This is the second video in a series where we will attempt to predict the winning probabilities for Major League Baseball games using modern machine learning techniques. In this video we explore the data frame we previously built, and then use gradient boosting to build a model to predict the winning probability of each team based on team-level hitting statistics only.
Data: www.retrosheet.org
Notebook: https://github.com/numeristical/resources/tree/master/BaseballPred/BP_2_BuildingFirstModel.ipynb
Personal links:
Consulting: www.numeristical.com
Github: https://github.com/numeristical