Using TMR's Fan Cost Index to Model the Chicago Cubs Average Ticket Price

Unlike my other economic themed papers, this article was written over a number of sessions during the span of about 3 months. It is written in a stream of consciousness style, and isn't a finished paper by any stretch of the imagination. However, it uses an intermediate level of statistical analysis in a step-by-step method, which concludes with a working model.

Back to the Web Friendly FCI Model

By: Byron Clarke
Begun: April 24, 2004
Last Updated: July 5th,-2004

The Fan Cost Index is maintained by the good folks at Team Marketing Report. Since 1991, they have been ranking Major League Baseball teams based on the cost of taking a family of four (two adults and two children) to the ball park. The FCI is often used as a reference by business writers who write stories about average ticket prices etc. However, there are also many people who rightly point out that the FCI assumes a lot of things that aren't necessarily accurate.

Anyhow, this information can be found in its original form at Team Marketing Report's FCI page. I have compiled these tables by team, instead of by year as TMR has done. Since this site (thecubdom.com) is mainly interested in the Cubs business practices, I have only got the Cubs table to compare to the MLB average. Over the coming weeks, I am planning to attempt to build a least squares analysis of the components affecting ticket prices for the Cubs. My initial hypothesis will be that the major factors affecting the Cubs ticket prices will be

• The Cubs record the year before
• Cubs player salaries
• The White Sox ticket prices
• MLB Average ticket prices
• Attendance as a percentage of capacity at Wrigley Field
• Inflation
• US GDP growth

This will obviously take some time, a lot of research, and a fair amount of number crunching, but hopefully I will be able to develop a reasonable model by the end of this summer. My goal is to try and explain 90% of the ticket price fluctuations from 1991-2004. Additionally, I am hoping to eventually develop a model of the Cubs revenues from game day operations. For example, with attendance of 38,500 and an average ticket price of $28.45 the Cubs would collect $1.095 million from ticket sales. How much more would the Cubs collect in concessions and merchandise? Eventually, I would like to piece together a fairly accurate financial statement for the Cubs.

Initial Conclusions from the Cubs FCI

As discussed elsewhere, the size of Wrigley Field is an obvious reason that the Cubs are among the upper echelon of teams in ticket prices. I am interested to see that the Cubs have actually reduced prices during some years (1996 and 1998) and probably didn't actually see an increase in real dollars during 1995 and 2003. The most cynical of fans might allege that the Cubs only start winning when it appears that their losing might cause a more permanent effect in ticket prices. I don't really subscribe to that idea, but I do think that the Cubs brass (from the Tribune) might have seen the numbers from the 2003 season and finally realized that it pays to win. I would be extremely interested to see what the Cubs claimed as their profit/loss last year.

Whatever the case may be, it would be difficult to expect the Cubs will lose money this year. With ticket prices increased dramatically, and attendance through the roof early in 2004, I expect the Cubs will be seeing about $100 million in gate receipts alone. However, this may include a fair amount of taxes... lots of research to be done.

Here is the data I compiled from TMR... go check out their site, it is fascinating.

The Cubs FCI (1991 — 2004)

See the Full Table

MLB Average FCI (1991-2004)

See the Full Table

* — In 2001, TMR did not report % changes in ticket prices or FCI. I calculated the numbers, but I suspect that TMR may have redefined their method of calculating average ticket price (and thus FCI) in 2001.

† — TMR does not note the Team's Won-Loss Record, but I feel that this is an important factor to see alongside ticket price changes.

° — In 1994, a labor dispute caused the season to end August 12. The strike and subsequent lockout caused most MLB teams to play about 18 fewer games in 1995.

‡ — In 1998, the Cubs played 163 regular season games. They played a single playoff game against the San Francisco Giants to determine the National League Wild Card. The Cubs won, and played three games against the Atlanta Braves. In 2003, the Cubs won the NL Central Division. They won a five game NL Division Series against the Atlanta Braves. The Cubs then lost in seven games during the NL Championship Series to the Florida Marlins. Playoff games are not included in the Cub's records.

CPI data from: Bureau of Labor Statistics CPI Data.

GDP Data from: Commerce Department Bureau of Economic Analysis. Download the spreadsheet of GDP data.

Cubs Payroll information used from USA Today's Baseball Salary Database.

Cubs Attendance information used from Cubs Year by Year Results.

Because the Cubs (and all other major league teams) set their ticket prices at the end of the year for which they take effect, I have adjusted the data in my calculations by setting ticket dates back one year.

For example: my model of Chicago Cubs 2004 ticket prices is based off of the following factors:

• 2003 Chicago Cubs winning percentage
• 2004 Cubs Payroll
• 2004 White Sox Ticket Prices
• 2004 Avg. Major League Ticket Prices
• 2003 Chicago Cubs Attendance
• 2003 Consumer Price Index Level
• 2003 US GDP Levels

The first step in building my model has been to find the correlation between Cubs ticket prices and each individual variable.

Perhaps the most interesting number here is also the most obvious number for Cubs fans. The Cubs ticket prices have very little to do with whether the Cubs win or not.

The interpretation of the above table is this: "coefficient of determination" percent of changes in Cubs ticket prices are accounted for by changes in the independent variable. Thus, we would say that the 95.36% of the change in Cubs ticket price over the period from 1991-2004 can be accounted for by examining changes in the Cubs Payroll. From a business standpoint, this seems logical as ticket revenues are the Cubs most significant form of revenue, and Cubs payroll is the most significant expense.

Initial Model

Using Microsoft Excel, I have constructed a multiple regression analysis using Cubs ticket prices from 1991-2004 as the dependent variable, and the above eight variables as the independent variables. I am presenting this work as an initial model now, but will refine it over time.

The model is this:

Cubs ticket price = -7.199 + (11.095 * Cubs win %) + (8.538E-08 * Cubs Payroll) + (0.552 * White Sox Tickets) + (.538 * MLB Avg Ticket Price) + (-1.221E-06 * Avg. Attendance) + (-0.004 * CPI) + (-0.0004 * GDP) + (0.0001764 * total attendance)

Using this model, which has a (coefficient of determination of 99.2%) I have calculated the Cubs projected ticket price for each of the previous 14 years. I have also listed the actual ticket price, and the deviation from the model.

Obviously, there are some glitches in this model because there are negative components (CPI, GDP, and average attendance). One of the causes, I believe is that when performing a multiple regression analysis the independent variables are assumed to be infact independent. Well, the MLB average ticket price is actually partially dependent on the Cubs, and the White Sox, so I will eliminate it in my next attempt. I also used Cubs attendance in total, and average Cubs attendance per game. I was attempting to account for the strike shortened years, but having both seems to be degrading the quality of my model. As a result, I will eliminate the average attendance per game because it has a lower coefficient of determination. Finally, because the coefficient of determination is only 1.4% for the Cubs winning percent, I will eliminate this variable.

Trial #2:

I will run a second multiple regression analysis to determine Cubs ticket prices (dependent variable) using the Cubs Payroll, White Sox average ticket price, Total Home Attendance, CPI, and GDP as the independent variables.

Copyright ©2004 - 2008 Byron Clarke
byron@thecubdom.com - legal - about thecubdom.com - site index