Kae Jonishi, the protagonist in the case, is a marketing analyst at Force Energy (Force). Her company has advertised with Major League Baseball (MLB) teams in the past and has gained moderate amounts of exposure from these marketing campaigns. However, Jonishi’s manager wants to increase the company’s exposure to MLB fans. One way to do so is to sponsor teams that are likely to advance into the MLB post-season, or playoffs. The top performing teams during the MLB regular season advance into the playoffs and increase their fan base, which results in greater marketing exposure for advertisers.Jonishi has access to a data set that contains aggregate team statistics for offence and pitching performance during all MLB seasons from 1995 to 2019. With adequate knowledge of both baseball and data science, Jonishi begins by analyzing and visualizing the data. She then builds a machine learning model that can predict whether a team will make the playoffs. Using this model, Jonishi can input future offence and defence performance predictions to determine if the team would have advanced to the playoffs in previous years.
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