Accurately assessing Major League Baseball player value is at the core of consistent success for any MLB organization. Effectively targeting players in trades and strategically spending available funds in the free agent market are of increasing importance as MLB salaries rise. In a sport where it takes 162 games to separate contenders, any advantage in identifying talent can be the difference between winning and losing. This paper draws team batting data from the past seven MLB seasons and runs a multi-variable regression to measure the run value of each individual batting outcome. If teams can more accurately measure the offensive value a player produces, they can more optimally spend their finances. Our regression results suggest that previously used statistics such as wOBA and OPS neglect outcome that have significant effects: baserunning ability and out type. Further contract analysis on four free-agent signing from 2018-2019 free agent class illustrate that teams often over and underestimate player value and could benefit greatly with more accurate player evaluation.