Abstract: As never before, Major League Baseball (MLB) teams are turning to analytics in an attempt to gain a number of small advantages that, in the composite, may result in significantly altering the odds of winning in their favor. This changing mindset was on full display during the 2016 MLB postseason, where teams showcased several strategies attributed to the field of sabermetrics [3, 6, 8]. One of these was their interesting use of relief pitchers; post-season managers removed starting pitchers from games earlier than in any other postseason to date , perhaps to avoid high pitch counts  or to prevent opposing lineups from seeing the same pitcher too many times during a single game . The result was, according to popular media, one of the most exciting World Series in recent memory .
Several issues arise when witnessing paradigm shifts in how baseball is played, and this paper at- tempts to address two interesting ones surrounding the potential use of relief and starting pitchers. Firstly, we look at the home-field advantage and propose a strategy for starters of visiting teams that can be used to remove roughly one half of the first-inning advantage to the home team. A byproduct of this analysis is a set of proper adjustments that must be made to calculate the true home-field advantage, which is roughly 0.429 runs/game, rather than the 0.133 runs/game suggested by the scoring data. Secondly, we wish to tackle the age-old question of when to remove a pitcher from a game by proposing a pitcher-by-pitcher analysis that utilizes data that can be easily measured during a game for real-time decision making.