data.csv", index_col=[0])
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  df['batter_name_team'] = df['batter_name'] + ' - ' + df['batter_team']
 
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  # Wrap the main content in a container with the specified width
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  st.markdown('<div class="main-container">', unsafe_allow_html=True)
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+ # Example text with links and bullet points
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+ markdown_text = """
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+ ## Catch Probability Lookup Tool
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+
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+ This Streamlit app retrieves catch probability data for a selected fielder from Baseball Savant.
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+ The app displays the fielder's data in a table and allows the user to select a
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+ row to view the corresponding catch video.
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+
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+ Catch probability data is only available for outfielders.
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+
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+ #### What is Catch Probability?
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+ *From MLB:*
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+ **Catch Probability** expresses the likelihood for a ball to be caught by an outfielder based on opportunity time,
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+ distance needed, and direction. “Opportunity time” starts when the ball is released by the pitcher,
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+ and “distance needed” is the shortest distance needed to make the catch.
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+ 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).
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+
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+ """
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+
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+ # Display the markdown text in Streamlit
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+ st.markdown(markdown_text)
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+
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+
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  # Load the data
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  df = pd.read_csv("2024_regular_data.csv", index_col=[0])
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  df['batter_name_team'] = df['batter_name'] + ' - ' + df['batter_team']