├── .gitignore ├── LICENSE ├── Procfile ├── README.md ├── __pycache__ └── app.cpython-37.pyc ├── app.py ├── model └── ipl_model.pkl ├── requirements.txt └── templates └── main.html /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2020 Harsh Bardhan Mishra 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /Procfile: -------------------------------------------------------------------------------- 1 | web: gunicorn app:app 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 |
3 |

4 | 5 | Logo 6 | 7 | 8 |

IPL Match Predictor

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11 | A simple Machine Learning Application developed and deployed on Flask Web Framework to predict an IPL Match Winner 🏏🎰 12 |
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16 | 17 | ## About The Project 18 | 19 | IPL Match Predictor is a Flask Application that deploys a Machine Learning Model that can predict the winner of an IPL Match. The Algorithm 20 | used to develop and deploy the Machine Learning Application was Random Forest and has been developed to research intuitive work on utilizing Machine Learning in Sports and Academics. The project was displayed during Project Expo held on February 1, 2020 at Sathyabama Institute of Science and Technology. 21 | 22 | ## Technology Stack 23 | 24 | * [Flask](https://github.com/pallets/flask) 25 | * [HTML](https://www.w3.org/TR/html52/) 26 | * [CSS](https://developer.mozilla.org/en-US/docs/Web/CSS) 27 | * [Bootstrap](https://getbootstrap.com/) 28 | 29 | ## Local Installation 30 | 31 | 1. Drop a ⭐ on the Github Repository. 32 | 2. Clone the Repo by going to your local Git Client and pushing in the command: 33 | 34 | ```sh 35 | git clone https://github.com/HarshCasper/IPL-Match-Predictor.git 36 | ``` 37 | 38 | 3. Install the Packages: 39 | ```sh 40 | pip install -r requirements.txt 41 | ``` 42 | 43 | 4. At last, push in the command: 44 | ```sh 45 | python app.py 46 | ``` 47 | 48 | 5. Go to ` http://127.0.0.1:5000/` and enjoy the application. 49 | 50 | ## LICENSE 51 | 52 | [MIT](https://github.com/HarshCasper/IPL-Match-Predictor/blob/master/LICENSE) 53 | -------------------------------------------------------------------------------- /__pycache__/app.cpython-37.pyc: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/HarshCasper/IPL-Match-Predictor/d82d13730644b51cec18d5573ec04fd4867d9b62/__pycache__/app.cpython-37.pyc -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | import flask 2 | import pickle 3 | import pandas as pd 4 | import numpy as np 5 | 6 | with open(f'model/ipl_model.pkl', 'rb') as f: 7 | model = pickle.load(f) 8 | 9 | app = flask.Flask(__name__, template_folder='templates') 10 | 11 | @app.route('/', methods=["GET", "POST"]) 12 | def main(): 13 | if flask.request.method == 'GET': 14 | return(flask.render_template('main.html')) 15 | 16 | if flask.request.method == 'POST': 17 | city = flask.request.form['city'] 18 | Home = flask.request.form['Home'] 19 | Away = flask.request.form['Away'] 20 | toss_winner = flask.request.form['toss_winner'] 21 | toss_decision = flask.request.form['toss_decision'] 22 | venue = flask.request.form['venue'] 23 | 24 | if toss_winner == 'Home Team': 25 | toss_winner = Home 26 | else: 27 | toss_winner = Away 28 | 29 | input_variables = pd.DataFrame([[city, Home, Away, toss_winner, toss_decision, venue]], columns=['city', 'Home', 'Away', 'toss_winner', 30 | 'toss_decision', 'venue'], dtype=object) 31 | 32 | input_variables.Home.replace(['Sunrisers Hyderabad', 'Mumbai Indians', 'Gujarat Lions', 33 | 'Rising Pune Supergiant', 'Royal Challengers Bangalore', 34 | 'Kolkata Knight Riders', 'Delhi Capitals', 'Kings XI Punjab', 35 | 'Chennai Super Kings', 'Rajasthan Royals', 'Deccan Chargers', 36 | 'Kochi Tuskers Kerala', 'Pune Warriors', 'Rising Pune Supergiants'], 37 | np.arange(0, 14), inplace=True) 38 | input_variables.Away.replace(['Sunrisers Hyderabad', 'Mumbai Indians', 'Gujarat Lions', 39 | 'Rising Pune Supergiant', 'Royal Challengers Bangalore', 40 | 'Kolkata Knight Riders', 'Delhi Capitals', 'Kings XI Punjab', 41 | 'Chennai Super Kings', 'Rajasthan Royals', 'Deccan Chargers', 42 | 'Kochi Tuskers Kerala', 'Pune Warriors', 'Rising Pune Supergiants'], 43 | np.arange(0, 