About

Hello! My name is Andrew Scheiner. I created this page for anyone with an interest in the MLB to use computer science to interactively predict the success of a team. Success for a baseball team is largely measured in wins, and to predict this I use team total WAR. This intriguing stat "measures a player's value in all facets of the game by deciphering how many more wins he's worth than a replacement-level player at his same position" (MLB.com). Basically, it gives a number value to how valuable a player is.

To acquire my data, I used Baseball Reference, which provided each MLB team's combined WAR between all of their players in a given season from the years 2006-2021. I only collected data from this MLB era because this was deemed the "post-steroid era." Please note that I excluded 2020 statistics from this dataset because it was the shortened season affected by the COVID-19 pandemic, hence an outlier.

If you would like to learn more about the process I undertook to develop this site, please check out my personal blog, Connecting the Game!

As a user of this site, you have several options for viewing predictions. For each option, you will have to either select a team, enter WAR value(s), or both. When entering WAR, please try to use one-decimal numbers between 3.0-68.0 for the most reasonable and realistic results. When running each of the predicting options, you will get two different outputs (except for the mass prediction). One is readable output and the other is meant to be copied into a CSV file for data analysis. If you do copy any of the outputs to be used for your own projects or analysis that gets published online, please give me a reference on your site. Thanks!

Make sure to check out the "More Resources" tab to learn more about machine learning, web development and sports predicting!

Thank you and enjoy the website!