Ichiro's Batting Stats: The April Edition

Ichiro Suzuki has hit poorly so far this season, with a slash line of .243/.289/.314. There's even been some media speculation that this means the Yankees might bench Ichiro in favor of Vernon Wells when Granderson returns.

How reasonable is it to pass judgement on Ichiro after 77 PAs in 22 games? This is a rhetorical question, as it's obviously unreasonable. However, for fun let's use the binomial distribution to estimate the probability that Ichiro's performance to date indicates his true talent level.

To use the binomial distribution, we need to estimate Ichiro's likely talent level. If we look at his Marcel projections, Ichiro's projected batting stats are as follows:

• BA: .273
• OBP: .311
• XBH/AB (Extra-base hits per AB)*: .056

It's doubtful that the Yankees would have given Ichiro a 2-year deal if these rather anemic numbers represented the front office's estimation of Ichiro's expected performance. Since the Yankees don't broadcast their performance projections, we'll have to make an educated guess. To do so, I am going to do is use Ichiro's 2001 season stats; since he's now a few years older, I'll reduce those numbers by 5%, meaing we will use the following:

• BA: .300
• OBP: .341
• XBH/AB*: .054

Here are the binomial probabilities that Ichiro's poor performance represents his actual skill levels.

Projection Type	BA	OBP	XBH/AB
Marcels	34%	37%	44%
2010-based estimate	18%	18%	47%

Not that this is surprising, but the probabilities indicate it is unlikely that Ichiro's first 77 PAs of the season reflect how he will perform in 2013. Moreso if you assume the Yankees' projections of his performance significantly exceed Marcels'.

Let's look at one other set of numbers, which are the expected range of these statistics after 77 PAs. The following table shows the range of values that the binomial distribution would expect, with 90% confidence, after 77 PAs:

Projection Type	BA	OBP	XBH/AB
Marcels	.186 - .357	.221 - .403	.014 - .100
2010-based estimate	.214 - .386	.260 - .429	.014 - .100

In other words, after 77 PAs a player's batting statistics could be either those of a superstar or those below a replacement-level player.


* To gauge Ichiro's projected power, I used extra-base hits per AB (XBH/AB) instead of slugging percentage because the latter cannot be used to estimate probability. This is because the binomial distribution requires that each trial have only 1 of 2 outcomes, and slugging percentage allows for 5 outcomes: out, single, double, triple, homer. So for today's purpose we'll just look at the probability that Ichiro gets an extra-base hit or not in HIS at-bats.

Rob Thomson's Reckless Tendency

On Saturday, Yankee third-base coach helped kill a rally. With a runner on 3rd and no outs, Francisco Cervelli lofted a shallow fly ball to Torii Hunter. Thomson sent the runner, who was thrown out - and by a mile, too!

Baseball conventional wisdom is that you should not make the first out of an inning at home. Statistics back this up.

Let's look at the impact of Thomson's coaching decision. According to the Run Expectancy Matrix published by Tom Tango:

• Teams with a runner on third and one out on average score .989 runs in the rest of the inning, with a 67.4% chance of scoring at least one run. 
• Conversely, a team with no one on base and 2 outs on average scores .112 runs in the rest of the inning, with a 7.5% chance of scoring at least one run. 

In other words, Thomson's decision reduced the Yankees' expected runs in the inning by .877 runs, and reduced the likelihood of scoring at least one run by 60%.
This unfortunately is hardly the first time Rob Thomson has so harmed the Yankees' chances to score runs. According to the Retrosheet play-by-play data, between 2009 (when Rob Thomson because the 3rd-base coach) and 2012, the Yankees have had 6 instances where a runner has been thrown out at home with zero outs. This is the 3rd worse such record in the major leagues - between 2009-2012, only the Red Sox and the Twins have had more instances of such bonehead coaching decisions.

There really is no excuse for this. Rob Thomson's standard response to such criticism is that he is aggressive. However, there is a difference between being aggressive and being reckless; and Thomson's tendencies here are merely reckless.

If you are interested, the following table lists the number of times each team has had a runner thrown out at home with no outs, ordered from worst to best:

Team	Times Out at Home, No Outs, 2009-2012
BOS	9
MIN	7
BAL	6
NYA	6
HOU	6
KCA	5
WAS	4
OAK	4
ARI	4
LAN	4
ANA	4
SEA	3
NYN	3
CLE	3
CHN	3
SFN	3
PIT	3
TBA	2
FLO	2
SDN	2
SLN	2
MIL	2
DET	2
CIN	2
TOR	1
COL	1
CHA	1
TEX	1
ATL	1
PHI	0

2013 AL East Projections: Are the Yankees the Favorites To Win the AL East?

Using the Marcels projection systems, I generated some team projections for the AL East.

