How to Win Your League

You play in a fantasy baseball league.

Your league is not like other leagues.

Sure, there are some common formats: 12-team 5×5 Roto, 10-team head-to-head. But even within that, there are a lot of important variables. How many middle infielders do you have to start? How many bench spots do you have? Do you have to start LF-CF-RF or just a mix of OFs? Do you have to start SP-RP or just any mix of pitchers? Do you use keepers? How many keepers?

By the time you answer these and all possible questions, it is likely that your league is unique, at least in some way from other leagues. And what may seem to be an insignificant difference between two leagues, if you understood it perfectly, would make a difference in choosing one player over another come draft time.

Let’s walk through a simple example. Let’s look at a player who would be most impacted by making a change to this simple league setting: how many teams are in your league?

Let me show you a player who had value in a 14-team league, who lost value in a 12-team league, who may not have been worth owning in a 10-teamer. Let’s assume a 25-man roster, that requires you to start 8 pitchers, and uses 5×5-standard stats.

This year, Jon Jay, STL CF, had 628 Plate Appearances, and also had this 5×5 stat line:

  • R: 75
  • HR: 7
  • RBI: 67
  • SB: 7
  • AVG: .262

In a 14-team league, this stat line added value. In a 12-teamer, it added less value. In a 10-team league, it was not worth owning.

From league to league, Jay’s performance did not change. So what did?

The difference between leagues is their individual replacement levels. Your fantasy league has its own, unique replacement level.

This may be a revolutionary, illuminating idea to you. This may be just another way of saying something you already knew. This may even just be saying something you have already said yourself.

Either way, I think there is a takeaway here. It has to do with what you read and listen to. You may be reading a column or listening to a podcast, and read/hear something like this: ‘I love Will Venable for next year.’ Understand that writer/analyst is speaking to everyone, not to you. They do not understand the uniqueness of your league.

If you would like for me to give you your league’s replacement stat line, I would be glad to do that. I think knowing what it takes to win your specific league can give you a huge advantage over your competitors. Shoot me an email at ayoung@outliarbaseball.com or catch me on Twitter.

A New League

A friend of mine and I are launching a new league.

Here are the specs on it:

12 Teams

  • Three Divisions of Four Teams
  • Six Teams make the Playoffs

Auction

Head-to-Head Categories

Weekly Lineups

7×7 Scoring

  • Runs
  • Total Bases
  • RBI
  • SB
  • OBP
  • Putouts
  • Assists
  • Strikeouts
  • Wins
  • Losses
  • Saves
  • Holds
  • ERA
  • WHIP

25-Man Rosters

  • C
  • 1B
  • 2B
  • 3B
  • SS
  • CI
  • MI
  • LF
  • CF
  • RF
  • 2 OF
  • DH
  • 5 SP
  • 3 RP
  • P
  • 3 Bench

8 Keepers per Team

We have a few spots left. Let me know if you would like to join, on Twitter or at ayoung@outliarbaseball.com

 

I2K Non-Qualified Leaders by Position

My last post looked at qualified I2K leaders by position. Now, I want to look at hitters who were not qualified, but still put up a respectable volume of I2K.

Let’s get right to it. Players are listed with their I2K and I2K+. They are sorted with respect to both performance and volume.

C

  • Evan Gattis, ATL. .269 / 1.31
  • Wilson Ramos, WAS. .278 / 1.33

1B/DH

  • Albert Pujols, LAA. .238 / 1.21

2B

  • None

3B

  • David Wright, NYM. .250 / 1.25

SS

  • Hanley Ramirez, LAD. .494 / 1.99

LF

  • Carlos Gonzalez, COL. .309 / 1.43
  • Raul Ibanez, LAA. .243 / 1.23
  • Khris Davis, MIL. .418 / 1.76

CF

  • None

RF

  • Nelson Cruz, FA. .247 / 1.24
  • Ryan Raburn, CLE. .297 / 1.39

The players on this list averaged 97 games, 340 ABs and .526 SLG, with an I2K+ of 1.42.

Yesterday’s list averaged 147 games, 547 ABs and .507 SLG, with an I2K+ of 1.35.

ISO-Squared per Strikeout

I have invented a new stat that I love. I have done a little internet-googling, and I see no record of this stat out there.

Let me tell you about it.

All hitters have a choice to make. How hard do they want to swing?

The benefit of swinging harder is a guy can hit the ball harder, which is a good thing. The benefit of swinging softer is a guy can make more contact, which is a good thing.

