Joe Clarke

11/5/03

ECO-043

Yankees

Introduction:

Baseball, the game is known as the American pastime. It is a game of skill, cooperation as well as luck. What is it that makes one team sell out their stadium while another barely sells enough tickets to make a profit? The answer is quite simple; no fan wants to go watch losers. It’s a teams winning percentage and other statistics that earn them respect. In this case no other team earns more respect than the New York Yankees. Since joining the American League in 1903, the Yankees have been a dominant force in baseball. Over that time they have won 38 pennants and 26 world championships, more than any other team in baseball. Like any team however, they have suffered through hard times but their life long winning percentage remains something to envy.

Model:

The theory behind my model as I have said earlier is quite simple and direct. Fans want to go see a team that wins. That means that all owners and players care about is winning. The more they win the more tickets they will sell and the more money they will make. More money means they can buy better players or pay current player more for playing well (which is an incentive to play better) and there fore win more games and so on and so on. So the key variable to my economic model is obviously the teams winning percentage. However there are many other variables that affect this winning percentage and thus will affect attendance. I have chosen a few of the main statistics in baseball as the variables that most affect winning percentage. These variables are the team batting average, team slugging percent, ERA and runs scored.

Data:

The affect the variables I have chosen have on winning percentage and thus attendance is quite straight forward but I will explain each variable for those that are not familiar with baseball. Batting average is just what it sounds like it is the number of hits divided by the total number of at bats. The more hits a team records the more likely they are to score and there fore win. Next is slugging average, this is the average number of bases gained for each hit. It is calculated by the formula [Number of (Singles + [2 x Doubles] +[ 3 x Triples] + [4 x Home Runs]) divided by At Bats]. So the higher this average is the more bases a team gains per hit, which has a large affect on winning percentage. ERA is a defensive statistic and means earned runs allowed, which is the number of runs you allow to the other team. As you might guess this stat has a negative relationship to winning percentage. So the lower this stat is the better chance a team has of winning. Last we have runs, this is the number of runs a team earns. So of course the higher this stat the more likely a team is to win. All of the information and numbers I gathered on these statistics were taken from the baseball almanac at www.baseball-almanac.com.

Results:

After running putting all of my parameters into the E-views program I ran a regression with attendance as my dependent variable and the rest as the independent variables affecting attendance. My results were for the most part not surprising, they followed what I expected from above. However I did find how much some variables affected attendance surprising. Winning percentage had a coefficient of 55929 and a std. error of 29144. Showing the winning percentage has a fairly large affect upon attendance. Batting average was the surprise in the data since it turned up a negative relationship with attendance. This I attribute the slugging percentage being in the regression as well. Since you much rather get more bases off of a low batting average than very little bases off a lot of hits. Slugging percentage had a coefficient of 184331 and a std. error of 67976. Showing the slugging percentage had the greatest affect out of all the variables. Runs had a coefficient of 7.9 and a std. error of 12.2 showing runs has a little affect and could even have none. ERA was also a little surprising showing a coefficient of 4241 and a std. error 3003. I am not sure why this turned out at a positive variable but my best guess is that if a team is scoring runs on you then as a team you have to step up and score more yourself and thus win the game. But for the most part my variables turned out how I expected.

Conclusions:

In conclusion there are many variables that affect a team’s ability to win. The variables I have tested are just a few but they get the main ideas behind baseball across. Although many people look at baseball as a sport, professional baseball is simply another form of entertainment. Like most other forms of entertainment it is driven by money. You can look at it from either direction but still always come back to money. You can say that the better their slugging percent the more that they will win and thus the more fans they will attract and the more money that team will make. However you can reverse that and say the same thing. The more money a team has the better players they can buy there fore they will have a better slugging percent, they will win more game, they will have more fans, they will sell more tickets and they will make more money. So no matter how you look at baseball it is a form of entertainment that like most other forms is driven by money.