First, a few comments on how I went about this, which I mention so that you can form your own judgement on the merits or pitfalls of this approach:

• To get to these team numbers, I started with the projected stats for players on each team most likely to play significant roles; these players were selected primarily by using MLB's depth charts. I then adjusted each team's totals to a full-season's worth of plate appearances and innings pitched - details are at the bottom of this post, below the fold.
• The won-lost records were calculated using the the Pythagorean expectation formula. For runs scored, I used the team total batting runs. For runs allowed, I used the team total of projected runs.
• The won-lost records should be used only to compare the AL East rivals; they are not intended for predicting actual wins. To do the latter properly, I would have had to total up the won-lost records of the entire league, and then make some adjustment to make sure the league total win-losses were equal. (Since I was primarily interested in gauging the Yankees' chances of winning the decision, and since the weather has been awesome this weekend I did not go to that length.)

Here are the projected AL East standings:

Team	W	L	R	RA	Winning %
Yankees	92	70	770	675	.565
Blue Jays	90	72	780	695	.557
Red Sox	90	72	800	716	.555
Rays	88	74	727	663	.546
Orioles	82	80	734	723	.508

The projections indicate what I'm sure we all thought: a tight race in which any of the 5 teams has a realistic chance of winning. That being said, for what it is worth, the Marcels projections make the Yankees a slight favorite.

That's nice to see. However, let's not pretend this is the "championship caliber" team that Hal Steinbrenner claimed he's built. The Yankees could certainly win it all with this team; the pitching especially should give us hope as Yankee fans. However, they are not one of the elite teams going into the season, which is what "championship caliber" means from the perspective of evaluating the front office's efforts. The team has a lack of depth which may make it harder to withstand injuries than Yankee teams of the recent past. That is why the Yankees go into the season with something like a 22-25% chance to win the AL East; a championship calibre team would have better odds than that.

For a basis of comparison, I put together team projections for the 2 elite teams in the AL, the Tigers and the Angels. As you can see, they project as significantly better teams:

Team	W	L	R	RA	Winning %
Angels	99	63	796	634	.612
Tigers	95	67	799	672	.586

The glass half empty perspective is that the Yankees project to be worse than last year's team. The glass half full perspective is that they still project to be competitive for the AL East.

Finally, here are the Marcels projections for your 2013 Yankees.

First, the hitters:

Hitter	Age	PA	AB	H	2B	3B	HR	BB	SO	IBB	HBP	SH	SF	SB	CS	BA	OBP	SLG	wOBA	Batting Runs	Reliability
Granderson, Curtis	32	611	533	130	20	6	34	65	158	2	6	2	5	14	4	.244	.330	.495	.352	88	87%
Cano, Robinson	30	617	560	169	39	3	27	46	89	9	7	0	4	5	2	.302	.360	.527	.369	100	87%
Teixeira, Mark	33	530	459	114	24	1	26	56	93	2	8	0	7	3	1	.248	.336	.475	.346	74	86%
Youkilis, Kevin	34	506	435	110	23	3	18	55	102	2	12	0	4	3	1	.253	.350	.444	.343	69	83%
Wells, Vernon	34	384	357	85	17	2	17	23	62	1	2	0	2	5	2	.238	.286	.440	.310	45	82%
Boesch, Brennan	28	499	457	118	24	2	15	34	99	2	5	0	3	7	3	.258	.315	.418	.316	59	83%
Hafner, Travis	36	368	322	82	16	1	13	36	77	4	8	0	2	2	1	.255	.342	.432	.331	48	78%
Jeter, Derek	39	631	576	163	26	2	11	44	93	1	5	3	3	12	4	.283	.338	.392	.319	74	87%
Rodriguez, Alex*	37	254	225	59	11	1	10	24	52	1	3	0	3	4	1	.262	.339	.453	.342	35	84%
Nix, Jayson	30	316	284	65	15	1	9	22	77	1	4	5	1	6	3	.229	.293	.384	.289	32	69%
Francisco, Ben	31	333	299	74	17	1	8	27	64	1	3	1	3	5	2	.247	.313	.391	.306	37	70%
Overbay, Lyle	36	309	277	66	17	1	8	29	69	2	1	1	1	2	1	.238	.312	.394	.303	34	78%
Suzuki, Ichiro	39	604	567	155	23	4	7	30	71	7	2	2	3	28	6	.273	.311	.365	.293	64	87%
Nunez, Eduardo	26	284	258	70	13	2	6	20	39	1	1	2	3	16	4	.271	.323	.407	.319	35	63%
Stewart, Chris	31	297	267	63	14	1	6	23	45	2	2	3	2	3	1	.236	.299	.363	.284	29	56%
Gardner, Brett	29	277	240	64	10	3	4	30	50	1	3	3	1	19	5	.267	.354	.383	.329	35	78%
Cervelli, Francisco	27	215	189	50	8	1	4	19	38	1	3	2	2	3	1	.265	.338	.381	.312	24	56%

* I prorated A-Rod's Marcels' projections by 50%, since we know he will not play until at least mid-season.

