With baseball back in season, I started to think of my team (the Red Sox) and their closer situation. They are transitioning to a new closer which made me wonder how they came to this decision. To get an idea of what makes a good closer I did some research on closer statistics. Ultimately, your ability as a closer comes down to how many save opportunities are converted. So, I analyzed save percentage (saves/save opportunities) as a function of various independent variables with the following results:
Table 1
Variable |
Probability |
R-squared |
BAA |
0.0311 |
0.137126 |
BABIP |
0.7301 |
0.003770 |
BB/9 |
0.4358 |
0.019089 |
ERA |
0.0001 |
0.285438 |
K/9 |
0.2874 |
0.035279 |
K/BB |
0.0976 |
0.083421 |
OBP |
0.0155 |
0.159534 |
OPS |
0.0005 |
0.315516 |
SLG |
0.0017 |
0.268218 |
WHIP |
0.0174 |
0.164343 |
Interpreting this information first requires an explanation of the table. Probability can be described as the likelihood that a statistic is significant. Generally, you want to see a number less than 0.05. R-squared can be roughly described as what percentage of the total outcome can be attributed to the independent variable. R-squared has a range of 0.0 to 1.0. For example, OBP has a probability of 0.0155 which means OBP is significant and has an R-squared value of 0.159534 which means that OBP accounts for 15.95% of total variability in save percentage. Below, I removed all insignificant variables and ordered them in order of R-squared values.
Table 2
Variable |
Probability |
R-squared |
OPS |
0.0005 |
0.315516 |
ERA |
0.0001 |
0.285438 |
SLG |
0.0017 |
0.268218 |
WHIP |
0.0174 |
0.164343 |
OBP |
0.0155 |
0.159534 |
BAA |
0.0311 |
0.137126 |
There are a couple of interesting takeaways from this information. The first takeaway is to recognize what stats are missing. K/9 appears to have no significance in converting saves. This is kind of a strange outcome because closers are generally thought of as big strikeout guys. BB/9 and K/BB are also missing. This is a little surprising because, even though closers aren’t necessarily control guys, you would expect a closer’s results to be somewhat dependent on these two variables. The final missing stat is BABIP (batting average on balls in play). This is something that is starting to be talked about more in the baseball world, but apparently has little effect on save percentage.
The next takeaway is the relative importance of each variable. According to my research, OPS is the most significant stat with respect to save percentage. This is somewhat surprising because I don’t think I’ve ever heard this stat with respect to pitchers. However, after absorbing this information for a minute, it should not be that surprising. OPS has grown in popularity over recent years as far as measuring a hitters performance. So, it would stand to reason that you could measure a pitcher’s value based on the OPS that hitters have against him. The next most important variable is an old-time statistic, ERA. As it turns out, the old guard in baseball are bigger stat geeks than they mare care to admit. But, again, this makes sense because if ERA didn’t matter than it wouldn’t have been such a popular stat for so long. One stat that I was surprised by is WHIP. This is my favorite new pitcher stat because I thought it encompassed most of the areas that ERA fell short on. As it turns out, WHIP is the 4th most significant stat that I analyzed which is far less important than I would have anticipated.
So, now that we have all this information we should apply some of it. First, let’s look at the closers who might be over their heads in their 2011 roles. Here are the highest OPS values for closers with more than 10 saves:
Name OPS
Jon Rauch 0.799
Houston Street 0.781
Kevin Gregg 0.773
Matt Capps 0.726
Frank Francisco 0.721
Joakim Soria 0.709
Of these six, Frank Francisco is the only one with a save so far this year and the only clear-cut closer. However, Francisco changed teams and leagues and also signed a very reasonable $5.5 million contract, all of which may contribute to him continuing as a closer. To be fair, Soria is out for the season with an elbow injury (perhaps his uncharacteristically poor 2011 could have been an indication of the arm injury), otherwise he’d be closing for the Royals. The other 4 are either setup guys or in a situation where it’s not completely clear. So, for the most part, the empirical evidence supports the theoretical research.
That’s it for my analysis this time around, but I intend to do some research on multi-variable analysis in the near future.
-Erik Clark