Monday, December 21, 2015

Leadoff Hitters, 2015

I will try to make this as clear as possible: the statistics are based on the players that hit in the #1 slot in the batting order, whether they were actually leading off an inning or not. It includes the performance of all players who batted in that spot, including substitutes like pinch-hitters.

Listed in parentheses after a team are all players that started in twenty or more games in the leadoff slot--while you may see a listing like "COL (Blackmon)” this does not mean that the statistic is only based solely on Blackmon's performance; it is the total of all Colorado batters in the #1 spot, of which Blackmon was the only one to start in that spot in twenty or more games. I will list the top and bottom three teams in each category (plus the top/bottom team from each league if they don't make the ML top/bottom three); complete data is available in a spreadsheet linked at the end of the article. There are also no park factors applied anywhere in this article.

That's as clear as I can make it, and I hope it will suffice. I always feel obligated to point out that as a sabermetrician, I think that the importance of the batting order is often overstated, and that the best leadoff hitters would generally be the best cleanup hitters, the best #9 hitters, etc. However, since the leadoff spot gets a lot of attention, and teams pay particular attention to the spot, it is instructive to look at how each team fared there.

The conventional wisdom is that the primary job of the leadoff hitter is to get on base, and most simply, score runs. It should go without saying on this blog that runs scored are heavily dependent on the performance of one’s teammates, but when writing on the internet it’s usually best to assume nothing. So let's start by looking at runs scored per 25.5 outs (AB - H + CS):

1. BOS (Betts/Pedroia), 5.7
2. CHN (Fowler), 5.6
3. STL (Carpenter/Wong), 5.5
Leadoff average, 4.9
28. TB (Guyer/Kiermeier/Jaso), 4.4
ML average, 4.2
29. ATL (Peterson/Markakis), 4.0
30. SEA (Marte/Jackson/Morrison), 3.8

The Rays are the team that stands out here, below average despite a healthy .339 OBA. Otherwise the leaders were above average in OBA and the trailers below average, although they weren’t extreme:

1. CLE (Kipnis), .368
2. HOU (Altuve/Springer), .367
3. CHA (Eaton), .356
4. SF (Aoki/Pagan/Blanco), .353
Leadoff average, .329
ML average, .319
28. KC (Escobar), .297
29. CIN (Phillips/Hamilton/Bourgeois), .291
30. LAA (Aybar/Calhoun/Giavotella), .282

I did include HB in OBA this year, so it is (H + W + HB)/(AB + W + HB).

I recently heard some on MLB Network saying that a key for the White Sox would be Adam Eaton getting back to form. But the Eaton-led Chicago leadoff men were quite solid. They even posted a .138 ISO which was one point better than the average for leadoff hitters, so I’m not sure where the notion that Eaton was the problem with the Chicago offense came from.

Escy-magic alright. But if it magically works for a handful of playoff games, by all means, let’s start a trend towards hacking low OBA leadoff hitters. Maybe the Angels will be the first takers and leadoff Andrelton Simmons--he couldn’t do much worse than their 2015 output.

The next statistic is what I call Runners On Base Average. The genesis for ROBA is the A factor of Base Runs. It measures the number of times a batter reaches base per PA--excluding homers, since a batter that hits a home run never actually runs the bases. It also subtracts caught stealing here because the BsR version I often use does as well, but BsR versions based on initial baserunners rather than final baserunners do not. Here ROBA = (H + W + HB - HR - CS)/(AB + W + HB).

My 2009 leadoff post was linked to a Cardinals message board, and this metric was the cause of a lot of confusion (this was mostly because the poster in question was thick-headed as could be, but it's still worth addressing). ROBA, like several other methods that follow, is not really a quality metric, it is a descriptive metric. A high ROBA is a good thing, but it's not necessarily better than a slightly lower ROBA plus a higher home run rate (which would produce a higher OBA and more runs). Listing ROBA is not in any way, shape or form a statement that hitting home runs is bad for a leadoff hitter. It is simply a recognition of the fact that a batter that hits a home run is not a baserunner. Base Runs is an excellent model of offense and ROBA is one of its components, and thus it holds some interest in describing how a team scored its runs, rather than how many it scored:

1. CLE (Kipnis), .337
2. SF (Aoki/Pagan/Blanco), .326
3. HOU (Altuve/Springer), .324
Leadoff average, .296
ML average, .286
28. SD (Myers/Solarte/Venable), .267
29. LAA (Aybar/Calhoun/Giavotella), .263
30. MIN (Dozier/Hicks), .257

I will also include what I've called Literal OBA here--this is just ROBA with HR subtracted from the denominator so that a homer does not lower LOBA, it simply has no effect. It “literally” (not really, thanks to errors, out stretching, caught stealing after subsequent plate appearances, etc.) is the proportion of plate appearances in which the batter becomes a baserunner able to be advanced by his teammates. You don't really need ROBA and LOBA (or either, for that matter), but this might save some poor message board out there twenty posts, by not implying that I think home runs are bad, so here goes. LOBA = (H + W + HB - HR - CS)/(AB + W + HB - HR):

1. CLE (Kipnis), .343
2. HOU (Altuve/Springer), .332
3. SF (Aoki/Pagan/Blanco), .331
Leadoff average, .303
ML average, .294
28. CIN (Phillips/Hamilton/Bourgeois), .273
29. LAA (Aybar/Calhoun/Giavotella), .267
30. MIN (Dozier/Hicks), .267

Usually the various OBA lists are pretty stable, and that was the case in 2015 as the Indians, Astros, and Giants leadoff hitters were the best at getting on base regardless of any slight differences in one’s definition of “getting on base” in this context.

