Over the past couple of weeks, we’ve been building a pretty good toolbox of stats... better yet, a utility belt of stats… like Batman uses… with which to evaluate pitchers. So far, we’ve discussed DIPS Theory, Batting Average on Balls in Play (BABIP), and Home Run per Fly ball rate (HR/FB). Today, we’re going to add another gadget to our utility belt by talking about Left On Base Percentage (LOB%).

Left On Base Percentage measures the portion of base runners that a pitcher (or subsequent relief pitchers who inherit runners, if the original pitcher leaves mid-inning) prevents from scoring. There are some slight variations to how it is calculated, but the formula that I use is as follows:


Left On Base Percentage is very important to a pitcher. It is really a measure of how many runs a pitcher allows given that there are runners on base. It is not surprising, then, that pitchers who allow a lot of base runners have worse LOB Percentages. Dave Studeman of Hardball Times put this concept quite succinctly:

The reason is simple: baserunners accumulate. If you allow only a couple of baserunners per game, chances are very good your LOB% will be 100%. However, as you allow more runners on base, chances are better that they will get on base in the same inning, making it more likely they will score. As you allow more runners on base, your LOB% will fall at an ever-faster rate. So good pitchers—who allow fewer baserunners—will have better LOB% rates.

We use Left On Base Percentage similarly to how we use BABIP and HR/FB. There is a considerable amount of luck involved, and we look for guys substantially above or below average to regress towards the mean. Like BABIP, there is also a significant amount of skill involved, as mentioned above.

Let’s run some tests to see exactly how much skill plays into LOB%. For this test, we’ll use Luck Independent ERA (LIPS ERA) as our independent variable. I know that I’ve mentioned it in passing, and I’ll be talking about it in more detail once we cover all of these other components, but for now just understand that LIPS ERA is a measure of a pitcher’s skill with neutral luck involved. Furthermore, we’ll use LOB% as our dependent variable.

Correlation Coefficient: -0.40
R2: 0.16
Adjusted R2: 0.16
P-value: 1.96E-22
Level of Significance: 1%

Essentially, what this all means is that as LIPS ERA decreases, LOB% increases. It also says that LIPS ERA can predict 16% of the movement of LOB% and that the tests are highly statistically significant.

16% might not seem like a lot, but it really is, and I’m not claiming that LOB% is entirely (or even mostly) skill driven anyway. It has a lot of luck involved, and that’s why we’re looking at it. In addition to luck, “clutch pitching,” if you will, can play a part in LOB%. If a pitcher tends to put up better (or worse) numbers when runners are on base, it will be reflected in this stat.

To further show just how important LOB% is, let’s run these same tests using LOB% as our independent variable and ERA as our dependent variable.

Correlation Coefficient: -0.76
R2: 0.56
Adjusted R2: 0.56
P-value: 1.3E-104
Level of Significance: 1%

Conclusion: As LOB% goes down, ERA goes up. 56% of ERA movement can be predicted by LOB%. It is extremely statistically significant. LOB% is very important.

So how do we use LOB% for fantasy purposes? Well, in general terms, the pitchers that are at the extremes of LOB% should be expected to regress. League average is generally around 71%, but here’s a table breaking it down by year in case you’re curious.


Check out how the 2006 LOB% leaders regressed in 2007:


As we saw last week with HR/FB rates, most guys tend to fall back into the typical, league average pattern. There are a few who did not, though. For most of them, the reason is because their skills support an above-average LOB%.

Roy Oswalt generally puts up good peripheral numbers and has had a LOB% below 76% just once in his career. Johan Santana hasn’t been below 76% since 2002 (which was also, not coincidentally, the last time his K/BB was below 3.00).

Chuck James, though, isn’t explained as easily. He has put up excellent LOB% despite LIPS ERAs of 4.72 and 4.55 in 2006 and 2007, respectively. These are the only two years we have of him, so we can’t call this a career trend as we did with Oswalt or Santana, and his peripheral numbers aren’t very good. He isn’t particularly better with runners on base either. In 2006 there was relatively no difference between his overall peripherals and those with runners on, and in 2007 he was only marginally better. I’m calling for some serious regression next year.

Curious who else you should be looking out for next year? Here are the best and worst rates of 2007:


That concludes Stat Head for this week. You guys now have some great ways of evaluating pitchers, and I’ll be explaining how to put a lot of this stuff together within the next couple of weeks. After that we’ll move onto hitters for a while.