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March 30, 2014 / Nat Anacostia

Lineup optimizer? Another look at the Nats’ lineup

Since my last post with my thoughts on the Nats’ lineup, I ran across a site, Baseball Musings, that has a lineup optimizer.  If you type in your assumptions for each player’s on-base and slugging percentages, it tells you how man runs per game to expect from the lineup you’ve entered, and also spits out the best lineups (roughly 25 of them) and the worst lineups.

Using the same assumptions as in my last post (the projections from FanGraphs with a 9.8% platoon factor for the left-handers and a 6.1% platoon factor for the right-handers; for pitchers, I used the Nationals’ pitcher batting statistics from last season), here are the “optimum” lineups. Actually, the website gives two sets of lineups, based on two different periods on which their model was estimated. This first set of lineups is based on data from 1989-2002:

vs. RHP (4.627 R/G)

1. Jayson Werth

2. Bryce Harper

3. Anthony Rendon

4. Ryan Zimmerman

5. Adam LaRoche

6. Wilson Ramos

7. Ian Desmond

8. Pitcher

9. Denard Span

vs. LHP (4.665 R/G)

1. Werth

2. Zimmerman

3. Rendon

4. Harper

5. Ramos

6. LaRoche

7. Desmond

8. Pitcher

9. Span

In contrast, the optimizer said that the lineups I proposed in my last post were worth only 4.418 R/G vs RHP and 4.464 R/G vs. LHP. Now the analysis says that the lineup that Matt Williams seems inclined to go with (1. Span, 2. Rendon, 3. Werth, 4. Zimmerman, 5. Harper, 6. Desmond, 7. LaRoche, 8. Ramos, 9. Pitcher) does even worse, 4.413 R/G vs. RHP and 4.396 R/G vs. LHP.

However, when we run the same assumptions through their other sample period, 1959–2004, we get quite different results:

vs. RHP (4.525 R/G)

1. Werth

2. Harper

3. Ramos

4. Zimmerman

5. LaRoche

6. Rendon

7. Span

8. Desmond

9. Pitcher

vs. LHP (4.563 R/G)

1. Werth

2. Zimmerman

3. Ramos

4. Rendon !

5. Harper

6. LaRoche

7. Span

8. Desmond

9. Pitcher

Rendon as cleanup hitter certainly was a surprise! Also, the optimizer doesn’t ask for handedness, so it doesn’t know that it lined up the Nats’ three left-handed hitters in a row. Looking over some of the other high-ranked lineups, this alternative is estimated to result in only .004 fewer R/G and avoids having the lefties all in a row: 1. Werth, 2. Zimmerman, 3. Desmond, 4. Harper, 5. Ramos, 6. Span, 7. Rendon, 8. LaRoche, 9. Pitcher.

Against these alternatives, my suggestions from the last post are worse, but not by nearly as large a margin (4.491 R/G vs. RHP and 4.517 R/G vs. LHP). The “Matt Williams” lineup is also only a little worse (4.477 R/G vs. RHP and 4.494 R/G vs. LHP). So the results from the longer time span seem to support the idea that lineups don’t make that much difference, whereas from the shorter time span, it seems to make quite a lot of difference.

Do I believe the Baseball Musings model? Actually, I’ve got some problems with their methodology. They base their model on linear regression analysis based on a model with two explanatory variables, OBP and SLG. The most common problem with regression models is that when there are additional variables that affect the dependent variable (in this case, runs per game), and they are left out of the model, the estimated coefficients of the variables that are included are going to be biased. In this case, it’s easy to think what some of those excluded variables might be—base running, for example.

Another model, the Markov model, is less affected by this problem, and it’s the model that was used in The Book: Playing the Percentages in Baseball by Tango, Lichtman, and Dolphin. It looks like it would be feasible to develop a similar script that could generate optimal lineups based on the Markov approach, and frankly, I’d trust that model a lot more. But the main message that comes through from all of this is that Span really shouldn’t be leading off any more.

 

 

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2 Comments

  1. j / Mar 30 2014 3:35 pm

    You know, the main thing I got out of this was that, statistically, Desmond should be batting 8th. And though I never would have thought about it that way before, it makes a sort of sense. Comparing his OBP and SLG, it is clear that he does a much, much better job clearing the table than setting it. He is one of the least likely Nats to find himself on first base at the end of an at bat—which is perfect for a number eight hitter.

    But will he chase bad pitches in the 8 spot? Would his psychological profile be crushed by the move? If it impacts his approach at the plate, he would end up useless. The same thing could happen to Span. He strikes me as somebody who would respond poorly to moving down in the lineup.

    This is the difference between Matt Williams and all of us. Matt is coaching actual people, people he knows, and neither we nor any model can do that. With as superstitious as most ballplayers are, it is just as important to know the psychology of the person you are dealing with as it is to know their stats.

    From what I can tell, this is the secret to Shu’s success so far. An overanalyzing, dispirited, uncomfortable ballplayer is not going to achieve their potential. And granite-souled types like Jordan Zimmermann are the exception among ballplayers; as a rule, these guys are kinda head-cases.

    I’ll take Matty’s lineup.

    • Nat Anacostia / Mar 31 2014 7:57 am

      That’s a good point about Desmond, though Ramos has a similar profile and doesn’t chase bad pitches as much as Desmond does. I’d be inclined to have Ramos bat 8th. I also like the idea of having the pitcher bat 8th and let Span hit 9th.

      I also agree that psychology and comfort are important factors that really can’t be measured statistically. If I’m going to criticize Williams, I’ll try to do it over more substantive points.

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