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Monday 22nd May 2017

Another month has passed so it is time to continue our look at the pitching peripherals.  Obviously, offense remains down, but some suggested as the weather warms, the runs will pick up.  Check local listings, but suffice it to say the weather was certainly warm in July.

With respect to fantasy analysis, not much can be done now to game the results.   The off season is the time to investigate if there are trends that can be applied to projection theory.  But, this does serve as an avenue to remind everyone of something I have been preaching since the spring.  In fantasy terms, value is relative.  The 50th best pitcher may have superior stats than in the past, but he still impacts your team as much as the 50th best pitcher of previous seasons.  His ERA and WHIP may be lower, but so are the totals at each point in the standings.  The leaders in ERA and WHIP have lower numbers than in past seasons.   Okay, I think there is ample text to get us below the pictured advertisement; here is the monthly 2011 data to date in tabular form along with the same numbers since 2007.

2011

ERA

WHIP

K/9

BB/9

HR/9

BAbip

April/March

3.903

1.311

7.09

3.28

0.91

0.290

May

3.801

1.316

6.92

3.23

0.87

0.292

June

3.780

1.293

6.91

3.01

0.88

0.291

July

4.002

1.322

7.23

3.03

0.91

0.299

2010

ERA

WHIP

K/9

BB/9

HR/9

BAbip

April/March

4.199

1.379

7.13

3.66

0.95

0.296

May

4.174

1.365

7.00

3.40

0.94

0.298

June

4.137

1.362

6.97

3.17

0.93

0.303

July

4.100

1.343

7.03

3.12

1.03

0.297

August

4.012

1.327

7.21

3.10

0.97

0.297

Sept/Oct

3.894

1.314

7.40

3.27

0.95

0.291

2009

ERA

WHIP

K/9

BB/9

HR/9

BAbip

April/March

4.583

1.440

6.96

3.87

1.07

0.299

May

4.354

1.395

6.88

3.47

1.01

0.300

June

4.045

1.342

6.81

3.35

1.05

0.289

July

4.265

1.373

6.98

3.35

1.04

0.299

August

4.532

1.406

7.12

3.29

1.17

0.306

Sept/Oct

4.205

1.391

7.14

3.49

0.97

0.302

2008

ERA

WHIP

K/9

BB/9

HR/9

BAbip

April/March

4.165

1.388

6.41

3.64

0.90

0.291

May

4.135

1.370

6.82

3.32

0.97

0.298

June

4.179

1.380

6.81

3.32

1.07

0.297

July

4.583

1.395

6.93

3.23

1.09

0.304

August

4.407

1.403

6.92

3.34

1.05

0.305

Sept/Oct

4.511

1.412

7.10

3.48

1.00

0.306

2007

ERA

WHIP

K/9

BB/9

HR/9

BAbip

April/March

4.123

1.369

6.60

3.52

0.92

0.291

May

4.375

1.378

6.39

3.25

0.99

0.297

June

4.512

1.405

6.70

3.24

1.05

0.304

July

4.497

1.415

6.50

3.31

0.99

0.305

August

4.596

1.419

6.78

3.26

1.11

0.307

Sept/Oct

4.699

1.445

7.05

3.44

1.10

0.313

 

Even though the overall ERA is highest in July, in terms of skills, pitching actually improved this past month.  The increase in runs is due to a higher BABIP, resulting in more hits.  Hurlers in fact fanned more and walked fewer batters that earlier in the season.  Note that homers also remained consistent.  There have been some recent instances of a power spike in July.

As alluded to, it is too early to determine why pitching remains improved, but at least in terms of the root skills (K/9, BB/9, HR/9), the Year of the Pitcher continues.  Could it be that it is poorer hitting as opposed to better pitching?  Sure, especially since there can be a cause and effect dynamic happening.  Teams feel they need better defense and they better defenders are weaker hitters.  Obviously, PEDs cannot be ruled out.  But again, this is a chore for the off season to help hone projection accuracy.

For now, the take home message is the top power hitters are even more valuable than before as they can really impact the delta in the standings since the hitting categories are so tightly bunched.  That is, as we have discussed previously, depressed offense results in compressed categorical distribution, meaning the top players can really move the needle, depending of course on the gaps in your unique league.