Here are the pitching projections:

Pitcher	Age	IP	G	GS	H	R	ER	HR	BB	SO	HBP	IBB	ERA	FIP	WHIP	HR/9	K/9	BB/9	K/BB	Reliability
Kuroda, Hiroki	38	190	29	29	186	82	75	23	49	147	6	4	3.55	4.00	1.237	1.1	7.0	2.3	3.00	81%
Hughes, Philip	27	161	30	28	160	84	78	25	46	136	5	1	4.36	4.43	1.28	1.4	7.6	2.6	2.96	76%
Sabathia, C.C.	32	184	26	26	174	78	69	19	49	175	6	3	3.38	3.46	1.212	0.9	8.6	2.4	3.57	82%
Nova, Ivan	26	161	27	26	166	83	77	21	53	131	7	3	4.30	4.30	1.36	1.2	7.3	3.0	2.47	76%
Pettitte, Andy	41	98	16	16	94	43	39	12	31	82	2	1	3.58	4.07	1.276	1.1	7.5	2.8	2.64	55%
Pineda, Michael	24	77	13	13	65	35	33	9	24	77	2	1	3.86	3.66	1.16	1.1	9.0	2.8	3.21	54%
Phelps, David	26	87	29	10	76	37	35	11	31	79	4	2	3.62	4.13	1.23	1.1	8.2	3.2	2.55	51%
Robertson, David	28	62	66	0	53	22	21	5	24	73	2	2	3.05	3.02	1.242	0.7	10.6	3.5	3.04	57%
Logan, Boone	28	57	84	0	53	26	24	6	22	58	2	3	3.79	3.61	1.316	0.9	9.2	3.5	2.64	51%
Eppley, Cody	27	49	61	0	48	23	22	5	17	39	1	2	4.04	3.88	1.327	0.9	7.2	3.1	2.29	36%
Kelley, Shawn	29	48	48	0	46	22	19	6	16	43	1	3	3.56	3.88	1.292	1.1	8.1	3.0	2.69	39%
Rapada, Clay	32	46	85	0	42	22	20	5	18	41	1	1	3.91	3.97	1.304	1	8	3.5	2.28	35%
Chamberlain, Joba	27	38	38	0	37	18	17	5	12	35	2	1	4.03	4.06	1.289	1.2	8.3	2.8	2.92	40%
Rivera, Mariano	43	35	37	0	32	14	13	3	9	30	1	1	3.34	3.34	1.171	0.8	7.7	2.3	3.33	40%

Play Ball!

Yankees are Worth $2.3 Billion: The Jayson Nix Edition

Forbes Magazine released its annual valuation of MLB teams. The Yankees are worth $2.3 billion.

$2.3 billion. Clearly the classic Yankee business model of going all in - started by Jacob Ruppert and revived by George Steinbrenner - pays off.

Hopefully Hal give this some thought and stop running the team as a cheap nitwit. It should be a sobering thought to the Yankees' CEO that the Opening Day lineup against lefty Jon Lester is likely to be something like this:

1. Brett Gardner
2. Ichiro Suzuki
3. Robinson Cano
4. Kevin Youkilis
5. Vernon Wells
6. Eduardo Nunez
7. Ben Francisco
8. Chris Stewart
9. Jayson Nix

My first thought when pondered this lineup was: "Wow. Hopefully the pitching lives up to its potential."

And you can't blame the injuries for the number of replacement-level and near-replacement players in this lineup. The lineup is this thin only because Hal put a lock on the petty cash drawer.

$2.3 billion dollars - that's a pretty nice return on the $8.8 million George Steinbrenner paid for the Yankees back in 1973. If the Yankee owners had run the team in Hal's penny-wise and pound-foolish fashion, the Yankees would be worth 1/3 of that. Just look at the Mets and do the math. The Mets have the same market as the Yankees, but are worth a mere $811 million - approximately 1/3 the worth of the Yankees.

WTF Did the Yankees Get Vernon Wells?

This is reminding me of a certain type of test question that you get as a kid. For example:


    Which one of the following baseball players does not belong in the same group as the other 2:

• Josh Hamilton
• Nick Swisher
• Vernon Wells

Pondering that one brought to mind another such question:

  Which one of the following people does not belong in the same group as the other 2:

• Jacob Ruppert
• George Steinbrenner
• Hal Steinbrenner

But since hope springs eternal, the one good thing I can say is that Wells has been truly horrible in only 4 of the last 6 seasons. Oddly, he was very good in the other 2 seasons - 2008 and 2010.

