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May 20, 2008

Prospectus Toolbox

Still Stranded

by Derek Jacques

I was ready to move on, but last week's column generated a lot of comment, so we're sticking with baserunners left on base for today's column. Now, last week we looked at the correlation between leaving runners on base—the Team LOB statistic—and run scoring, by looking at team totals of those stats going back to 1971. I kept the conversation limited to raw totals of runners left on base, times on base, and runs scored for two reasons: first, because that was the question that had been asked, and second, because raw totals are the way the left on base stat is most often used and discussed. Once the strike-shortened seasons of 1981, 1994, and 1995 were omitted (although I failed to take the first strike year, 1972, out of the sample) the teams were on more or less equal footing in terms of opportunities to put men on base, score runs, or strand them.

As several readers noted, using raw counting stats left a number of questions unanswered. For example, reader S.B. pointed out:

The better stat to look at is probably Percentage of Baserunners who are Stranded (or a very-pleasing acronym POBWAS). This is analogous to the RBI/RBI opportunity stat for an individual batter being a better indicator than total RBI.

Statheads often favor rate statistics to counting stats, because rate statistics provide us with valuable context—usually, by contrasting a counting stat against opportunities. Reader M.P. took things a bit further than S.B. did, crunching some numbers while using the stats I provided in last week's column:

It seems to me that the key stay for LOB would actually be the percentage of runners left on base, a sort of offensive strand rate, OSR perhaps? Just using the data from 2007 that you presented, the coefficient of correlation between runs scored and OSR would be -.62, which shows a pretty strong negative correlation between OSR and runs scored. That would explain the Tigers outscoring the Nationals despite the Nationals stranding fewer runners. The Nationals stranded over 58 percent of their runners while Detroit stranded just under 53 percent. It would be interesting to see if home runs are a factor. I would think Detroit hit a good number more homers than Washington, making their offense much more efficient.

OSR also explains Oakland's high LOB/low runs situation. No one stranded runners at a higher rate than Oakland in 2007, leaving nearly 59 percent of their runners high and dry.

OSR would explain why it is so frustrating to watch a team strand runners sometimes. Red Sox and Yankees fans do not get to end of the season feeling like their teams left too many players on base because, even though they left more runners on base than 25 other teams, they were both in the top half in percentage of runners brought home (the Yankees were second in fact).

It would also be interesting to see how GIDP fits into this equation. If we counted GIDPs as LOBs as well (since they sort of are), then wouldn't the numbers change? Maybe the correlation would increase and some of the anomalies would even out? Something to think about...

The rate stat described by both S.B. and M.P., the ratio of runners left on base to times reached base safely or LOB/TOB, would seem to be a pretty good (albeit inverse) measure of a team's offensive efficiency, and a negative correlation between that stat and run-scoring would undercut the conclusion of last week's study, that a high number of LOB aren't necessarily bad for your offense. M.P.'s point about Detroit's home runs makes some intuitive sense, and is bolstered by the fact that the Yankees, another power-hitting ballclub, featured a similarly low LOB/TOB ratio. However, the most efficient offense last year, by this measure, that of the Los Anaheim Angels of Angeles, had the exact same number of homers (123) as the Washington Nationals, who had the second-highest LOB/TOB. We'll shelve further investigation of that theory, for the moment.

M.P.'s other point, about the how much double plays might throw off the LOB/TOB ratio, was interesting, but when I followed up on it, it seemed incomplete. If double plays should be added to LOB, why not triple plays? That's easy enough, but then there were other questions ("Why not caught stealing? Why not pickoffs?") which were a bit of a headache. So, with the assistance of William Burke, I took a look at another statistic, Team OBI percentage (OBI%), that includes double plays and takes the batter scoring on a home run out of the equation.