In this research poster we are exploring the possibility that the statistic of WAR (wins above replacement) can have some predictive qualities in determining what a player’s salary may be following the signing of a new contract. The group of players that was studied was the free agent class going into the league year of 2019 (here on to be preferred to as the free agent class of 2018). These players’ contracts with their current team expired at the conclusion of the 2019 season. Some players were removed from this sample set for a variety of reasons that will be addressed in the data and methodology section of this paper. Additional data on these players (age, position, and categorical race) was also gathered to see if they had any bearing in predicting a player’s salary. When the regression was run, the variables WAR and age were statistically significant at the 5% level in having some predictive qualities of salary. This regression model is important to study because it can give a better idea of what players are underpaid and overpaid based on the amount of value (WAR) that the player provides to the team.
Dr. Sam Schreyer
Economics, Finance, & Accounting
Copyright the Author(s)
"How have advanced statistics impacted salary in major league baseball?,"
SACAD: John Heinrichs Scholarly and Creative Activity Days: Vol. 2022, Article 22.
Available at: https://scholars.fhsu.edu/sacad/vol2022/iss2022/22