Tuesday, December 15, 2009

Leadoff Hitters, 2009

Once again, here is a look at the composite performances of the players who batted in the leadoff spot for each team. The data is from baseball-reference.com and again, it includes ALL of the PA out of the leadoff spot. In parentheses I list the players who appeared in twenty or more games in the #1 slot (which is not the same as starting twenty games; they could have been pinch runners, defensive replacements, etc.), but that does not in any way mean that they are the only contributor to the team total.

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 score runs. So let's start by looking at runs scored per 25.5 outs (AB - H + CS):

1. NYA (Jeter), 6.6
2. LAA (Figgins), 6.4
3. TOR (Scutaro), 6.3
7. LA (Fucal/Pierre), 5.9
Leadoff average, 5.3
ML average, 4.6
28. CIN (Taveras/Stubbs/Dickerson), 4.6
29. NYN (Pagan/Reyes/Cora), 4.5
30. OAK (Kennedy/Cabrera/Sweeney), 4.4

I will always list the top and bottom three, as well as the leader and trailer in each league if they are not already included. There will be some different names popping up on the leader lists, as there were a number of changes involving top leadoff hitters: injury-riddled seasons for Jose Reyes and Grady Sizemore, the flip-flop of Johnny Damon and Derek Jeter, and Hanley Ramirez' move into the #3 slot in the Florida batting order.

Next up is the other obvious metric, On Base Average, which here excludes HB and SF:

1. NYA (Jeter), .398
2. LAA (Figgins), .389
3. SEA (Suzuki), .382
6. PIT (McCutchen/Morgan), .362
Leadoff average, .344
ML average, .330
26. OAK (Kennedy/Cabrera/Sweeney), .320
28. SF (Velez/Rowand/Winn), .304
29. CIN (Taveras/Stubbs/Dickerson), .301
30. PHI (Rollins), .293

Two things jarred me when looking at this list--first, the fact that Pirates leadoff hitters led the NL in OBA. Andrew McCutchen (.366 in 487 PA) and Nyjer Morgan (.351 in 211) both contributed to this feat. Meanwhile, on the other side of the state, Jimmy Rollins led the Phillies to baseball's worst mark.

What I call Runners On Base Average is a modified OBA, equal to the Base Runs A factor per PA (or regular OBA less HR and CS in the numerator). It measures the number of times a player is actually on base available to be driven in by a teammate. It penalizes homers, obviously, but if you believe that the role of a leadoff hitter is to get on base for others, that is not necessarily a drawback. The leaders were:

1. NYA (Jeter), .364
2. LAA (Figgins), .359
3. SEA (Suzuki), .355
4. STL (Schumaker/Ryan/Lugo), .348
Leadoff average, .313
ML average, .296
28. CIN (Taveras/Stubbs/Dickerson), .272
29. DET (Granderson), .266
30. PHI (Rollins), .256

The Tigers leadoff men led baseball with 34 homers, dropping their already below-average .321 OBA to last in the AL when homers are removed. Incidentally, Astros leadoff hitters hit the fewest longballs (4).

Runs to RBI ratio is not a measure of quality, but rather of shape. The conventional stereotype of an ideal leadoff man would have a high ratio; those who are non-traditional are more likely to have a low ratio:

1. CIN (Taveras/Stubbs/Dickerson), 2.5
2. STL (Schumaker/Ryan/Lugo), 2.4
3. WAS (Guzman/Morgan/Harris), 2.4
5. LAA (Figgins), 2.1
Leadoff average, 1.6
ML average, 1.0
28. TEX (Kinsler/Borbon), 1.3
29. DET (Granderson), 1.2
30. SF (Velez/Rowand/Winn), 1.2

As you can see with just a glance, R/RBI ratio does not track the quality measures above very closely. Cincinnati ranked in the bottom three in the first group of metrics we examined, but here they lead the way, not due to any particular ability to score runs but due to their anemic .348 SLG (last) and .093 ISO (third last, ahead of only HOU and LAA). The Angels rank high as well, yet did well in runs scored and OBA.

