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| import streamlit as st | |
| import pandas as pd | |
| import pickle | |
| # Declaring the teams | |
| #st.write("Made_By_Arpon_Mandal") | |
| st.set_page_config( | |
| page_title="BPL Win Predictor", | |
| page_icon="🔥", | |
| layout="centered", | |
| initial_sidebar_state="auto", | |
| ) | |
| st.markdown( | |
| """ | |
| <h2 style='text-align: center'> | |
| BPL Win Predictor | |
| </h2> | |
| <h6 style='text-align: center'> | |
| Made_By_Arpon_Mandal | |
| </h6> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.markdown( | |
| """ | |
| <p style='text-align: center'> | |
| <a href='https://github.com/arponmandal/BPL-win-prediction' target='_blank'>https://github.com/arponmandal/BPL-win-prediction</a> | |
| <br /> | |
| Follow me for more! <a href='https://www.facebook.com/arpon0007' target='_blank'> <img src="https://img.icons8.com/color/48/000000/facebook.png" height="30"></a><a href='https://github.com/arponmandal' target='_blank'><img src="https://img.icons8.com/fluency/48/000000/github.png" height="27"></a><a href='https://www.linkedin.com/in/arponmandal' target='_blank'><img src="https://img.icons8.com/fluency/48/000000/linkedin.png" height="30"></a> | |
| </p> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.write("##") | |
| teams = ['Comilla Victorians', | |
| 'Fortune Barishal', | |
| 'Chattogram Challengers', | |
| 'Khulna Tigers', | |
| 'Minister Dhaka', | |
| 'Sylhet Sunrisers', | |
| 'Rajshahi Royals', | |
| 'Rangpur Rangers' | |
| ] | |
| # declaring the venues | |
| cities = ['Chattogram', 'Khulna', 'Dhaka', 'Sylhet'] | |
| pipe = pickle.load(open('pipe.pkl', 'rb')) | |
| #st.title('BPL Win Predictor') | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| battingteam = st.selectbox('Select the batting team', sorted(teams)) | |
| with col2: | |
| bowlingteam = st.selectbox('Select the bowling team', sorted(teams)) | |
| city = st.selectbox( | |
| 'Select the city where the match is being played', sorted(cities)) | |
| target = st.number_input('Target') | |
| col3, col4, col5 = st.columns(3) | |
| with col3: | |
| score = st.number_input('Score') | |
| with col4: | |
| overs = st.number_input('Overs Completed') | |
| with col5: | |
| wickets = st.number_input('Wickets Fallen') | |
| if st.button('Predict Probability'): | |
| runs_left = target-score | |
| balls_left = 120-(overs*6) | |
| wickets = 10-wickets | |
| currentrunrate = score/overs | |
| requiredrunrate = (runs_left*6)/balls_left | |
| input_df = pd.DataFrame({'batting_team': [battingteam], 'bowling_team': [bowlingteam], 'city': [city], 'runs_left': [runs_left], 'balls_left': [ | |
| balls_left], 'wickets': [wickets], 'total_runs_x': [target], 'cur_run_rate': [currentrunrate], 'req_run_rate': [requiredrunrate]}) | |
| result = pipe.predict_proba(input_df) | |
| lossprob = result[0][0] | |
| winprob = result[0][1] | |
| st.header(battingteam+"- "+str(round(winprob*100))+"%") | |
| st.header(bowlingteam+"- "+str(round(lossprob*100))+"%") | |