Multiple Regression Analysis Fan Attendance for Major League Baseball Essay

Custom Student Mr. Teacher ENG 1001-04 19 December 2016

Multiple Regression Analysis Fan Attendance for Major League Baseball

Individuals with the desire and resources to own a Major League Baseball team have much more to investigate than the simple choice of logo and mascot. Baseball is a business that is primarily reliant on labor and the capability of that labor to generate revenues. A team’s success is determined not by wins and losses, but like any business, its success is determined by the revenue it generates and its potential for future revenues.

Fan attendance is the major indicator of a team’s capability to generate revenue because it not only determines gate income but it also is a measuring device for the number of television viewers, the amount of team product sales, and the potential valuation for television packages. Although there are many factors that affect fan attendance such as ticket prices, condition of the stadium, and alternate entertainment options, the primary indicators are market size and team payroll. By understanding the relationship between fan attendance, market size, and team payroll, an individual can predict the potential for financial success for his team.

This analysis will examine the hypothesis that both the market size in which the team is located and the total team payroll have a significant positive effect in determining fan attendance. This analysis is based on cross section data of all 29 Major League Baseball (MLB) teams within the United States. The only major league team not included in this analysis is the team located in Toronto, Canada since its market information is not included in the United States’ data. The market rankings used are the 2007 Nielsen Media Research Designated Market Areas (DMA’s) which consist of 210 different metro areas and their nearby counties.

The DMA in which a team is located encompasses the geographic area that not only includes the population in close proximity to the team but it also includes the population within driving distance (Pensa & Brassard, 2006). Market sizes for teams within the New York, Chicago and Los Angeles markets are an estimated apportionment since these markets each share two teams. The payroll data is from the USA Today database of 2007 MLB total team payroll and the attendance figures are totals for home games as determined by Major League Baseball.

The relationship of total team payroll to fan attendance is significant with the assumption that the higher payroll results in a higher level of talented players. Those talented players generally require higher salaries and produce a higher quality of product for the fans. A multiple regression analysis will be used to determine the relationship between fan attendance to market size, and team payroll. The model of market size and payroll amount to fan attendance in general form is Y = X + f(M) + g(P) where Y = Total Fan Attendance, M = Market Size, and P = Payroll.

Within any broad population segment, a portion of that population will attend baseball games so a positive X coefficient is expected. In conjunction, as that market population increases and/or the team payroll increases the attendance total will also increase resulting in the f coefficient > 0 and the g coefficient also > 0. The regression output is shown on Attachment A. The estimated equation is Y = 1,070,291 + . 209M + . 014P with the Y intercept at 1,070,291, the coefficient of M at . 209 and the coefficient of P at . 014.

This equation reveals that the minimum expected attendance for a baseball team; the hard core fans that would attend games simply because they’re available is 1,070,291. In addition, both the M (market) and P (payroll) variables have a positive effect on attendance. The positive . 209 coefficient for the M variable indicates that attendance will increase by 209 fans when the market increases by 1,000 people and the payroll amount remains constant. The positive . 014 coefficient for the P variable indicates that attendance will increase by 14 fans for every $1,000 spent on payroll and market size remains constant.

In the analysis, the adjusted R2 is . 65 indicating that the data explains 65% of the variation of the dependent variables and that the data is reliable. The F stat of 27. 01 indicates a good fit of the data to the regression line and the Significance F of 4. 49638E-07 shows that there is only a . 00004% probability that the good fit of the data is due to chance. In comparing the P-values of the two variables we find that the P-value of Payroll (Variable #2 @ 3. 97143E-5) is significantly smaller than the P-value for Market size (Variable #1 @ . 12277).

The difference in these two values indicates that payroll has a more significant effect on fan attendance than does market size. The data indicates that a baseball organization should be prepared to manage their payroll wisely no matter what size market they are in. By using these two variables to predict fan attendance, teams should be able to successfully predict future revenues. One of the problems that Major League Baseball has dealt with for several years is the amount of competitive advantage that a large market team has over a smaller market team.

