Tuesday, December 26, 2006

Leadoff Hitters, 2006

Last year I did a piece ranking the leadoff performances of each teams in a number of categories. I will do the same this year, although without a lot of the comments about each method and how it is calculated. I’ll refer you to last year’s post for that.

In brief, though, I don’t believe that this is a particularly useful activity--for the large part, hitters are hitters, regardless of what slot in the order they bat. Leadoff is probably the most important role, but in general, the best leadoff hitter and the best hitter period would be the same guy. That does not of course mean that leadoff is necessarily the best possible slot for the best hitter, but in general, too much is made of lineup construction among traditional folks anyway. Nevertheless, it is an interesting exercise if not particularly enlightening.

The data comes from the Baseball Direct Scoreboard and is for the team’s #1 slot hitters as a whole. I have listed in parentheses the guys who had the most games played while batting in the #1 spot, which sometimes is less then half of the team’s games. The “ML average” listed in the table is for ML leadoff hitters, not the entire league as a whole. I’ll sometimes discuss the league total in my comments.

The first category I’ll look at is good old runs scored, per 25.5 outs:
1. CLE(Sizemore), 7.3
2. NYA(Damon), 6.7
3. NYN(Reyes), 6.6
ML Average, 5.5
28. ARI(Counsell), 4.8
29. CIN(Freel), 4.6
30. CHN(Pierre), 4.2
Johnny Damon’s Red Sox were number one a year ago, and his Yankees are #2 this go around. Of course, runs scored are heavily influenced by the succeeding batters, and it’s little surprise three of the game’s best offenses are represented in the top 3 spots here. Juan Pierre was seen as a leadoff solution for the Cubs, but as I pointed out last year, this was dubious as he was coming off a year in Florida in which the Marlins were in many of the trailer categories.

On Base Average is an obvious criteria to look at:
1. CLE(Sizemore), .369
2. LA(Furcal), .366
3. SEA(Suzuki), .365
ML Average, .339
28. ARI(Counsell), .301
29. MIL(Weeks), .300
30. PIT(Duffy), .298
The average for all players was .333, so the leadoff advantage is only six points; last year it was ten. The Yankees are fourth on the list, so Damon did his job, although none of the OBAs are eye-popping for an individual player.

Runners On Base Average removes HR and CS from OBA, leaving it not as a pure measure of skill but as an accounting for the percentage of PA in which the leadoff men sets the table by remaining on base:
1. SEA(Suzuki), .351
2. LA(Furcal), .330
3. OAK(Kendall), .327
ML Average, .305
28. WAS(Soriano), .271
29. ARI(Counsell), .267
30. MIL(Weeks), .265
The average for all hitters was .293, making a larger leadoff/overall gap in ROBA then in OBA. Last year, when the opposite was true, I presumed it was because of the high number of caught stealings racked up by leadoff hitters. Washington is near the bottom here because of Soriano’s 40 HR season (they ranked ninth in OBA). The usual suspects, Cleveland and New York, come in at seventh (.321) and eleventh (.318) respectively.

Run Element Ratio from Bill James is not a skill or production measure at all. It is a ratio between offensive elements ideally placed at the beginning of an inning to set it up (walks and steals) versus those ideally placed at the end to clean it up (extra bases):
1. LAA(Figgins), 2.1
2. OAK(Kendall), 1.8
3. MIN(Castillo), 1.7
ML Average, 1.0
28. CLE(Sizemore), .6
29. TOR(Johnson), .6
30. TEX(Matthews), .6
The overall average is .7, and only five teams were below that with their leadoff hitters (the three above as well as Kansas City and Tampa Bay). Sizemore’s power again put Cleveland in the bottom three, while Texas is last for the second year in a row despite changing their primary leadoff hitter from David Dellucci to Gary Matthews. Since those two are now in Cleveland and Los Angeles, we’ll see if they can do it again with a new man in 2007.

Another Bill James tool was his own method for evaluating leadoff hitters, which I call Leadoff Efficiency. This is the number of expected runs scored per 25.5 outs, which is a (relatively) pure of the leadoff man, unlike the actual runs scored figures we looked at first:
1. CLE(Sizemore), 7.1
2. NYN(Reyes), 6.6
3. WAS(Soriano), 6.6
ML Average, 5.6
28. STL(Eckstein), 4.8
29. ARI(Counsell), 4.7
30. MIL(Weeks), 4.6
Damon is again just off the list, fourth at 6.5. Last year the leadoff efficiency formula overestimated actual runs scored for leadoff hitters by a fairly big margin, but this year, the actual was 5.49 and the expected 5.55, not bad at all. Scott Podsednik is fourth to last and Chone Figgins sixth to last.

