How are wins, attendance and payroll all related?
“…there are rich teams and there are poor teams. Then there’s fifty feet of crap. And then there’s us.” — Moneyball (2011)
The release of Moneyball helped bring baseball economics into the mainstream. Obviously, given the subject matter, a lot of the attention has been centered on the plight of the small-market team, and how small-market general managers need to be smarter to survive. A common refrain I hear is that small-market teams are often pulled into a death spiral where payroll, attendance, and the quality of the team drag each other down, sinking the team into the gutter with no easy way out. And it intuitively makes sense. But is it really that simple? How strong are the links between those three variables?
Thankfully, testing the strength of the links is fairly easy. I created a data set comprised of all MLB teams between 2000-2011, consisting of team payroll at the beginning of the season (via USA Today), total attendance per game figures (via Baseball-Reference), and winning percentage. Sure, it seems intuitive that all three of the possible pair combinations between payroll, attendance, and wins would have noticeable correlations. More money should buy more wins, wins should go hand-in-hand with more people in seats, and attendance should mean more revenue dollars for the front office to play with. But instead of relying on conjecture, why not actually test it?
Before I continue, I need to touch on a very important point. Correlation does not necessarily imply causation. Two variables may be correlated, but the existence of a correlation does not mean that one of the variables caused the other. The percentage of US households with a television over the last 50 years correlates with the price of a gallon of milk, as both have increased over time, but the correlation certainly doesn’t mean that the price of milk caused more US families to purchase TVs. Correlation can certainly point in the direction of causation, but proving causation is a rather tricky proposition that requires research in a controlled environment. So think of this as a loose suggestion, rather than anything that’s set in stone.
Now, onto business. What conclusions can we draw?
By far, the biggest correlation is between payroll and attendance.
| Variable Pair | R2 |
|---|---|
| Payroll/Wins | 0.16 |
| Attendance/Wins | 0.27 |
| Payroll/Attendance | 0.54 |
The R2 between payroll and attendance is 0.54, which is a fancy, statistical way of saying that 54 percent of the variation in payroll can be attributed to changes in attendance. The R2 figures for payroll/wins and attendance/wins are far lower, indicating a lesser degree of correlation. It makes sense that the two other pairs should be related, but the links between those pairs don’t seem to be quite as strong as payroll/attendance.
But is it possible to shed a little more light on the correlation? Sure, A and B share a correlation, but does A influence B more than B influences A? It’s easy enough to test by looking at correlations between a set of variables and another set of variables from the previous year.
Again, before delving into this, I have to give a similar warning as above. Another common logical fallacy is to assume that if an event happened after a previous event, the first caused the second. After writing this article, I made myself a sandwich, but typing about baseball didn’t cause me to get hungry. An event that follows another can certainly be the caused by the first event, but it’s not necessarily true. So again, nothing here is set in stone as an emphatic “this is how it is” conclusion.
Attendance follows wins, not the other way around.
| Variable Pair | R2 |
|---|---|
| Attendance/Wins | 0.27 |
| Attendance/Last Year’s Wins | 0.30 |
| Wins/Last Year’s Attendance | 0.13 |
If we compare attendance with the previous year’s wins, the R2 jumps up a little from the same-year correlation. But when reversed, when wins are compared to last year’s attendance, the R2 falls to 0.13. This seems to suggest that a fanbase shows up in larger numbers if the team is doing well, but the reverse effect of a team doing well because of a large fan base (more revenue from ticket sales) doesn’t generally exist.
Payrolls expand after a team does well more often than the reverse.
| Variable Pair | R2 |
|---|---|
| Payroll/Wins | 0.16 |
| Payroll/Last Year’s Wins | 0.25 |
| Wins/Last Year’s Payroll | 0.12 |
Again, we see an R2 change as these variables are moved around in time. This indicates that teams generally expand payroll to push a talented team over the edge, instead of using payroll to give a bad team a talent spike. Nothing surprising here, but it’s nice to have it in black and white numbers.
Payroll and attendance are far “stickier” than wins.
| Variable Pair | R2 |
|---|---|
| Payroll/Last Year’s Payroll | 0.83 |
| Attendance/Last Year’s Attendance | 0.80 |
| Wins/Last Year’s Wins | 0.31 |
For this set, I ran a correlation analysis between each variable and it’s value in the previous year. (To borrow a term from economics, a variable is called “sticky” when it isn’t very susceptible to change over time.) The year-to-year correlations between payroll and attendance are extremely high, whereas wins are much more volatile.
