├── .gitignore
└── README.md


/.gitignore:
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1 | NFL_Superbowl_Winner_Model 1_2.ipynb
2 | data.csv
3 | .DS_Store


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/README.md:
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 1 | # NFL Prediction Model
 2 | To predict the match-winners of a gameweek of the National Football League based on game stats parsed from NFL.com's live GameCenter using the [nflgame API](https://github.com/derek-adair/nflgame) - API used in order to get the in-game stats.
 3 | 
 4 | ### Things done 
 5 | * Built a model using RandomForest Classifier and utilized statistics like Rushing Yards per game, Passing Yards per game, etc. after applying Feature Selection.
 6 | * Wrote ETL(Extract,Transform,Load) job to collect stats for the home and away teams for the last 10 years using python nflgameapi.
 7 | 
 8 | #### This project works on python 2.7 as the API first worked only for python 2.7 but this would be updated to python 3 in some time.
 9 | 
10 | The outcome and the predictions for the gameweeks are all posted on my [Blog](https://medium.com/@siddhantthakur08) on Medium. Do check it out.
11 | 
12 | ### If the notebook is not rendering then use the link given below in order to view the ipynb file.
13 | * [nbviewer](https://nbviewer.jupyter.org/)
14 | 


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