Dan Johnson, Projections, and Filling In for Mark Teixeira

There's a good chance that Dan Johnson will fill in for Mark Teixeira until Teixeira's wrist heals. So I thought it would be fun to compare the 2 players' batting projections, in order to estimate how much the injury might harm the Yankees in terms of runs scored.

This thought-experiment assumes that Teixeira will miss 45 games - about 28% of the season - and so we'll prorate their projected numbers to 190 PAs.

Prorating to 190 PAs assumes Johnson will play regularly in this period. If he makes the team he may just platoon. But since Johnson's career splits indicate no difference in his stats against righties vs. lefties, we'll keep this comparison simple by assuming he plays regularly.

We'll look at prorated projections from 2 systems - Marcels and Cairo - with the projected numbers prorated to 190 PAs. The reason for looking at both systems is that Marcels only uses major league statistics from recent years, while Cairo also incorporates minor-league statistics. As you'll see, this makes a difference for Johnson.

First, here are the Marcels projections:

Player	PA	AB	H	2B	3B	HR	BB	BA	OBP	SLG	wOBA	Batting Runs	Reliability
Teixeira	190	165	41	9	0	9	20	.248	.337	.467	.343	26	86%
Johnson	190	165	37	7	1	7	21	.224	.317	.406	.312	22	44%

Marcels projects Johnson as being significantly worse than Tex, as would be expected. In terms of a quarter-season, if we apply the sabermetric convention of 10 runs correlating to 1 win, the 4-run difference in batting runs has Teixeira contributing an extra .4 wins. So Marcels evaluates the injury to Teixera as being significant, but not so much that it risks ruining the season.

One thing to note before moving onto Cairo is the reliabilty column. In Marcels, the reliability percentage describes how much of the player's projection was based on his actual stats, versus the regression-to-the-mean component. This means that Teixeira's projections are significantly more likely to be accurate.

Now here are the prorated Cairo projections:

Player	PA	AB	H	2B	3B	HR	BB	BA	OBP	SLG	wOBA	Batting Runs
Teixeira	190	164	41	9	0	9	21	.250	.342	.470	.346	27
Johnson	190	162	39	7	0	8	25	.241	.347	.432	.338	25

Cairo is much more favorable to Dan Johnson. This is because it incorporates his minor league stats, which have been pretty good. Cairo thus has Teixeira as only marginally better than Johnson over 190 PAs.

As a fan, the differences in the 2 projection systems make Dan Johnson a more interesting player to me. The way I look at it is that Marcels rates Johnson the way GMs' decisions have rated him - as a marginal AAAA player. Cairo however rates him as an underrated bargain - a player whose skills GMs have been wrong about. If Johnson gets a chance, it'll be interesting to see which of these evaluations is closer to the mark. 190 PAs won't prove anything; but if Johnson hits similarly to what Cairo projects, he'll get an opportunity for more PAs.

Age and the 2013 Yankees: Historical Perspective

There's been a lot of talk about the Yankees' age. When I ran Marcels projections, the average ages of the 2013 Yankees were as follows:

• Batters: 33.2
• Pitchers: 30.6

The batters' collective age is relatively old; since 1996, only 4 teams had hitters averaging age 33 or older. One of them was last year's Yankees - they won 95 games and reached the ALCS.

Do these numbers mean anything?

One way to examine this question is to look at baseball history. For this exercise, we'll take all the teams since 1996, group them into ages, and compare the age groups' average winning percentages.

The following table shows the results for hitting. As you can see, the older teams actually do better than the younger teams:

Team Average Batter Ages and Winning Percentage (since 1996)

Age	# of Teams	Avg. W. Pct.
32+	15	.540
31	34	.541
30	79	.528
29	119	.506
28	132	.491
27	95	.477
26	24	.461
Below 26	8	.418

This surprised me - I excepted that the sweet spot would be teams averaging around 28-30.

Certainly I'm not suggesting that being older causes teams to be better; age is more nuanced than that. There have been plenty of mediocre old teams, such as the 1998 Orioles.

Rather, the point merely that being an older team does not mean the team will do poorly in a given season. This may seem obvious. But I mention this because there has been a fair amount of premature fork-sticking into the Yankees due to their age; these numbers provide a counter weight.

That being said, I am concerned about age and this year's team, because the team has lost depth. Starting players such as Nick Swisher and Russell Martin have not been well-replaced.  Travis Hafner's roster spot is devoted to a player who cannot play in the field. Invaluable bench player Eric Chavez was let go.

If you've got an aging team, it's wise to plan for needing to rest some players and to have perhaps more than your share of injuries. Hopefully players such as Corban Joseph, Ronnier Mustelier, Melky Mesa, Zoilo Almonte, etc., will exceed expectations; what scares me is the risk of players such as Jayson Nix, Dan Johnson, and Matt Diaz getting 400 ABs.