Predicting QB Success in the NFL

Last year I wrote and submitted a paper for the MIT Sloan Sports Analytics Conference. While my abstract was accepted my paper was not. The title of my paper was Reducing Risk in the NFL Draft: Using Machine Learning Algorithms to Predict Success in the NFL. You can read the full paper here. 

In it I describe a decision tree model that predicts a college QBs success in the NFL. To train the model I used over 40 variables including college stats, school competitiveness, combine performance, and text mining of pro scouting reports. Ultimately, the final model used 4 variables: college win %, body mass index (BMI), college games started per season, and age. The final model was 88% accurate in predicting whether a college player would be a success or a bust in the NFL. This model can be used to predict whether the top prospects in this year's draft will be successful in the NFL.

Below is an interactive version of that final QB model.