The cost of swinging harder is contact. The cost of swinging softer is power.

So there is a tradeoff, power for contact. Or contact for power.

You could express this, statistically as ISO/K% (ISO/K). For every Strikeout a player collects, how many Extra Bases does he hit for?

The 2013 leader in ISO/K was Edwin Encarnacion, Blue Jays 1B/DH, and occasional 3B. His ISO/K was 2.620. The worst in 2013 was Michael Bourn, Indians OF. His ISO/K came in at 0.422. This is only among qualified hitters, of course.

But this is a flawed stat. Here is why:

Jose Bautista and Nori Aoki had very similar ISO/K in 2013. Bautista’s was 1.503 (38% above league-average); Aoki’s was 1.424 (32% above league average). This stat does not tell the whole story though. Here are their respective ISO and K%.

  • Bautista: .239 ISO / .159 K%
  • Aoki: .084 ISO / .059 K%

Bautista hit for a lot of Power. Aoki never struck out. They did not have similar seasons.

My solution to this is to multiply a player’s ISO/K+ (ISO/K compared to league average) by their ISO. Bautista’s ISO/K+ was 1.38; Aoki’s was 1.32. Multiply that by their ISO, and it looks like this:

  • Bautista: .330 – 48% above league average
  • Aoki: .111 – 17% below league average

I call this stat ISO-Squared per K, or I2K.

The question that has to be asked next is: ‘Is I2K predictive?’

It is. Here is a table of how segments of I2K performed, from a 5×5 perspective, next season. This data is for consecutive, qualified seasons from 2008-2013.

I have included BsR (Fangraph’s Baserunning) to show that players who do not hit well are (necessarily) contributing in other ways.

nR, nHR, nRBI, nAVG represent next season’s stats. All other stats are for year-zero.

I2K+ # Players I2K BSR nR nHR nRBI nAVG
1.33+ 33 0.391 (0.3) 90 31 100 0.292
1.00-1.33 178 0.236 (0.1) 81 24 86 0.274
0.67-1.00 251 0.128 1.4 75 15 67 0.271
-0.67 13 0.042 6.2 83 5 48 0.278
Population 475 0.185 0.9 78 19 76 0.274

Those are pretty robust effects. Some of the strongest I have seen.

I think the reason this stat works is that ISO and K% are true hitter skillsets – conscious choices hitters make. And hitters that can hit for real power without giving up contact are special players whose skills will not erode quickly.

Here are the 2013 I2K leaders by position, listed with their I2K and I2K+.

C

  • Jonathan Lucroy, MIL. .238 / 1.21
  • Yadier Molina, STL. .234 / 1.20

1B/DH

  • Edwin Encarnacion, TOR. .573 / 2.21
  • Chris Davis, BAL. .399 / 1.69
  • David Ortiz, BOS. .395 / 1.68
  • Paul Goldschmidt, ARI. .293 / 1.37
  • Brandon Moss, OAK. .265 / 1.29

2B

  • Robinson Cano, SEA. .296 / 1.38
  • Chase Utley, PHI. .233 / 1.19

3B

  • Miguel Cabrera, DET. .501 / 1.99
  • Adrian Beltre, TEX. .295 / 1.38
  • Josh Donaldson, OAK. .232 / 1.19
  • Evan Longoria, TB. .230 / 1.19

SS

  • Troy Tulowitzki, COL. .296 / 1.38
  • JJ Hardy, BAL. .235 / 1.20
  • Andrelton Simmons, ATL. .235 / 1.20

LF

  • Domonic Brown, PHI. .264 / 1.28
  • Matt Holliday, STL. .239 / 1.21
  • Alfonso Soriano, NYY. .228 / 1.18

CF

  • Mike Trout, LAA. .277 / 1.33
  • Coco Crisp, OAK. ..272 / 1.31
  • Adam Jones, BAL. .230 / 1.19
  • Andrew McCutchen, PIT. .230 / 1.19

RF

  • Jose Bautista, TOR. .330 / 1.48
  • Nate Schierholtz, CHC. .250 / 1.24
  • Carlos Beltran, NYY. .241 / 1.22
  • Jayson Werth, WAS. .237 / 1.21
  • Hunter Pence, SF. .232 / 1.19

 

Platoon Splits in Fantasy Baseball

This offseason, I am going to greater lengths to understand MLB roster construction. This is part of an effort to understand which players will have a chance to shine in 2014. It is also part of why there has been a dearth of posts on this site. I am doing a lot of fantasy baseball research – so much that I have not made time to write.

