I have made my submissions for the kaggle competition, i will run the

re trained the models on only tournament games and the ChalkSeedDiff

working on training neural networks and evaluating performance against

adding the opponent chalk seed so that we can make baseline predictions

split up the mens and womens data and beginning building a neural

making new super detailed games dataframe where each row is a game, and

adding all sorts of diff data to the team aggregated stats

went back and fixed an issue in pre processing, realized that I was not

got rid of unnessessary tournament and regular season split attributes

merging the regular season stats and the tournament stats together and

did the same merge and aggregation for the detailed tournament data

working through aggregating the regular season data, deleted the data

columns that did not need to be aggregated were being aggregated. I

working on a new pre processing file with a much better approach to the