Bill James' designed his Run Element Ratio for a similar purpose--identifying whether hitters fit the traditional mold of table setters or cleanup men. RER is the ratio of steals and walks (both events that do little to advance other baserunners) to extra bases (power). We should expect somewhat similar results to R/RBI ratio, but without the influence of teammates and with singles excluded from consideration:

1. LAA (Figgins), 2.4
2. HOU (Bourn/Matsui), 2.0
3. BOS (Ellsbury/Pedroia), 1.4
Leadoff average, 1.1
ML average, .8
28. PHI (Rollins), .7
29. SF (Velez/Rowand/Winn), .7
30. DET (Granderson), .6

Another Bill James measure was what I'll call Leadoff Efficiency--an estimated runs scored per 25.5 outs. James' formula assumes that 35% of runners on first (estimated as S + W - SB - CS) will score; 55% of runners on second (D + SB); 80% of runners on third (T); and of course homers always result in a run scored. As Tango Tiger has pointed out here in the past, these weights are not particularly accurate, which is evidenced by the fact that the average LE is 6% higher than the average of actual runs scored/25.5 outs for leadoff men. Nevertheless, it is James' metric and I'll present it as he figures it:

1. NYA (Jeter), 7.3
2. SEA (Suzuki), 6.4
3. TOR (Scutaro), 6.3
5. PIT (McCutchen/Morgan), 6.3
Leadoff average, 5.7
ML average, 5.5
28. OAK (Kennedy/Cabrera/Sweeney), 5.0
29. SD (Gwynn/Cabrera), 4.9
30. CIN (Taveras/Stubbs/Dickerson), 4.6

Transitioning back to metrics that are designed for more general application, David Smyth has suggested using 2*OBA + SLG for leadoff hitters. Since the most accurate weight for OBA in an OPS-type construction (for the purpose of predicting team runs scored) is somewhere in the vicinity of 1.5-1.8, using a weight of two gives a little bit of a boost to OBA, but not excessively so (and still closer to the ideal weight than what is used in standard OPS or even OPS+). I have taken 70% of the result to bring it back onto the normal OPS scale; since neither OPS nor 2OPS is on an organic scale, we might as well stick with the more familiar scale:

1. NYA (Jeter), 892
2. SEA (Suzuki), 851
3. TOR (Scutaro), 816
5. PIT (McCutchen/Morgan), 811
Leadoff average, 769
ML average, 754
27. OAK (Kennedy/Cabrera/Sweeney), 705
28. PHI (Rollins), 701
29. SD (Gwynn/Cabrera), 694
30. CIN (Taveras/Stubbs/Dickerson), 665

Finally, we can always just evaluate a leadoff hitter in the same way we'd generally evaluate any other: standard Runs Created per Game:

1. NYA (Jeter), 7.1
2. SEA (Suzuki), 6.2
3. PIT (McCutchen/Morgan), 5.7
Leadoff average, 5.0
ML average, 4.8
28. OAK (Kennedy/Cabrera/Sweeney), 4.1
29. SD (Gwynn/Cabrera), 3.8
30. CIN (Taveras/Stubbs/Dickerson), 3.7

If writing a piece like this obligates one to anoint one team's leadoff men as the most effective, then it's the Yankees, led by Derek Jeter. The worst? Well, it's tough to believe, but Willy Taveras managed to do what Jerry Hairston, Corey Patterson, and friends could not in 2008--lead the Reds leadoff slot to the bottom of the rankings in three categories.

Here is a link to a spreadsheet with all of the data, sorted by OBA:

Leadoff Hitters 2009

5 comments:

  1. for the uninformed here, mostly me, why 25.5 outs?

    ReplyDelete
  2. I'm defining outs made in this case as AB-H+CS, and the average outs/game when outs are defined in that manner is right around 25.5 (it was actually 25.43 in the AL and 25.38 in the NL this season).

    So using 25.5 outs puts it on roughly the same scale as team runs scored/game.

    ReplyDelete
  3. 2*OBP+SLG is mentioned in THE BOOK as a good estimator of wOBA. So using that or Runs Created is simply a general measure of hitter production, not specific to leadoff. I like to think in terms of hitters that derive a larger proportion of their output from OBP rather than slugging so OBP/SLG ratio or wOBA*OBP/SLG might be a better stat for choice of leadoff man.

    ReplyDelete
  4. Marc, it's true that 2*OBA + SLG approximates wOBA, but Tango's work and my own have both indicated that 1.6-1.8 times OBA is the best value. Assuming that is the case, using 2 is a very slight extra weight on OBA. I agree, though, that it is something of a general hitter method.

    OBA/SLG ratio is a similar concept to the Run Element Ratio--I wouldn't be crazy about it because of the different denominators. wOBA*OBA/SLG is interesting, but my personal preference is for metrics with easily explicable units.

    ReplyDelete
  5. I just realized that if you substitute 2(or 1.8 or 1.6)*OBP +SLG for wOBA, then wOBA*OBP/SLG becomes 2*OBP^2+OBP, something that will rank hitters no differently than OBP. If, however, you use OBP-SLG instead you get something a little more interesting: 2*OBP^2-OBP*SLG-SLG^2

    ReplyDelete

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