Platoon splits are incredibly important in real baseball, but are commonly ignored in fantasy. So I dove into it a little. Here is what you need to know about it:

On average, all players deal with platoon splits

To illustrate, here is what a standard platoon split look like:

  • Strong Side: .276/.338/.452
  • Blind Side: .253/.303/.390

When facing a same-handed pitcher, ISO and Walks go down, and Strikeouts go up – performance suffers all around.

Some players deal with extreme platoon splits

Here is what a problematic platoon split looks like:

  • Strong Side: .268/.332/.436
  • Blind Side: .237/.283/.348

You can see that these hitters are slightly worse off to begin with, but their performance suffers more against same-handed pitchers. They reach un-rosterable levels, for MLB and fantasy purposes.

All of this, you probably already knew. Here is something you may not know – how does this affect their fantasy production?

To get into this, we will begin to split out players who struggle against right- and left-handed pitching.

Some players who struggle against one side also struggle against the other side – they are just bad hitters, and have been eliminated from the population for this study.

Here is the performance – for comparison – of 249 players who do not particularly struggle against either side.

  • 111 G, 3.8 PA/G, 49 R, 12 HR, 48 RBI, .261/.327 (AVG/OBP)

Right-Handed Problem

Here is the 2013 fantasy performance of 55 players who have struggled against RHPs.

  • 116 G, 3.5 PA/G, 41 R, 8 HR, 37 RBI, .241/.295 (AVG/OBP)

This group contains the following position counts:

  • C: 5
  • 1B/DH: 1
  • 2B: 9
  • 3B: 7
  • SS: 12
  • OF: 21

Left-Handed Problem

Here is the 2013 fantasy performance of 62 players who have struggled against LHPs.

  • 123 G, 3.8 PA/G, 52 R, 13 HR, 49 RBI, .249/.321 (AVG/OBP)

This group contains the following position counts:

  • C: 8
  • 1B/DH: 19
  • 2B: 4
  • 3B: 4
  • SS: 5
  • OF: 22

You can see that having problems against LHPs is hardly a problem at all. In fact, those 62 players outperformed the ‘no problems’ group in a few categories, most notably in Games Played.

But, when a player has a problem against RHPs, he really has a problem. This is extremely apparent in the positional counts. Players who cannot hit RHPs are much more skilled defenders – 33 skill positions v 21 for the Lefties.

One thing I always try to do is apply any findings to actual players. That said, here is a list of fantasy-level players (by 2012 ADP) who have really struggled against RHPs. They are listed with their triple slash against RHPs from 2011-13.

  • Alcides Escobar, SS, KC .260/.290/.352
  • Ichiro Suzuki, OF, NYY .263/.301/.352
  • Rajai Davis, OF, DET (Did not qualify by ADP – but, you know) .232/.269/.329
  • Matt Wieters, C BAL .225/.289/.382
  • JP Arencibia, C, TEX .207/.257/.395
  • Alexei Ramirez, SS, CHW .271/.307/.378
  • Jose Altuve, 2B, HOU .271/.309/.349
  • Brian Dozier, 2B, MIN (Did not qualify by ADP) .222/.277/.335
  • Ben Revere, OF, WAS .279/.322/.326
  • Juan Pierre, OF, MIA .284/.321/.352
  • Dustin Ackley, OF/2B, SEA .246/.318/.353
  • Zack Cozart, SS, CIN .251/.288/.389
  • Gordon Beckham, 2B, CHW .252/.309/.374
  • Starlin Castro, SS, CHC .276/.310/.401
  • Trevor Plouffe, 3B, MIN .230/.289/.384
  • Dayan Viciedo, OF, CHW .240/.286/.385
  • JJ Hardy, SS, BAL .251/.289/.425
  • Omar Infante, 2B, KC .283/.317/.384
  • Elvis Andrus, SS, TEX .281/.342/.356
  • Mike Moustakas, 3B, KC .252/.304/.404
  • Alex Rios, OF, TEX .263/.301/.419
  • BJ Upton, OF, ATL .233/.299/.412

This is sorted by wOBA v RHPs (by volume). wOBA does not include anything done on the bases, so Andrus’ empty .281/.342 is less empty when you tack on all the steals.

I think the biggest surprise for me was how miserable Matt Wieters is against RHPs. How does he fare against LHPs, you ask? .312/.382/.576. But, the PAs are, as you would expect, heavily slanted in favor of RHPs. In Wieter’s case it is 1,252 against RHPs and 471 against LHPs.

