On Friday, Lee aggregated various projections for Tiger players to find the average projection. On Saturday, David Pinto web enabled a script written by Ken Arneson based on work by Cyril Morong that optimizes lineups. On Sunday, I do the easiest part of all and stick Lee’s numbers into David’s tool.
First some lineups, and then some explanation. I first put in what would probably be the most common assortment of players the Tigers would use. I’m guessing this would be Rodriguez/Inge/Guillen/Polanco/Shelton/Monroe/Granderson/Ordonez/Young. Various combinations of those players would average 5.330 runs per game. Here are the best and worst variations on that lineup
Both of those look pretty screwy, but still are pretty high powered. One thing that you may notice is that the #3 hitter is the same in the best and worst lineups. This goes against the conventional wisdom that the best hitter hits third. If this were the case, you’d think the #3 hitter would be significant, but that doesn’t appear to be the case. In fact, Dan Scotto has been experiementing with these models quite extensively and found some interesting trends. The high OBP players get put at 1, 2, and 9 with 9 being kind of like a second lead off hitter. The clean-up spot goes to the biggest slugger and the number 8 spot goes to the worst hitter.
In case you were wondering, I put together a more conventional lineup that balances left/right handed batters, takes into account old school paradigms (centerfielder=leadoff), and balances egos. The lineup of Granderson/Polanco/Guillen/Ordonez/Shelton/Young/Pudge/Monroe/Inge has an expected run value of 5.384 per game
Now because there are some position battles and platoon options I tried a couple variations. First I substituted Nook Logan for Curtis Granderson. That lineup averaged 5.117 runs per game with the best and worst cases being 5.269 and 4.966 respectively. You can see the results of the various permutations here. Now the model doesn’t take stolen bases into account, so Nook’s ability to “make things happen” isn’t accounted for in the model.
Finally, I ran one more version. This one had Granderson in center and Dmitri Young at third base (with Pena DH’ing). That lineup averaged 5.443 runs per game with 5.549 and 5.348 at the extremes.
First, and not surprisingly, it appears that the components of the lineup are just as important as the order. Subsituting a weak hitter for a strong hitter seemed to produce a shift of about .2 runs. The difference between an optimized lineup, and an unoptimized lineup is about .2 to .3 runs.
Second, lineup optimization would only probably gain a team (at least this Tiger team) no more than two wins a season. With a swing of only .25 from best to worst lineups, and assuming that Jim Leyland doesn’t march the worst possible line up out there the difference is probably much smaller. If one assumes an improvement of .1 runs a game, thats only 16 runs over the course of the season.
Third, it is too bad that we will never see these lineups as experiments. I can’t imagine many managers who would bat Polanco 9th more than once. On a related note, having a set lineup is such a rarity between platoons, injuries, and off days I don’t know how much you’d be able to tell.
Fourth, the baseball blog-o-sphere is wonderful. All these other people do substantial work, so I can just plug and play.
Go ahead and play around with the line-up optimizer and let me know what you find. See how many more runs the Tigers could have theoretically scored in 1984. Or what would be the optimal all time Tiger lineup. It’s fun stuff.