One of the favorite discussion points at this time of the season is what players historically have strong second halves and are therefore acquisition targets and the flip-side, what players usually crash and burn so it is best to get rid of them.  This is a concept that has long bothered me as it is my belief that while examples of such players likely exist, the fact they have done it for a few years is not predictive of it continuing to happen.  That is, I do not feel it is salient analysis to label a player as “first half” or “second half” and strategize accordingly.

The example I have used in the last involves the flipping of a coin.  My argument is if 32 people flip a coin five times, probability dictates that one will flip five heads.  One person flipping five heads is therefore expected within the range of possibilities.  I use this metaphor for the fantasy baseball population.  There are 750 active players at a given time and well over 1200 that are active over the course of the season.  Based on sheer randomness, one of 32 could have a better first (or second) half five years in a row.  That is somewhere between 25 and 35 players which is a pretty decent amount.  And no doubt, the list fantasy enthusiasts come up with each season are replete with these 25 to 35 players.  If you want to extend the metaphor further, one of 64 players will repeat their first or second half performance six consecutive campaigns.  So, I would even contend that if a player displayed a trend for six or even seven years, it fell within the realm of statistically anticipated outcomes.

The thing is, this sort of analysis is done on players who fared better the second half of LAST season, let alone two or three seasons.  If the analysis is spotty over multiple years, it is certainly suspect based on three months of data.  Again, I am not contending such a player does not exist.  There very well may be players that for one reason or another take a few months to get it going or peter out at the end.  All I am saying is it is not sage to look at what Gordon Beckham or Stephen Drew did the second half of last season and target them now, just as it would be a bad idea to get rid of Dan Haren because he always collapses in the second half.

A year or so ago, I made this point in the forums at our friends at Baseball HQ and a couple of guys much smarter than me in this area had their interest piqued and did some of their own analysis.  The forum is private so I cannot share every intimate detail, but using Bayesian probability analysis (Google it, I had to),  they concluded that for at least an individual season, some first and second half splits feel outside of the expected range of performance level.  The player studied was Adam LaRoche, long considered a second half monster.  The study did not perfectly address my specific hypothesis, but it was enlightening in that for at least one season, it could be strongly argued that LaRoche was statistically better in the second half and it was not just a case of skills not translating into results, which is so often the case in these instances.

I will conclude this discussion by doing something I often frown upon and deem hack analysis, and that is providing selected anecdotal examples to illustrate my point.  The difference is others cite a couple of examples as proof of their argument.  I only want to highlight some rather well known players as a means to help convince those not believing the argument that I at least could be correct, as well as point out how some of this due to perception and not reality in terms of skills not wavering, but rather surface stats not being reflective of said skills.

The first player that piqued my personal interest in this realm was Ichiro Suzuki.  Those of you that have played this game for several seasons might recall that when he first came over to the States, Ichiro enjoyed better first halves, thus the smarts always advised getting rid of him at the All Star break or thereabouts.  Here are his first half and second half numbers, using March to June and July to Oct as the cutoffs.

2001

HR

R

RBI

SB

AVG

1H

3

70

36

27

0.349

2H

5

57

33

29

0.350

2002

HR

R

RBI

SB

AVG

1H

2

62

28

21

0.359

2H

6

49

23

10

0.286

2003

HR

R

RBI

SB

AVG

1H

7

59

26

21

0.340

2H

6

52

36

13

0.284

2004

HR

R

RBI

SB

AVG

1H

3

39

29

19

0.315

2H

5

62

31

17

0.423

2005

HR

R

RBI

SB

AVG

1H

6

51

27

18

0.294

2H

9

60

41

15

0.312

2006

HR

R

RBI

SB

AVG

1H

4

61

27

25

0.350

2H

5

49

22

20

0.295

2007

HR

R

RBI

SB

AVG

1H

5

56

39

23

0.368

2H

1

55

29

14

0.336

2008

HR

R

RBI

SB

AVG

1H

3

57

21

33

0.293

2H

3

46

21

10

0.328

2009

HR

R

RBI

SB

AVG

1H

6

38

18

16

0.373

2H

5

50

28

10

0.333

2010

HR

R

RBI

SB

AVG

1H

3

31

24

21

0.333

2H

3

43

19

21

0.299

 