The next two categories are most definitely categories of shape, not value. The first is the ratio of runs scored to RBI. Leadoff hitters as a group score many more runs than they drive in, partly due to their skills and partly due to lineup dynamics. Those with low ratios don’t fit the traditional leadoff profile as closely as those with high ratios (at least in the way their seasons played out):

1. CHN (Folwer), 2.3
2. CIN (Phillips/Hamilton/Bourgeois), 2.2
3. MIA (Gordon), 2.0
4. TEX (DeShields/Choo/Martin), 1.9
Leadoff average, 1.6
28. ATL (Peterson/Markakis), 1.3
29. SEA (Marte/Jackson/Morrison), 1.3
30. BOS (Betts/Pedroia), 1.2
ML average, 1.1

You may recall that the Red Sox leadoff hitters led the majors in runs scored per out, so seeing them with the lowest R/RBI ratio suggests they drove in a whole bunch of runs. Their 95 RBI easily led the majors (St. Louis was next with 82). Meanwhile, the Braves and Mariners had the lowest runs scored per out, so they got here more conventionally.

A similar gauge, but one that doesn't rely on the teammate-dependent R and RBI totals, is Bill James' Run Element Ratio. RER was described by James as the ratio between those things that were especially helpful at the beginning of an inning (walks and stolen bases) to those that were especially helpful at the end of an inning (extra bases). It is a ratio of "setup" events to "cleanup" events. Singles aren't included because they often function in both roles.

Of course, there are RBI walks and doubles are a great way to start an inning, but RER classifies events based on when they have the highest relative value, at least from a simple analysis:

1. MIA (Gordon), 1.7
2. CIN (Phillips/Hamilton/Bourgeois), 1.3
3. SF (Aoki/Pagan/Blanco), 1.2
Leadoff average, .8
ML average, .7
28. BOS (Betts/Pedroia), .5
29. MIN (Dozier/Hicks), .5
30. STL (Carpenter/Wong), .5

Since stealing bases is part of the traditional skill set for a leadoff hitter, I've included the ranking for what some analysts call net steals, SB - 2*CS. I'm not going to worry about the precise breakeven rate, which is probably closer to 75% than 67%, but is also variable based on situation. The ML and leadoff averages in this case are per team lineup slot:

1. CIN (Phillips/Hamilton/Bourgeois), 28
2. MIA (Gordon), 21
3. COL (Blackmon), 17
4. TOR (Reyes/Revere/Tulowitzki/Travis), 14
Leadoff average, 4
ML average, 1
28. STL (Carpenter/Wong), -8
29. ATL (Peterson/Markakis), -10
30. CLE (Kipnis), -10

Shifting back to quality measures, beginning with one that David Smyth proposed when I first wrote this annual leadoff review. Since the optimal weight for OBA in a x*OBA + SLG metric is generally something like 1.7, David suggested figuring 2*OBA + SLG for leadoff hitters, as a way to give a little extra boost to OBA while not distorting things too much, or even suffering an accuracy decline from standard OPS. Since this is a unitless measure anyway, I multiply it by .7 to approximate the standard OPS scale and call it 2OPS:

1. HOU (Altuve/Springer), 833
2. BOS (Betts/Pedroia), 823
3. CLE (Kipnis), 823
4. BAL (Machado), 815
5. STL (Carpenter/Wong), 812
Leadoff average, 745
ML average, 730
28. CIN (Phillips/Hamilton/Bourgeois), 641
29. KC (Escobar), 640
30. LAA (Aybar/Calhoun/Giavotella), 639

Along the same lines, one can also evaluate leadoff hitters in the same way I'd go about evaluating any hitter, and just use Runs Created per Game with standard weights (this will include SB and CS, which are ignored by 2OPS):

1. BOS (Betts/Pedroia), 5.6
2. HOU (Altuve/Springer), 5.6
3. COL (Blackmon), 5.4
Leadoff average, 4.4
ML average, 4.2
28. CIN (Phillips/Hamilton/Bourgeois), 3.4
29. LAA (Aybar/Calhoun/Giavotella), 3.2
30. KC (Escobar), 3.1

This is as good of a time as any to note that no park adjustments are applied anywhere in this post, which explains the presence of Colorado (St. Louis was the next highest-ranked NL team with 5.3).

Allow me to close with a crude theoretical measure of linear weights supposing that the player always led off an inning (that is, batted in the bases empty, no outs state). There are weights out there (see The Book) for the leadoff slot in its average situation, but this variation is much easier to calculate (although also based on a silly and impossible premise).

The weights I used were based on the 2010 run expectancy table from Baseball Prospectus. Ideally I would have used multiple seasons but this is a seat-of-the-pants metric. The 2010 post goes into the detail of how this measure is figured; this year, I’ll just tell you that the out coefficient was -.217, the CS coefficient was -.584, and for other details refer you to that post. I then restate it per the number of PA for an average leadoff spot (742 in 2014):

1. HOU (Altuve/Springer), 19
2. COL (Blackmon), 19
3. BOS (Betts/Pedroia), 19
Leadoff average, 3
ML average, 0
28. CIN (Phillips/Hamilton/Bourgeois), -14
29. LAA (Aybar/Calhoun/Giavotella), -19
30. KC (Escobar), -20

The Mets (Granderson) were the top non-Coors NL team at 16. Just to think that a few years ago Billy Hamilton was being hyped as a potential leadoff dynamo, the Angels had Mike Trout doing leadoff duties, and Alcides Escobar…well, I’m pretty sure everyone thought he would be a terrible leadoff hitter.

The spreadsheet with full data is available here.

No comments:

Post a Comment

Comments are moderated, so there will be a lag between your post and it actually appearing. I reserve the right to reject any comment for any reason.