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Procfile
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web: sh setup.sh && streamlit run app.py
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app.py
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import streamlit as st
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import pickle
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import pandas as pd
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teams = ['Sunrisers Hyderabad',
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'Mumbai Indians',
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'Royal Challengers Bangalore',
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'Kolkata Knight Riders',
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'Kings XI Punjab',
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'Chennai Super Kings',
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'Rajasthan Royals',
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'Delhi Capitals']
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cities = ['Hyderabad', 'Bangalore', 'Mumbai', 'Indore', 'Kolkata', 'Delhi',
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'Chandigarh', 'Jaipur', 'Chennai', 'Cape Town', 'Port Elizabeth',
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'Durban', 'Centurion', 'East London', 'Johannesburg', 'Kimberley',
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'Bloemfontein', 'Ahmedabad', 'Cuttack', 'Nagpur', 'Dharamsala',
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'Visakhapatnam', 'Pune', 'Raipur', 'Ranchi', 'Abu Dhabi',
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'Sharjah', 'Mohali', 'Bengaluru']
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pipe = pickle.load(open('pipe.pkl','rb'))
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st.title('IPL Win Predictor')
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col1, col2 = st.beta_columns(2)
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with col1:
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batting_team = st.selectbox('Select the batting team',sorted(teams))
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with col2:
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bowling_team = st.selectbox('Select the bowling team',sorted(teams))
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selected_city = st.selectbox('Select host city',sorted(cities))
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target = st.number_input('Target')
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col3,col4,col5 = st.beta_columns(3)
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with col3:
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score = st.number_input('Score')
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with col4:
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overs = st.number_input('Overs completed')
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with col5:
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wickets = st.number_input('Wickets out')
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if st.button('Predict Probability'):
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runs_left = target - score
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balls_left = 120 - (overs*6)
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wickets = 10 - wickets
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crr = score/overs
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rrr = (runs_left*6)/balls_left
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input_df = pd.DataFrame({'batting_team':[batting_team],'bowling_team':[bowling_team],'city':[selected_city],'runs_left':[runs_left],'balls_left':[balls_left],'wickets':[wickets],'total_runs_x':[target],'crr':[crr],'rrr':[rrr]})
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result = pipe.predict_proba(input_df)
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loss = result[0][0]
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win = result[0][1]
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st.header(batting_team + "- " + str(round(win*100)) + "%")
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st.header(bowling_team + "- " + str(round(loss*100)) + "%")
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requirements.txt
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streamlit
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pandas
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numpy
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sklearn
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setup.sh
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mkdir -p ~/.streamlit/
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echo "\
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[server]\n\
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port = $PORT\n\
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enableCORS = false\n\
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headless = true\n\
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\n\
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" > ~/.streamlit/config.toml
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