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Optimizing Yesterday’s Lineups

Lineup optimization — ordering batters to create a lineup that produces the most runs — is a topic that receives a great deal of attention relative to its importance (and this article will only make the ratio worse). The fact is most sensible lineups (not batting the pitcher first or putting Alex Rodriguez 8th) will produce nearly the same amount of runs. Still, with the ever-expanding search to find any slim advantage it is something to think about. Sabermetric studies of lineup optimization have produced some interesting results; Sky Kalkman neatly reviews The Book‘s findings on the topic. Compared to the old-school lineup dogma, more weight is given to the second and fifth spots, while less to the third spot. In addition, the Book suggests that batting the pitcher 8th is a good idea.

Baseball Musings has a lineup optimizer tool, which gives the optimal lineup based on each players’s projected OBP and SLG (this ignores speed and handedness, which are also important). Out of curiosity I wanted to see how each of yesterday’s lineups compared with the best one predicted by this tool. I used the CHONE projections and the tool spit out the estimated runs per game for the given lineup and the optimal lineup. I gave all pitchers the average OBP, 0.176, and SLG, 0.179, that NL pitchers had in 2009:

Team      Actual      Best      Dif
TEX       5.017       5.033    -0.016
MIN       5.257       5.308    -0.051
OAK       4.519       4.571    -0.052
CLE       5.019       5.081    -0.062
KCA       4.379       4.446    -0.067
PIT       4.552       4.628    -0.076 *
DET       4.698       4.776    -0.078
TOR       4.676       4.763    -0.087
CHA       4.759       4.858    -0.099
SEA       4.478       4.578    -0.100
LAA       4.891       5.016    -0.125
HOU       3.967       4.142    -0.175
COL       5.064       5.258    -0.194
ATL       4.898       5.106    -0.208
LAN       4.773       4.982    -0.209
ARI       4.704       4.916    -0.212
FLO       4.813       5.035    -0.222
SFN       4.294       4.522    -0.228
PHI       4.873       5.102    -0.229
WAS       4.410       4.644    -0.234
CIN       4.608       4.846    -0.238
CHN       4.660       4.899    -0.239
MIL       4.629       4.876    -0.247
SDN       4.176       4.431    -0.255
NYN       4.381       4.645    -0.264
STL       4.843       5.116    -0.273

* pitcher batted 8th

First off, notice that the worst-optimized lineups were all NL teams that had the pitcher bat 9th. The one NL team that had the pitcher bat 8th, Pittsburgh, fell out in the middle of the AL teams. So it looks like, given a reasonably constructed lineup (as these are), having the pitcher bat 9th results in a pretty big drop. The average pitcher-bats-9th team was 0.23 runs below optimal, while Pittsburgh and the AL teams averaged 0.07 runs below optimal. This would suggest flipping the pitcher and 8th hitter on the other NL teams would result in an improvement of about 0.16 runs. Over 162 games that is 25 runs or 2.5 wins, a surprisingly high number to me.Edit: It looks like the method I took is not correct and this conclusion is false. See the comments and this post by Tango. I apologize.

St. Louis had the worst-optimized lineup. The big problem for them, in addition to having Chris Carpenter batting 9th, was Albert Pujols batting 3rd. As noted above, the studies of lineup optimization shows that the 2nd, 4th and 5th spots should all have better hitters than the third, so having the game’s best hitter bat third really hurts.

I think Texas is the closest to their optimized lineup because they have so many similar hitters. Josh Hamilton, Vladimir Guerrero, Nelson Cruz and Chris Davis all project to have about average OBP (0.320 to 0.340) and good SLG (0.467 to 0.508). Once you throw Julio Borbon in the leadoff spot and Andres BlancoElvis Andrus eight-nine there is little variation in runs scored based on the ordering of the middle guys.

Two other quick notes: with Boston, Tampa Bay and the Yankees all off for the night CHONE saw the Twins’ lineup as the best, and Houston’s lineup was expected to score under four runs against the average pitcher, but they had to face one of the best.