Is it possible to boil down a team sport to a few predictive elements and consistently predict the outcome of competetion? Every game is different - the mental and physical state of ach player, weather, venue conditions, policitcal climate, expectations. Is it possible?
It would appear that it is - at least 70% of the time
I used data compiled from every game of the past 58 seasons of professional baseball in the United States (MLB) to build predictive models. Models include: logistic regression, random forest, adaboost, ensemble voting (of the prevoius three), and an artificial neural net.
I processed and modeled the data in a the Jupyter notebook using python.
All models essentially returned the same reuslt - 70% accuracy.
youtube video with explanation my approach: https://youtu.be/qv5KKVciZeQ
A similar project, which I used as a benchmark for success: http://cs229.stanford.edu/proj2013/JiaWongZeng-PredictingTheMajorLeagueBaseballSeason.pdf