The goal of this project is to simulate the 2018 World Series winner using publicly available team data. We'll define a series of functions that compute simularity between teams using the Nearest Neighbors sklearn model, then simulate games using performance against an opponents similar batting neighbors (for pitchers) and pitching neighbors (for batters).

We'll then randomly select scores from the distribution, assign a winner, simulate the series, then repeat the process over the course of 20,000 simulations and calculated the odds of a team winning the series.

The accompanying write-up can be found on Medium here: https://medium.com/@jordanbean/simulating-the-2018-world-series-45bc16e3aa27