Tango on the 1992-94 home run explosion

There was a large increase in major-league baseball hitting in 1993 and 1994, one that continues today. In 1992, there were 0.721 home runs per game. In 1994, there were 1.033 home runs per game. It wasn't a one-time increase: the 1994 rate has pretty much stayed with us to the present day.

What happened? There are various theories. One says that the 1993 expansion brought in a bunch of inferior pitchers, and the dilution of talent caused the numbers to jump. Another theory says that it's the ballparks – Coors Field entered the National League in 1993. A third theory says it's the ball: it was juiced up around that time, and remains juiced today.

In a post about a year ago, I argued that expansion couldn't have caused an effect as big as the one we saw. With reasonable assumptions, you can show that expanding by two teams should cause home runs to increase by only 3%. And you could also do the same for ballparks – even with Coors Field now in the equation, and even combining that with the 3% for expansion, there's still no way you can explain the 40% increase in home runs.

But for those who don't follow that logic, Tom Tango has an excellent study that should now win over the unconvinced.

Tango looked at the 1993 season, and compared it to 1992. But he stripped 1993 down, considering only players who played in 1992, in parks that were in existence in 1992. And he adjusted all the players' stats to give them equal playing time in 1992 and 1993.

The results: even among the incumbent players and parks, there was an 18% increase in home runs.

Repeating the study for 1993/1994, Tango found a second increase, this time of 20%.

Over two years, even without the effects of expansion, and the effects of new parks, there was a 42% jump in home runs.

So it can't be the parks. And it can't be expansion.

I don't think this finding is a big surprise, but it's so thorough, and so understandable, that even non-sabermetric fans should be convinced. You'd hope.

Anyway, if it wasn't the parks or expansion, was it the ball? Tango presents convincing evidence to say it was.

According to Dr. James Sherwood, MLB's ball tester, minor-league balls travel 391.8 feet under the same conditions that major-league balls travel 400.5 feet, for a difference of 8.7 feet. And, according to Greg Rybarcyzk of HitTracker Online, if you eliminated all home runs in 2006 that cleared the wall by less than 8.7 feet … you'd have roughly the same home run rate as before the jump.

I think Tango has found the answer.

JQAS study on the effects of MLB expansion and relocation

Here's a study from JQAS called "Growing and Moving the Game: Effects of MLB Expansion and Tem Relocation 1950-2004." It's by Kevin G. Quinn and Paul B. Bursik.

Quinn and Bursik start by running straightforward graphs of MLB trends from 1950 to 2004. These are as expected. Attendance rises, run scoring drops then rises again, fielding percentage improves, and so on. (The graph of park factor (bpf) is fairly flat, as you would expect; the authors seem unaware that bpf is relative to other teams in their era, and should stay roughly around 100 for all timeframes.) Competitive balance is the most interesting; it's highest in the early 1950s and lowest in the late 1950s. It then goes higher in the early 1960s, and declines irregularly until 2000, rising slightly after that.

The authors then run regressions to predict attendance changes based on these factors. They use time series analysis, which (I think) includes prior year attendance trends in the regression. This automatically corrects for long-term trends, if I remember the Time Series course I took so long ago.

Again most of the results are what you would have guessed: the higher the change in population in MLB cities between one year and the next, the bigger the corresponding jump in attendance. In the year following a strike, attendance falls (relative to the trend). And so on.

There are two results that surprised me. In expansion years, attendance drops among existing teams to a statistically significant degree – about 1000 per game, when adding two teams. (Looking at their graph (Figure 5), there was a big drop in 1962, but none of the other expansion years show large effects.) Also, one team relocating cities leads to a drop of about 600.

The authors hypothesize that fans are not as attracted to games featuring expansion teams, which is why attendance drops; or that the temporary changes in competitive balance reduce fan interest. Also, they suggest that perhaps relocations reduce natural rivalries (Dodgers and Giants, say), and attendance drops for that reason.

Another regression predicts compeitive balance (with a given season) based on some of these variables. Not surprisingly, expansion reduces balance. But new stadiums decrease balance to a statistically significant extent, and I don't know why that would be.

They also try to predict runs per game, and there is no surprise there: the only significant variables are DH and an indicator variable for 1969. Fielding percentage is reduced by expansion, but also (at the 10% level) by bpf; the bpf finding is probably random noise. Also, if there is a jump in the number teams that use the DH, more errors are committed. This is probably related to expansion in some way.

My overall feeling is that this study breaks no new ground, but does find some unexpected effects. I don't understand time series enough, or AR(1) or MA(1) models, to know if these effects are artifacts of the method, and I wish the authors had looked into some of them a bit deeper, or using different statistical techniques.