Python language using sci-kit learn and Selenium to scrape mlb websites and collection information to get inputs and outputs to potentially predict who will win the next game.

The machine learning model is designed to essentially predict which team is going to win the game

• A python script will navigate through https://www.espn.com/mlb/schedule/_/20190320
• It will iterate through and collect the scores and that will be the outputs we want from the data
• Each game has information that will essentially be our inputs for the model to train on
• This is going be a work of web scraping to collect that data and store it into a type of data format (JSON, CSV, etc

Linear Regression Model because the inputs have a strong correlation on the output of the game

Step 1: Using Selenium package to create a webdriver to open the desired web page to scrape

path_to_chromedriver = 'chromedriver.exe'
browser = webdriver.Chrome(executable_path=path_to_chromedriver)
date = datetime.datetime(2019, 3, 20)
date = date.strftime('%Y%m%d')
url = 'https://www.espn.com/mlb/schedule/_/date/{}'.format(date)
browser.get(url)