One can always just look at a leadoff hitter just like we would any other. So here is the list by good old Runs Created per Game:
1. CLE(Sizemore), 6.9
2. NYN(Reyes), 6.4
3. WAS(Soriano), 6.3
ML Average, 4.9
28. LAA(Figgins), 3.9
29. ARI(Counsell), 3.9
30. MIL(Weeks), 3.7
The average for all hitters was 5.0, so once again the average leadoff hitter was worse then the average hitter. Damon is fourth at 6.2

Last year I included what I called Pure Leadoff RAA. Basically, it is the linear weight RAA total a player would get if he always batted with nobody on base and nobody out (the ideal leadoff situation). I based it off of Pete Palmer’s Run Expectancy table from The Hidden Game for simplicity’s sake, which means it is not fully adapted to the run environment of today’s game, but the values should not be too far off. One assumption that the formula makes that I did not mention last year is it assumes that all stolen base attempts occur during the next batter’s PA (or in other words, in a runner at first, no out situation). Here are the figures in this category:
1. CLE(Sizemore), +37
2. NYN(Reyes), +32
3. WAS(Soriano), +29
ML Average, +1
28. ARI(Counsell), -9
29. STL(Eckstein), -10
30. MIL(Weeks), -12
NYA is again fourth at +27. The top three are the same as the RG list for overall hitting, with Soriano’s homers only worth 1 run instead of 1.46 there.

Last year, David Smyth suggested that I look at a modified OPS, 2*OBA + SLG, which I will call 2OPS. Since the optimal OPS construction is something like 1.7 or 1.8*OBA + SLG, using 2 is a way to give a bit more credit to the on base side of things while still having a decent overall measure of production. Since the OPS units are meaningless anyway, I scaled these back so that the league 2OPS ~ league OPS. So these figures are for (2*OBA + SLG)*.7:
1. CLE(Sizemore), 893
2. WAS(Soriano), 864
3. TEX(Matthews), 847
ML Average, 767
28. ARI(Counsell), 686
29. PIT(Duffy), 680
30. MIL(Weeks), 677

Although he may not fit the ideal prototype of a leadoff hitter, Grady Sizemore still comes out on top in most categories as the top leadoff hitter in the game in 2006, with Jose Reyes, Alfonso Soriano, and Johnny Damon close behind in many categories.

4 comments:

  1. Patriot,

    This link gives you the LWTS values for bases empty, 0 outs:
    http://www.tangotiger.net/RE9902event.html

    I also have this one, though I can't remember how I did it:
    http://www.tangotiger.net/lwtsrobo.html

    There is a better chart (Table 50) in THE BOOK, that uses Markov chains. I'd recommend that last one.

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  2. I was wondering why you didn't include Kevin Youkilis as a leadoff hitter. He played 65% of his games (95 out of 147) as a leadoff hitter. His .385 OBP when leading off the game would put him at number 1 on that list. 6.7 RC/G would put him at number 2. .352 runners on base average would put him at number 1. 6.7 runs scored per 25.5 outs would tie him at number 2 with Damon.

    I'm not sure how to calculate the rest of the metrics, but Youkilis was pretty clearly a great leadoff hitter in the 95 games in which he was the leadoff hitter. I'm not particularly experienced with crunching numbers, so some of these stats may be a bit off, but it seems to me that, since Youkilis was Boston's primary leadoff hitter for the year, he should be included in this analysis.

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  3. For those who might miss it, the references in Tango's post would enable you to get better/more accurate/more current weights for the PLRAA formula. I am not going to go back and redo the numbers, but next year I will base them off of one of those charts.

    James, I may not have made this clear, but the figures are for the aggregate team performance from the leadoff spot. The names in parentheses after the team indicate the team's primary leadoff hitter, who was indeed Youkilis. But I'm not looking at Youkilis' individual performance, rather all of the players who batted leadoff for the Red Sox and only their stats when actually leading off.

    Youkilis, as you point out, would do well in these categories, but as a whole, the Red Sox leadoff hitters were pretty average.

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  4. Alright. I guess I missed that (I must admit I sometimes skim through the words to get to the numbers. Rereading it, I missed a pretty clear paragraph, didn't I?

    Either way, great work.

    ReplyDelete

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