So what does it all mean, as far as small-market teams? Having a healthy fan base and a strong payroll is extremely important for the health of a franchise. Wins are volatile, but payroll and attendance will stick around for a while. Of course, the problem is that wins lead to payroll and attendance, so there seems to be truth in the death spiral idea after all. It’s also interesting to note that the correlation between payroll and wins isn’t nearly as strong as one might expect. An R2 of only 0.16 is absolutely tiny, indicating a relationship that is far from ironclad. (That’s your cue to gloat or sulk, Rays and Cubs fans.)
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This is a great start and I have long wondered about it. My feeling is that if they build it we will come. That is, people will pay to see a good team, regardless of payroll. I have been frustrated that my favorite team, the White Sox, have seemed to have an attitude that they can only build a good team if people buy tickets and by extension that the current rebuilding is due to poor attendance over the last one or two years and not the failure of high priced talent such as Dunn, Peavy, Rios and Pierre. That excuse covers up their inability to acquire and develop cheap talent through the draft and MiLB.
I think that even beyond correlation not equaling causation it becomes difficult to tell which direction causation may work. Does spending money make you better or do you spend money because you have better players? I would love a more in depth analysis if possible.
Interesting analysis, Dan. Like MikeS, I’d be interested to see you take it further.
You have started to analyze a subject where 30 MLB owners should be interested in what your summary will suggest!! I have often wondered if the presence of key/core players for 10-15 years has a positive impact on attendance. Teams like Florida would make a WS run (twice) without great attendance and then trade away the keys faces of the franchise and attendance rates did not improve. The fringe fans can become attached to the Chippers, Jeters, Gwynns and Ripkens of their local teams and drop by to watch them whereas a fringe fan may not know (or care) that Mike Stanton is a budding star in the making. They do not have a favourite so they won’t buy tickets.
Just an angle…
Love the anlaysis. We need more of this kind of writing.
You drew the conclusion that “Having a healthy fan base and a strong payroll is extremely important for the health of a franchise.” I don’t disagree, but the analysis in this article was univariate. How does the R2 of these independent variables change when your analysis is multivariate? Is it stronger or weaker? I.E do Payroll and Wins combined explain more of the variance in attendance, than just Payroll or Wins alone?
The one thing I have a hard time believing is that “payroll” is the true variable here. I agree its relevant, but it looks like you’re using it as a proxy for some other things that drive attendance.
What I mean is, do people really decide “I’m going to a Mariner’s game because Felix Hernandez has a $78M contract? “ I’d be more likely to say, “I’m going to a Mariner’s game because I really want to see Felix pitch against Albert Pujols, and I want to watch Ichiro do his thing at the plate.” My point is, I’m wondering if maybe we could get closer to what we mean if we break down “payroll” further. I believe things like “star power” and “player performance” really drive attendance not payroll.
Granted, there’s probably a strong correlation between payroll and star power, since stars cost more, but if you want to talk causation, it’s the player, not the player’s salary that drives attendance.
I’m sure the relationship between player performance, wins, and attendance is a dead horse, but why not beat it again? We watched Michael Pineda rise as a star rookie pitcher last year. His performance may (or may not) have contributed to wins, but….did his really strong individual performances contribute to attendance?…regardless of whether the team won? Point is, how much of attendance can be explained by “stars,” either those that are established (like a Felix or Albert), or those who are “on the rise” or “hot” (like Pineda), that fans are excited about. I’d be more interested in these, rather than payroll.
I assume you’re taking inflation into account, since overall payrolls are going up, but the total wins of MLB will stay even. How about taking new stadium effect out of the attendance? What about looking at the relative rank of payroll vs other teams? Just some thoughts. Amazing how your data shows how difficult it is to spend your way to the top. Great article, but like some of the other commenters, this just leaves me wanting more!
While I’m sure the team on the field is a major influence on attendance, I’d be curious to see how other factors rate. There are the obvious ones like ticket and concession prices, but parking, promotions, corporate involvement, the general area and accompanying infrastructure (other local attractions, accommodations, dining, access, etc.), and atmosphere of the park (typically viewed as family friendly or a good place to pick up some meth and hookers, e.g.) can also factor in to a decision. I also wonder if the local media (quantity/quality of newspaper, radio, and tv coverage) has any bearing, though that’s much harder to quantify.
What happens to the ratios if you eliminate outliers like the Cubs, Red Sox and/or Rays, where attendance is known to be inelastic?
Great stuff. More please.