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Offensive Ordering

Entering play Sunday, the Brewers offense rode a listless Chicago series to erase many of their gains made over the last couple of weeks. While the bats have performed at a notably below average rate throughout the season, there were signs of life while picking on some of the National League bottom feeders: Milwaukee scored 51 runs during their 8-2 sequence against the Mets, Reds, Marlins and Royals. Even with some expected correction from shifting to the Cubs pitching staff from struggling opponents, the Cubs arms themselves were not exactly great entering the series against the Brewers. If anything, the Brewers had a chance over the weekend to show their offensive improvements were legitimate against a currently-average pitching staff; instead, the bats catapulted the Cubs pitching staff back on track during (what will hopefully remain) the worst offensive sequence of games of the season.

Before Sunday’s shut out, the Brewers were playing in an NL / Miller Park environment scaled to approximately 126 Runs Scored over 28 games. With only 107 RS entering the game, Milwaukee’s offense was significantly below average, extrapolated to a 162 game pace of -110 RS. In other words, what this means is that if everything else remained equal for Milwaukee, the Brewers would be expected to win approximately 73 games based on the bats. Remarkably, this is an improvement over the club’s standing after 19 games (when the bats were on approximate pace of -160 RS), so it must be stated that perhaps the Cubs series could indeed be viewed as a rather unfortunate blip during a substantial upward trend. For example, if the Brewers can improve from -160 RS pace to -110 RS pace over the span of nine games, perhaps the club is indeed improving the offense and en route to a better RS / G outlook (on a related note, there are obviously real issues with attempting to extrapolate 162 game performance from 28 games played).

By position, the Brewers are struggling across the diamond. While it is commonly known by Brewers fans and analysts that second base, short stop, catcher, and right field are slow-starting positions, run production is lacking at other positions as well. Undoubtedly, one might suggest that this is a systemic outcome: batting orders are dynamic, and if players around the order are uniformly failing to produce, it stands to reason that even the best bats might under perform. Here, my quick-and-dirty at-a-glance stat RRBI will test the harmonic mean between Runs and Runs Batted In [(2*R*RBI)/(R+RBI)] for Brewers bats and National League bats, in order to approximate actual production within the run environment:

Positional Production NL RRBI/PA NL OPS MIL RRBI/PA MIL OPS Comparison
as DH 0.16 0.815 0.15 1.450 -0.08
as LF 0.13 0.729 0.09 0.626 -4.19
as RF 0.12 0.728 0.08 0.680 -4.93
as 1B 0.12 0.766 0.18 1.017 6.70
as 3B 0.12 0.753 0.13 0.810 1.03
as 2B 0.12 0.766 0.06 0.641 -6.80
as CF 0.11 0.729 0.10 0.872 -1.88
as C 0.10 0.686 0.05 0.561 -5.19
as SS 0.10 0.684 0.07 0.419 -3.59
as PH 0.08 0.602 0.09 0.804 0.29
as P 0.04 0.304 0.05 0.306 0.53
Total -18.10

This basically shows the under performing offense, including below average production in center field and left field. What is interesting is that despite the acquisition of Lorenzo Cain and Christian Yelich, and their respectively strong performances thus far, the Brewers have been unable to capitalize on the presence of either player. Yet this could also be viewed as an area of correction: if even the strong performances of Cain and Yelich are not leading the offense to produce runs, the Brewers could relatively easily change course.

By batting order, another quick-and-dirty RRBI analysis shows that the Brewers may indeed be a due a course correction through the development of their batting order. Thus far, the Brewers’ batting order shows a better offensive performance (by distribution of runs produced) compared to the National League than the raw positional analysis. Have a look:

NL NL RRBI/PA NL OPS MIL RRBI/PA MIL OPS Comparison
Batting 1st 0.10 0.699 0.10 0.746 -0.46
Batting 2nd 0.12 0.785 0.14 0.801 2.25
Batting 3rd 0.13 0.801 0.12 0.718 -1.16
Batting 4th 0.13 0.785 0.13 0.831 0.00
Batting 5th 0.13 0.773 0.09 0.938 -4.38
Batting 6th 0.12 0.723 0.08 0.583 -3.95
Batting 7th 0.10 0.674 0.08 0.663 -2.38
Batting 8th 0.08 0.593 0.06 0.570 -2.17
Batting 9th 0.07 0.457 0.06 0.383 -1.44
Total -13.70

A couple of things stand out here. First, it is notable that batting Orlando Arcia eighth basically mitigates his short stop production lapse. While he’s not batting at the level of an average short stop, if the Brewers continue to bat Arcia eighth that performance may not damage the Brewers run production as much as one might expect. Meanwhile, the fifth spot has produced a fantastic On-Base Percentage-plus-Slugging Percentage (OPS) without producing runs, which suggests that more of a course correction might be in order for the offense.

Using these tools to produce an ideally distributed batting order, Milwaukee’s order might look like this (with everyone healthy):

Ideal Order NLĀ OPS Rank Brewers Bat
1 6th 2B Villar
2 T-2 CF Cain
3 Best 1B Thames
4 T-2 3B Shaw
5 4th RF Yelich
6 5th LF Braun
7 7th C Pina
8 8th SS Arcia
9 Pitcher Pitcher

It is definitely tough to follow the Brewers offense for the time being, but despite the poor offensive showing it may not be time for a batting order shift. Lorenzo Cain and Christian Yelich should indeed lead the offense. Meanwhile, Domingo Santana’s bat must come along, and his middle order presence will be important; while Eric Thames is out, Santana should be given the opportunity to improve as the club’s fifth batter. If anything, the only major change from the club should be to play Jonathan Villar more exclusively at second base, as he represents a current in-house improvement over Eric Sogard and Hernan Perez. It is difficult to think that an offense on pace to be significantly below average over the course of 162 games should not make changes for the time being, but there is reason to believe that some of the lack of runs produced is due to distributional inefficiencies.


 

Photo Credit: Patrick Gorski, USA Today Sports Image

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