The takeaway here is to be cautioned against a few of these players, especially guys like Wieters, Castro, Rios and Andrus who you might look at for Top 100ish picks. Make sure you discount their value accordingly in drafts and auctions.

How to Win Your League

You play in a fantasy baseball league.

Your league is not like other leagues.

Sure, there are some common formats: 12-team 5×5 Roto, 10-team head-to-head. But even within that, there are a lot of important variables. How many middle infielders do you have to start? How many bench spots do you have? Do you have to start LF-CF-RF or just a mix of OFs? Do you have to start SP-RP or just any mix of pitchers? Do you use keepers? How many keepers?

By the time you answer these and all possible questions, it is likely that your league is unique, at least in some way from other leagues. And what may seem to be an insignificant difference between two leagues, if you understood it perfectly, would make a difference in choosing one player over another come draft time.

Let’s walk through a simple example. Let’s look at a player who would be most impacted by making a change to this simple league setting: how many teams are in your league?

Let me show you a player who had value in a 14-team league, who lost value in a 12-team league, who may not have been worth owning in a 10-teamer. Let’s assume a 25-man roster, that requires you to start 8 pitchers, and uses 5×5-standard stats.

This year, Jon Jay, STL CF, had 628 Plate Appearances, and also had this 5×5 stat line:

  • R: 75
  • HR: 7
  • RBI: 67
  • SB: 7
  • AVG: .262

In a 14-team league, this stat line added value. In a 12-teamer, it added less value. In a 10-team league, it was not worth owning.

From league to league, Jay’s performance did not change. So what did?

The difference between leagues is their individual replacement levels. Your fantasy league has its own, unique replacement level.

This may be a revolutionary, illuminating idea to you. This may be just another way of saying something you already knew. This may even just be saying something you have already said yourself.

Either way, I think there is a takeaway here. It has to do with what you read and listen to. You may be reading a column or listening to a podcast, and read/hear something like this: ‘I love Will Venable for next year.’ Understand that writer/analyst is speaking to everyone, not to you. They do not understand the uniqueness of your league.

If you would like for me to give you your league’s replacement stat line, I would be glad to do that. I think knowing what it takes to win your specific league can give you a huge advantage over your competitors. Shoot me an email at ayoung@outliarbaseball.com or catch me on Twitter.

Defensive Liabilities

I spent the month of October doing two things, regarding baseball.

  1. Enjoying the playoffs
  2. Getting up to speed on defensive stats

Now that the playoffs are over, I want to share some thoughts with you.

Defense is important. It is also less visible and less discussed (and maybe less important) than offense. So how do we approach it?

To put it simply, being good at defense is less important than being bad at defense. Players who can hit only need to be good enough at defense. If they can do that, their teams will probably not need to make any changes.

As we approach the offseason, the hot stove, there will be teams that need to address their defensive liabilities. As fantasy owners,you will probably only notice this if the players affected also have big bats.

With that, here is a list of players with big bats (by wOBA) and tiny gloves (by Range Runs). They are sorted from worst to bad, in terms of defense.

  • David Ortiz, BOS. .400 wOBA, (.300) RngR/9 (SSS – 39 Innings on defense)
  • Darin Ruf, PHI. .354, (.147)
  • Miguel Cabrera, DET. .455, (.138)
  • Shin-Soo Choo, FA. .393, (.107)
  • Dom Brown, PHI. .351, (.104)
  • Michael Cuddyer, COL. .396, (.096)
  • Carlos Beltran, FA. .359, (.088)
  • Daniel Nava, BOS. .366, (.086)
  • Adam Jones, BAL. .350. (.085)
  • Ryan Zimmerman, WAS. .353, (.074)
  • Brandon Moss, OAK. .369, (.065)
  • Aramis Ramirez, MIL. .366, (.062)

It is important to understand a couple of things. Range is unimportant at first base. Most of a first baseman’s defensive value comes from making catches for putouts, not from being rangy. It is even less important at DH. David Ortiz and Brandon Moss are staying put where they are.

This list probably affects position eligibility more than anything else. Free Agent Carlos Beltran will likely cease to be an outfielder. Michael Cuddyer is rumored to move to first base full time. If you read what I read, you probably already knew this.

There are a couple of takeaways from this list.

I always hear how good Jones and Zimmerman are at defense. That may not be true, and a positional change could be in their future.

The Phillies’ outfield needs some help. Ryan Howard’s contract does not expire until after 2016 (the club carries an $23M option for 2017, but come on). First base is not open for either Ruf or Brown. One of these two could lose their job, or be traded.

