Friday, December 30, 2005

Hitting by Position, 2005

This will be a fairly boring article examining offensive production by fielding position in 2005. The data, as it did for the leadoff hitter piece, came from the Baseball Direct Scoreboard, which apparently gets its’ data from STATS. Anyway, I included just the basic hitting stats(AB, H, D, T, HR, W) so this examination will not include SB/CS and other useful information.

The first basic thing is to take a look at the averages at each position for all hitters. These are BA/OBA/SLG and then RG:
C : 253/310/390/4.11
1B: 276/350/471/5.69
2B: 274/330/413/4.67
3B: 270/334/435/5.01
SS: 270/321/394/4.32
LF: 276/339/448/5.24
CF: 272/330/423/4.79
RF: 270/335/454/5.23
DH: 259/334/438/5.05
P : 148/178/190/.42
TOT: 266/327/421/4.72

The Total line is not the total for all ML players, it is the total for those positions. I’m not exactly sure how STATS determines which PAs count as hitting for a particular position, but they have other categories such as pinch hitters.

I don’t see anything remarkable in those numbers; they match the defensive spectrum fairly well. The spectrum can be written as:
DH - 1B - LF - RF - 3B - CF - 2B - SS - C - P
The RGs put in order are:
1B - LF - RF - DH - 3B - CF - 2B - SS - C - P
The only difference is with the DH position. It is clear that the DH position is the least demanding defensively, but there are various possible explanations for why they don’t come out that way in terms of production. Other than that, the one year sample is a perfect match for our expectation.

One question that is raised by the DH’s performance is how do DH stats vary between the AL and NL? NL teams only use the DH for a very small number of games; do they get similar production to AL teams? And we can ask the same question about AL pitchers.

Here’s how it turned out in 05:
AL DH: 259/335/441/5.10
NL DH: 250/321/385/4.24
AL P : 115/139/167/-.12
NL P : 150/180/191/.46
As you can see, AL DHs easily outperformed their NL counterparts, and NL pitchers did the same to the AL hurlers. Whether this is because NL hitters take batting practice, or because AL teams seek out a DH and NL teams just use some guy off the bench, or because of some other potential explanation, I don’t know. But there was a big difference.

We can also use this data to come up with positional adjustments based on the ‘05 season. To do this I will divide the positional RG by the total RG. I have always lumped DH and 1B in together, and I have also combined LF and RF. It is my belief that the difference between the players who fill out those positions is largely based on defense. What I mean is that at other positions, you choose a second baseman and a shortstop and a third baseman, etc. At LF and RF, you choose two corner outfielders, and the one with the better arm may wind up in RF, or the one with more range in LF, or what have you. But the two positions are very much interchangeable. At least that’s how I see it. With that considered, here are the total positional averages for 1B/DH and LF/RF:
1B/DH: 270/345/460/5.48
LF/RF: 273/337/451/5.23
That gives us these positional adjustments (the positional adjustments that I have traditionally used, based on 1992-2001 data, are in parentheses):
C = .87(.89)
1B/DH = 1.16(1.19)
2B = .99(.93)
3B = 1.06(1.01)
SS = .91(.86)
LF/RF = 1.11(1.12)
CF = 1.01(1.02)

Looking at the differences between the 2005 data and the 1992-2001, the major difference is the gain of production at the skill positions in the infield at the expense of the corners. Of course, this is just a one-year sample and so it would be inappropriate to draw any conclusions about changes in the game from it.

One fun application of these PADJs that I have not done in the past is to see how teams’ offensive production was distributed by position. Some teams might have the bulk of their offensive strength coming from the traditional hitting positions, while others may take advantage of good hitting at traditional weak spots like the middle infield.

I’m not sure that the way I’ve chosen to do this is the best, but it is what it is. I have simply found the correlation between the position adjustment (for the league as a whole) and the position RGs for each team. Positive correlations will indicate that the team got higher production from the positions you would expect would give higher production (left side of the spectrum). For the AL, all positions were used except pitcher, while pitcher and DH were ignored for the NL. So here are the team correlations broken down by league:
American League
DET…..+.87
SEA…..+.81
KC……+.71
CHA….+.61
TB……+.59
BOS….+.59
TOR….+.56
NYA….+.40
LAA….+.36
MIN….+.27
TEX…..+.15
OAK….+.09
CLE….-.08
BAL….-.27
All players…..+.33
The “all players” figure is the correlation between PADJ and RG for all 9*14 positions in the AL.
National League
ARI……+.93
COL…..+.82
FLA……+.77
MIL……+.76
WAS…..+.76
STL……+.73
HOU…..+.62
PIT…….+.56
CHN…..+.52
PHI…….+.43
SF……..+.35
NYN…..+.33
SD……..+.33
LA…….+.26
CIN……+.20
ATL……+.13
All players….+.52

As you can see, most teams had fairly strong correlations between PADJ and the Positional RG. Only two teams had negative correlations; the Indians and the Orioles. I expected to see Cleveland on this list, because of the pathetic performance from the corners which I have touched on a number of times here (particularly Blake, Boone, and Broussard). We’ll take a look at the team with the best correlation, the Diamondbacks. What I have done is list the league position adjustment on the first line and below that the position adjustment based on the team stats. This was calculated by taking the average of RG from each position, and then dividing the RG for a given position by this. The reasoning behind this is that if the PADJ for catcher is .87, then a team’s catcher should have an RG 87% of his team’s RG. You can see that if the PADJ and Team Adjusted RG numbers match up well, the correlation will be high (I have dropped the decimal points):
POS……....C…….1B……..2B……..3B……..SS…….LF…….CF………RF

As you can see, every position at which you expect to have below average offense had a below average output, and vice versa, except for center field. The Diamondbacks got most of their offense out of the left side of the spectrum. But how about the opposite side of the coin in Baltimore, which had the lowest correlation?
POS……....C…….1B……..2B……..3B……..SS…….LF…….CF………RF…….DH
The Orioles two best hitters, by far, were Roberts and Tejada at two of the weakest offensive positions. They also had pathetic production in the outfield and at DH.

Finally, since I write about them a lot anyway, here are the Indians’ figures.
POS…….......C…….1B……..2B……..3B……..SS…….LF…….CF………RF…….DH