So in his rookie campaign, Ichiro did not display any difference.  But in his second and third seasons, he indeed had markedly better first halves.  I distinctly recall the pundits suggesting he be dealt before the crash and burn in 2004.  Why you might ask?  Simple – I looked at his first half and determined he was snake-bit and was more than willing to take advantage of others hastiness and acquired him everywhere I could, and 2004 was a very good year for me.  Keep in mind, BABIP had yet to become a household acronym.  My point is, I was more focused on what was happening in 2004, and not at all what transpired the latter part of the two previous seasons.  I felt a low BABIP with a still-stellar contact rate was a more reliable indicator of future performance, in this of the improved variety than the fact Ichiro struggled the second half of ’02 and ’03.

The next guy that got my dander up when he was constantly called a second half pitcher was Johan Santana.  What bothered me was his skills remained consistent one half to the next, but his surface stats, most notably ERA happened to be better for a few second halves.  My argument at the time was it is not a sure thing that if you acquire Santana at the break, your ERA and WHIP would benefit.  Let’s take a look at some numbers:

2004

ERA

WHIP

K/9

BB/9

HR/9

BABIP

1H

4.3782

1.1959

9.12

2.28

1.46

0.297

2H

1.2526

0.7114

11.48

2.02

0.56

0.208

2005

ERA

WHIP

K/9

BB/9

HR/9

BABIP

1H

3.7768

0.9732

10.53

1.69

1.04

0.280

2H

2.0308

0.9694

8.05

1.81

0.68

0.253

2006

ERA

WHIP

K/9

BB/9

HR/9

BABIP

1H

2.586

0.9634

9.43

1.52

0.91

0.274

2H

2.9654

1.0318

9.44

2.11

0.94

0.272

2007

ERA

WHIP

K/9

BB/9

HR/9

BABIP

1H

2.7632

1.0439

9.47

2.21

1.26

0.267

2H

3.9429

1.1048

9.86

2.06

1.46

0.283

2008

ERA

WHIP

K/9

BB/9

HR/9

BABIP

1H

3.0087

1.2228

8.16

2.53

1.11

0.292

2H

2.0885

1.0774

7.68

2.31

0.67

0.265

 

In 2004, Santana’s first year as a full-time starter, he had a markedly batter second half.  His skills were improved across the board after June.  However, there was also some good fortune involved as his BABIP was quite lucky, leading to more opportunities to pitch from the more comfortable wind-up which may have assisted in the better peripherals.

In 2005, the southpaw’s ERA was better in the second half, but his skills were actually better in the first half, at least in terms of strikeouts and walks.  What improved was he kept the ball in the yard post break.  While this could be part skill, it is also part good fortune.  But, since this was now two straight season of a better ERA in the second half, Santana was labeled as someone to go get for the second half.

But alas, look what happened in 2006.  He was the basically the same pitcher both halves, though walking a couple more hitters leading to a slightly elevated ERA and WHIP.  The key is he did not have a BETTER second half as many that season anticipated.   Knowing many would want to potentially overpay for Santana after the break, I drafted him in a couple of trading leagues and indeed got a king’s ransom for him later.  I also had a pretty good 2006.

Real quickly, in 2007, Santana had a much better ERA in the first half, but the difference in skills was not sufficient to account for the disparity, he was a bit unlucky the second half.  Then is 2008, his second half looked better but was actually just a tad luckier.

The bottom line is these were two famous examples of the herd feeling a player’s second half fate could be anticipated based a two year trend.  But that is all it was, a trend, not a pattern.  If someone in your league is willing to overpay for your Mark Teixeira because he is a second half stud, oblige them.  If Dan Haren’s owner is looking to rid their staff of the impending struggles, help ease their mind and open your arms to the Angel’s ace.  You will not regret it.  Well, at least you shouldn’t anyway.

