In this order:

run PlayerDatabase.py to update the postgreSQL player database with salary data, player statistics, and player IDS

run dataModels.py to update the machine learning training models for predictions

run Predictions.py to update the player databases salary predictions for each player

to run the program, run flaskbootstrapapp.py

currently the website allows user to search for a player and it will display their stats and a prediction for annual salary based on weighted war, average war and peak war for their career. User can also explore prediction leaderboards for each salary prediction model.

SOURCES FOR DATA:

USA TODAY for Salary data

ESPN for player statistics

http:https://crunchtimebaseball.com/baseball_map.html for playerIDS