Can a team in Milwaukee, Wisconsin with a market population of 882,990 compete with a team in Philadelphia which has a market population of 2,941,450? How do medium market teams such as Cincinnati (886,910 market population) and Cleveland (1,537,500 market population) which are 240 miles apart compete with the team in Denver (1,431,910 market population) which has no competition from other teams within 600 miles? A system where only large market teams are able to win consistently and compete for a championship is not healthy for the league.

As a result of these issues, Major League Baseball has developed a revenue sharing program to assist the financial condition of smaller market teams. The plan is for large market teams with larger income levels to pay a portion of their net local revenues to the smaller market teams. As a result, in 2006 the New York Yankees paid $77 million toward the revenue sharing system and the Boston Red Sox paid $51 million (Ozanian, 2006). A major contention with this plan though is that it was initiated to provide small market teams with additional dollars to reinvest into the payroll to remain competitive but this isn’t occurring in all cases.

A number of small market teams are not reinvesting the shared dollars back into the team payroll but instead are maintaining a low payroll and simply considering the shared revenue dollars as profit. Although team revenues are clearly affected by market size, many other issues concerning the markets can also stimulate or depress the market draw of a baseball team. The average affluence of the market can stimulate revenues while in contrast, a market that depends heavily on an industry that is declining in size and profitability will limit revenues.

The long-term success and competitiveness of a team also has shown to affect the amount of market draw that a team can produce. As with market size, the team payroll is also affected by many issues so that high payrolls do not necessarily result in large revenues. Each team has different strategies and skill levels in evaluating player’s abilities and negotiating contracts. Baseball has its own version of Oil Field Economics. In the 50’s, oil companies bid on offshore drilling rights in the Gulf of Mexico with great uncertainty as to the amount of oil in the areas they were bidding on (Marasco, 2007).

Today, baseball organizations bid on the rights to use a particular player’s skills with great uncertainty as to their future performance. Consider the case of the Colorado Rockies who in 2001 signed pitcher Mike Hampton to an 8 year, $121 million contract (Luft, 2007). For their investment, Hampton accumulated a record of 21 wins and 28 losses over two seasons before they traded him to another team. There are uncertainties in every business but when competitors bid against themselves for a particular product or service, over-payment by the “winner” is likely.

The New York Yankees continually have the highest annual payroll of all teams and is one of the most successful teams on the field but they are the only franchise to lose money in 2006. Kurt Badenhausen, an associated editor at Forbes said: “Only in baseball could the most valuable team also be the only one to lose money. ” (Sessa, 2007) Obviously, payroll (quality of product) and fan attendance is not a guarantee of financial success. The analysis supports the hypothesis that fan attendance is positively affected by market size and team payroll.

Both market size and team payroll effects fan attendance although the degree to which they affect it varies. Market size is important to the financial success of teams as shown by the data and as a result, Major League Baseball developed the revenue sharing program in an attempt to “level the playing field”. The data shows that payroll has a more significant effect on fan attendance than does market size although a large payroll with the most talented players is the optimum result. Ron Colangelo, VP of communications for the Florida Marlins, states “Winning obviously draws people to the ballpark.

That’s what gets everybody excited. ” (Muret, 2000) The New York Yankees and Boston Red Sox are in two of the largest markets and are ranked number 1 and 2 with the largest payroll so naturally they also draw the largest home fan attendance. They also however, draw the most attendance on the road which validates the significance of payroll. Prospective owners of Major League Baseball teams have many challenges when evaluating the future success of their team but the two most significant issues are the size of the market that their team is located in and the amount of payroll that they choose to extend.

Free Multiple Regression Analysis Fan Attendance for Major League Baseball Essay Sample

B

  • Subject:

  • University/College: University of California

  • Type of paper: Thesis/Dissertation Chapter

  • Date: 19 December 2016

  • Words:

  • Pages:

Let us write you a custom essay sample on Multiple Regression Analysis Fan Attendance for Major League Baseball

for only $16.38 $13.9/page

your testimonials