Always remember, never forget, never say always or never.  Shakespeare?  Whitman?  Longfellow?  Hemingway?  No, this is a Zola original and I do not mean Emile.  This is one of the tag lines I use in my forum signature and the message is simple: when it comes to fantasy baseball, there is no always or never.  Every decision is contextual.  It is a mistake to approach decisions myopically.  Granted, there is what many would deem conventional wisdom, but sometimes non-conventional is the way to go.  The bottom line is when managing your fantasy squad, there is no always or never.  The correct decision is that which best aids your chances of winning.  Today I will review some adages that fall under the mantra of conventional advice and elucidate why going against the grain could be beneficial.

NEVER TRADE HITTING FOR PITCHING

Huh?  Never?  Even if your hitting is solid and your staff is weak?  This is perhaps the advice that is presently sitting atop my fecal list and I am hearing and reading it more and more.  The primary reason offered for never dealing sticks for arms is there are always acceptable pitchers available on the waiver wire.  Why deal offense when you can pick up a decent starter from your free agent pool?  The reason goes back to what I was harping on this spring and that is value is relative.  Pitching in general is better than in previous seasons so the rotisserie totals are improved.  The so-called decent waiver wire fodder is not of sufficient quality to make a dent when the totals you need to catch are better than in previous seasons.  In most leagues, between the evolution of pitching analysis and the proliferation of information, most potential impact pitchers are already residing on a team’s reserve or farm roster.  While in a vacuum, the quality of what is left is “decent”, relatively speaking, it is not going to get the job done as well as a trade to acquire a stud difference maker.  The evaluation is roster pre-trade as compared to post-trade.  If dealing hitting for pitching nets you positive points, then buck (yes, I mean buck) conventional wisdom and go for it.

ALWAYS ACQUIRE THE BEST PLAYER IN A TRADE

I have discussed this one recently, so I won’t dwell on it, but the principle is just like above: roster before versus roster after.  You cannot look at the value of the players in the deal, but rather focus on the construct and points potential of your squad if you do the deal and if you don’t.  This entails factoring in the players you use to replace those being dealt, assuming the trade itself does not take care of this.  Often, you have a player returning from the disabled list, promoted from the Minors or the recipient of a role change that increases their worth.  If the best way to work this player into your active lineup is to deal away the best player, so be it – roster before versus roster after.   If the best player in the deal helps you in categories where you can afford to lose stats without losing points and the acquired players provide stats in categories you can gain points, do the deal, which segues to the following.

ALWAYS TRADE FROM STRENGTH TO IMPROVE WEAKNESS

The problem here is not so much the concept, but the wording.  The proper way to approach this is to deal from a category in which you can lose few points to improve categories where you can gain more points.  The idea being this may not always involve dealing from a category you are faring well in to improve where you are not faring so well.  The key is to look at the distribution of points within your specific league.  Granted, it may be early to comfortably make this sort of evaluation, but in some league the gaps are already such that you know it is going to be hard to gain points, especially in the non-correlated like steals and saves.

NEVER TRADE FOR AN INJURED PLAYER

Okay, this is as close to a “never” as there is for me.  In most instances, no matter how attractive the injured player might be, I am extremely reticent to deal for someone on the disabled list.  I have seen too many examples of setbacks.  There are two exceptions.  The first is rather obvious and that is it is extremely apparent the player is healthy and will be activated as targeted.  The second is if I am so desperate, that the only way I can compete is for the injured player to come back and perform at or above their usual level.   An example may be David Wright.  Say someone wants my Placido Polanco for Wright.  Unless I am convinced I am not going to win with Polanco, I will hold onto him and pass on Wright.  If I am going nowhere and need the potential Wright provides, I will roll the dice.

 

Today we are going to take a look at the All-Value team based on first half performance.  What I did was take the National Fantasy Baseball Championship ADP and assign dollar values per draft spot based on history.  I opted to use the NFBC ADP as opposed to our pre-season projections as a “wisdom of the crowd” exercise.  You will not find a sharper group of drafters anywhere and the sample is sufficient to weed out those using odd strategies that could skew an ADP.  I kept the analysis simple, just calculating the amount the players earned over what was expected based on their draft spot.  All reserves were assigned an expected value of $0.