The Tigers’ probably cannot move Cabrera off third until after Victor Martinez’s contract expires at the end of 2014.

Shin-Soo Choo may not deserve to be an outfielder, and certainly not a center fielder.

Boston could let Napoli walk and slot in or platoon Nava at first base. I would still guess they re-sign Napoli, though.

Aramis Ramirez could play first for Milwaukee before the end of his contract. If they chose to do that, they would need to acquire a third baseman.

I would be interested to hear your thoughts and responses on Twitter.

The Best Pitches of the World Series: Game 1

I have recently fallen in love with a singular pitchF/X stat: z-Contact%. Simply put, z-Contact% is

Contact / [Pitches that were both in the zone and swung at].

I prefer to think of it as: ‘you should be able to hit this pitch, but you can’t.’

Pitchers, of course, want z-Contact% to be low.

Max Scherzer led the league in these types of in-zone swings-and-misses this season, with 202. Justin Verlander was next with 187, followed by RA Dickey at 177.

Among qualified pitchers, Joe Saunders had the least of these, accumulating just 53.

But none of those pitchers pitch for the Red Sox or the Cardinals. What I want to show you are the least-hittable pitches in the World Series, starting with tonight’s Game 1 starters, and the best pitches from both bullpens.

The criteria for these ratings is twofold:

  • The pitch must have a low z-Contact%
  • The pitch must be thrown frequently

For instance, Junichi Tazawa threw a Splitter 17 times this season, or 2% of the time. It had a very low, elite-level z-Contact of 60%. This pitch does not appear on the list due to its infrequency. If it was really a great pitch, Tazawa would throw it more often.

Let’s look at tonight’s starters. Each pitch is listed with its rating, frequency (% of pitches thrown), its z-Contact%, and its velocity. The ratings are on a 0.50-1.50 scale, where 1.00 is average. See that Lester’s Sinker is rated at 1.20, or 20% above average.

Jon Lester, LHP

  • Sinker: 1.20 – 23.4%, 89% zCon, 92-96 mph
  • Cutter: 1.11 – 16.1%, 90% zCon, 89-94 mph
  • Changeup: 1.04 – 12.3%, 82% zCon, 85-89 mph
  • Curveball: 1.01 – 12.0%, 92% zCon, 76-81 mph
  • Four-Seam: 0.97 – 36.2%, 92% zCon, 92-97 mph

You can see that Lester throws his most hitable pitch, the Four-Seam fastball, most often. It is still a good pitch.

Adam Wainwright, RHP

  • Curveball, 1.27 – 27.3%, 88% zCon, 75-80 mph
  • Cutter, 1.05 – 29.8%, 91% zCon, 88-93 mph
  • Four-Seam: 1.04 – 17.2%, 91% zCon, 91-95 mph
  • Sinker: 0.97 – 21.9%, 92% zCon, 91-95 mph
  • Changeup: 0.83 – 3.8%, 93% zCon, 84-88 mph

Neither of these pitchers have a single pitch that they throw more than 36% of the time. Peavy is the only other starter in the World Series who can say that. They both offer a good mix of quality pitches.

This is not news to you, probably.

Here are the best pitches from both bullpens. In the 2013 World Series, there are roughly 59 pitches thrown from 15 bullpen arms. Here are the most exceptional of those. I have notated when they are coming from a left-hander.

  1. Koji Uehara, BOS – Splitter, 1.84 – 48.4%, 65% zCon, 81-85
  2. Trevor Rosenthal, STL – Four-Seam, 1.47 – 87.7%, 79% zCon, 96-101
  3. Randy Choate, L, STL – Slider, 1.44 – 29.8%, 60% zCon, 76-79 mph
  4. Koji Uehara, BOS – Four-Seam, 1.40 – 43.3%, 80% zCon, 89-91 mph
  5. Junichi Tazawa, BOS – Four-Seam, 1.39 – 61.1%, 81% zCon, 93-97 mph
  6. Kevin Siegrist, L, STL – Four-Seam, 1.35 – 64%, 82% zCon, 95-99 mph
  7. Junichi Tazawa, BOS – Two-Seam, 1.35 – 25%, 81% zCon, 88-93 mph

Koji Uehara makes me think velocity is a seriously overstated commodity, and that command and deception are vastly more important. Trevor Rosenthal makes me think that velocity is also very important. Eno Sarris wrote an interesting piece on velocity today; you should read it.

These are the tools at the disposal of Matheny and Farrell this evening. Enjoy the game.