# Baseball Payroll Project Proposal

Teddy Weaver

Andrew Leopold

Jon Getz

Professor Bruff

Math 216

Applications Proposal

March 26, 2012

It is almost summer and to many sports fans that means that the only thing on is baseball.  While there have been numerous debates over the years, both on television and radio, about whether pitching or hitting wins championships, there is one statistic that generally seems to get overlooked: team salary. Baseball has one of the most lax salary caps in professional sports, which often leads to debate over its fairness. Does having a higher payroll lead to a more winning team? Or do player’s salaries not bear any impact on a team’s performance?

There have been many teams throughout the history of baseball to make arguments for both sides. There have been teams such as the 2003 Oakland Athletics, who were portrayed in the book (and movie), Moneyball, who managed to turn a small team salary budget into a playoff contender. But is this just an exception to the rule, or do teams with low budgets often succeed? It is common knowledge that teams such as the New York Yankees, Philadelphia Phillies, and Boston Red Sox consistently have some of the highest payrolls in baseball, nearing \$200 million, and are perennial playoff teams.  But there are teams such as the Tampa Bay Rays who have a team salary of around \$70 million and continuously make the playoffs. The 2003 World Series Champion Florida Marlins who had the sixth lowest team salary in the league that year at \$49 million.

Is a team’s salary an indication of their playoff potential? To answer this question we will first look at the salaries of teams from the last ten seasons (2002-2011).  We are limiting it to the last ten seasons to help prevent accounting for large changes in inflation and player value.  For each season, the team’s salary and salary rank will be recorded along with the playoff teams and World Series champions of that year.  Standard deviations of playoff teams and their salaries would be calculated, and use to determine confidence intervals for each team.

Two of the methods that we will use for statistical analysis are confidence intervals and hypothesis testing.  We will propose a null hypothesis from the data along the lines of: “In order to have a 70% chance of making the playoffs, the team salary needs to be X” and an alternate hypothesis implying a lack of correlation. The null hypothesis will be determined by calculating the percent chance that teams with the top eight highest salaries will make the playoffs. We are using teams with the top eight highest salaries, because only eight teams make the playoffs each year.

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