While it is interesting, not to mention fun to draw conclusions from the results to aid in future drafts, it must be noted that we are only halfway through the season, the trends may change, not to mention there is no guarantee next year’s player pool acts in the same manner as 2011.  That said, there are some trends I am going to keep my eye on with the hope it gives me an edge come next spring.

Here is your FIRST TEAM ALL-PROFIT FIRST HALF SQUAD:

Player

POS

ADP

Actual

Expected

Profit

Asdrubal Cabrera

SS

251.45

$30

$5

$25

Curtis Granderson

OF

104.81

$40

$15

$25

Lance Berkman

1B

250.74

$29

$5

$24

Matt Kemp

OF

19.8

$49

$28

$21

James Shields

SP

200.34

$28

$8

$20

David Ortiz

UT

177.54

$27

$9

$18

Michael Morse

OF

275.52

$21

$4

$17

Alex Gordon

OF

277.77

$21

$4

$17

Jhonny Peralta

MI

247.18

$22

$5

$17

Carlos Beltran

OF

225.63

$22

$7

$16

Jose Bautista

3B

31.52

$39

$24

$15

Paul Konerko

CI

72.07

$33

$19

$15

Michael Pineda

SP

264.31

$19

$4

$15

Justin Verlander

SP

47.37

$36

$22

$15

Danny Espinosa

2B

236.37

$20

$6

$14

Jair Jurrjens

SP

279.9

$17

$4

$13

Jered Weaver

SP

60.28

$31

$20

$11

Miguel Olivo

C

288.93

$14

$3

$11

Anibal Sanchez

SP

250.21

$16

$5

$11

Josh Beckett

SP

166.78

$20

$10

$10

Kyle Farnsworth

CL

314.09

$11

$2

$9

Joel Hanrahan

CL

180.45

$17

$9

$8

Russell Martin

C

253.25

$13

$5

$8

 

And your SECOND TEAM ALL-PROFIT FIRST HALF SQUAD:

Player

POS

ADP

Actual

Expected

Profit

Michael Bourn

OF

132.98

$28

$13

$15

Johnny Damon

OF

310.98

$17

$2

$15

Ryan Ludwick

OF

315.46

$15

$1

$14

Jose Reyes

SS

25.79

$40

$27

$14

Seth Smith

OF

299.08

$16

$2

$14

Erick Aybar

MI

277.18

$17

$4

$13

Jacoby Ellsbury

OF

42.2

$34

$22

$12

Adam Lind

CI

152.7

$23

$11

$12

Gaby Sanchez

1B

180.51

$21

$9

$12

Placido Polanco

3B

316.28

$12

$1

$11

Yunel Escobar

UT

253.98

$16

$5

$11

Ty Wigginton

2B

279.5

$13

$4

$9

Ian Kennedy

SP

198.92

$17

$8

$9

Ricky Romero

SP

188.17

$16

$8

$8

Scott Baker

SP

259.91

$12

$4

$8

Johnny Cueto

SP

275.02

$12

$4

$8

Ryan Madson

CL

310.99

$10

$2

$8

Craig Kimbrel

CL

163.02

$18

$10

$8

Paul Maholm

SP

578.76

$7

$0

$7

Cole Hamels

SP

57.75

$27

$20

$7

Tim Stauffer

SP

274.6

$10

$4

$6

J.P. Arencibia

C

251.37

$11

$5

$6

Jason Varitek

C

484.55

$5

$0

$5

 

With the caveat that the following are presently observations and do not yet have any tangible application to game theory, here are some quick thoughts:

1.  I am pleased by the fact that there are not as many pitchers at the upper end of each profit list.  One of the dictums most preach is value pitching always emerges.  At least through the first half of the season, my preseason suggestion that as a populace, we are getting better at valuing pitching may have legs.  Though, we do need to keep in mind the specific populace used here is the NFBC drafter, but, so far, so good.  It will be interesting to determine at season’s end if this pattern still holds.

2.  It is curious that there are no catchers that are significantly outperforming their expectations.  I’m not sure yet how to apply this, but it is worth noting.