14), inplace=True) 44 | #input_variables['toss_winner'] = np.where(input_variables['toss_winner'] == 'Home Team', input_variables['Home'], input_variables['Away']) 45 | input_variables.toss_winner.replace(['Sunrisers Hyderabad', 'Mumbai Indians', 'Gujarat Lions', 46 | 'Rising Pune Supergiant', 'Royal Challengers Bangalore', 47 | 'Kolkata Knight Riders', 'Delhi Capitals', 'Kings XI Punjab', 48 | 'Chennai Super Kings', 'Rajasthan Royals', 'Deccan Chargers', 49 | 'Kochi Tuskers Kerala', 'Pune Warriors', 'Rising Pune Supergiants'], 50 | np.arange(0, 14), inplace=True) 51 | input_variables.toss_decision.replace(['bat', 'field'], [0, 1], inplace=True) 52 | input_variables.city.replace(['Hyderabad', 'Pune', 'Rajkot', 'Indore', 'Bangalore', 'Mumbai', 53 | 'Kolkata', 'Delhi', 'Chandigarh', 'Kanpur', 'Jaipur', 'Chennai', 54 | 'Cape Town', 'Port Elizabeth', 'Durban', 'Centurion', 55 | 'East London', 'Johannesburg', 'Kimberley', 'Bloemfontein', 56 | 'Ahmedabad', 'Cuttack', 'Nagpur', 'Dharamsala', 'Kochi', 57 | 'Visakhapatnam', 'Raipur', 'Ranchi', 'Abu Dhabi', 'Sharjah'], 58 | np.arange(0, 30), inplace=True) 59 | input_variables.venue.replace(['Rajiv Gandhi International Stadium, Uppal', 60 | 'Maharashtra Cricket Association Stadium', 61 | 'Saurashtra Cricket Association Stadium', 'Holkar Cricket Stadium', 62 | 'M Chinnaswamy Stadium', 'Wankhede Stadium', 'Eden Gardens', 63 | 'Feroz Shah Kotla', 64 | 'Punjab Cricket Association IS Bindra Stadium, Mohali', 65 | 'Green Park', 'Punjab Cricket Association Stadium, Mohali', 66 | 'Sawai Mansingh Stadium', 'MA Chidambaram Stadium, Chepauk', 67 | 'Dr DY Patil Sports Academy', 'Newlands', "St George's Park", 68 | 'Kingsmead', 'SuperSport Park', 'Buffalo Park', 69 | 'New Wanderers Stadium', 'De Beers Diamond Oval', 70 | 'OUTsurance Oval', 'Brabourne Stadium', 71 | 'Sardar Patel Stadium, Motera', 'Barabati Stadium', 72 | 'Vidarbha Cricket Association Stadium, Jamtha', 73 | 'Himachal Pradesh Cricket Association Stadium', 'Nehru Stadium', 74 | 'Dr. Y.S. Rajasekhara Reddy ACA-VDCA Cricket Stadium', 75 | 'Subrata Roy Sahara Stadium', 76 | 'Shaheed Veer Narayan Singh International Stadium', 77 | 'JSCA International Stadium Complex', 'Sheikh Zayed Stadium', 78 | 'Sharjah Cricket Stadium'], 79 | np.arange(0, 34), inplace=True) 80 | prediction = model.predict(input_variables) 81 | prediction = pd.DataFrame(prediction, columns=['Winners']) 82 | prediction = prediction["Winners"].map({0:'Sunrisers Hyderabad', 1:'Mumbai Indians', 2:'Gujarat Lions', 83 | 3:'Rising Pune Supergiant', 4:'Royal Challengers Bangalore', 84 | 5:'Kolkata Knight Riders', 6:'Delhi Capitals', 7:'Kings XI Punjab', 85 | 8:'Chennai Super Kings', 9:'Rajasthan Royals', 10:'Deccan Chargers', 86 | 11:'Kochi Tuskers Kerala', 12:'Pune Warriors', 13:'Rising Pune Supergiants'}) 87 | return flask.render_template('main.html', original_input={'city':city, 'Home':Home, 'Away':Away, 'toss_winner':toss_winner, 'toss_decision':toss_decision, 88 | 'venue':venue}, 89 | result=prediction[0], 90 | ) 91 | 92 | if __name__=='__main__': 93 | app.run(debug="True") 94 | -------------------------------------------------------------------------------- /model/ipl_model.pkl: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/HarshCasper/IPL-Match-Predictor/d82d13730644b51cec18d5573ec04fd4867d9b62/model/ipl_model.pkl -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | flask 2 | pandas 3 | numpy 4 | -------------------------------------------------------------------------------- /templates/main.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 27 | 28 | 29 | 30 | 31 | 32 | 34 | 35 |
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37 | IPL Match Predictor using Machine Learning 38 |
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By Harsh Bardhan Mishra
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46 | Input Values: 47 |
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129 | {% if result %} 130 | {% for variable, value in original_input.items() %} 131 | {{ variable }} : {{ value }} 132 | {% endfor %} 133 |
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Predicted Winner: 135 |

{{ result }}

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