3.  Something not shown form the above data is the vast majority of the next group of high profit players are outfielders.  This lends credence to notion of leaving a couple of outfield spots available to be considered fungible, in search of one or two of these value players.

We will broach this again at season’s end.  Good luck to everyone, here is hoping you have a bunch of top second half profit earners on your squad(s)!  Later this week, we will take a look at those on the opposite end of the spectrum, those earning the most negative value the first three months.

The title of this column, Chance Favors the Prepared Mind, was named to represent my philosophy when playing this game.  Last week’s discussion served to reinforce that philosophy.  In short, my belief is determining the highest percentage play and managing my squad accordingly.  Of course this implies I am capably identifying the highest percentage play, which is a concept up for debate.  But, that is a story for another day.

Lately, I have been really thinking about what has become commonplace and conventional advice with respect to in-season roster management.  I am not so sure the masses are doing the right thing.  I am referring to benching or reserving struggling players until they display signs of breaking out of their slump.  On message forums I read frustrated owners say they are reserving their scuffling player as well as reading and hearing my fantasy brethren advise those seeking counsel to go down that path.  Again, I am not convinced this is the sage way to go.

Intuitively, it makes sense.  Keeping a slumping player on your active roster means you are accruing some hurtful stats.  But the flip-side is also true.  Assuming the player indeed turns it around, they do so while on your reserve, be it a hitter or a pitcher.

Here is my theory, with the emphasis on theory.  I intend on putting this on my Toddy-do list for the off-season so I am better prepared to manage my squads in season next year.  At the heart of my philosophy is by season’s end, water reaches its intended level.  In other words, a player’s stats will be as projected, within a reasonable margin of error.  There will be some good weeks and some bad weeks.  But benching a player until they get hot means you are going to miss out on the stats that are good enough to get them back in your lineup.  The question is, do you also miss out on enough bad stats previous to the turnaround to render the benching a wise decision, or do you end up missing out on positive production, so ultimately, even though the player indeed produced as expected, the contributions you realize are a bit less than expected?

I should point out that I am not referring to the fringe or what I like to call fungible players.  My style is to always dedicate some roster spots to fringe players and I will use matchups to decide who plays and who sits.  I am referring to those players I intended to pick and stick, only taking them out if they are hurt.  It should also be noted that the decision to bench is also quite league contextual and depends on what you have to use instead.

By means of example, the sort of hitter I am talking about is Alexis Rios, someone taken pretty early in drafts or someone that cost a good amount in an auction while an example of such a pitcher would be Ricky Nolasco, a guy whose skills appear intact but the results are lacking.  Actually, that gives me an idea.  While I prefer not to restrict analysis to a couple of anecdotal examples, let us do the following.  Let us pretend than we own Rios and Nolasco and decided to bench them this week and let us track their performance over the coming weeks until we get to a point we are comfortable putting them back in our hypothetical lineup.  We will then calculate the total of their respective stats that were lost and compare that to reasonable free agents that are likely available.  For kicks, let us pretend we are inserting Roger Bernadina into our hitting and Andrew Miller into our pitching.  The results are strictly for entertainment purposes only as conclusions cannot be made from isolated scenarios such as these.  Though, by adding some names, I am doing my editors a favor so now they can better select a photo to accompany the column.

Anyway, as mentioned, I intend on looking at ample instances to in fact draw significant conclusions in the off-season.   But in the meantime, I do need to manage my squads.  Long time readers know I am a big fan of using strikeouts and walks for hitters and pitchers to facilitate these types of decisions.  Based on the hypothesis above, I am inclined to leave my struggling hitters active unless they are striking out at an excessive rate if I am blessed with a reasonable replacement.  Similarly, I will start my pitchers when I normally would start then unless their peripherals from recent games are really poor.  I am not so concerned about hits and homers, but if a pitcher is walking a bunch of guys and not fanning many, I may sit him if he is on the road.  My thinking is as outlined above.  By the end of the season, I am going to get what I paid for.  And if I am not confident they will attain their numbers by the end of the season, they are not long for my roster, assuming I can find someone better.  That is, I would rather find a replacement than try to time their positive production.

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