Tagged: Tim Lincecum

Predicting pitchers’ walks using xBB%

The other day, I discussed predicting pitchers’ strikeout rates using xK%. I will conduct the same exercise today in regard to predicting walks. Using my best intuition, I want to see how well a pitcher’s walk rate (BB%) actually correlates with what his walk rate should be (expected BB%, henceforth “xBB%”). Similarly to xK%, I used my intuition to best identify reliable indicators of a pitcher’s true walk rate using readily available data.

An xBB% metric, like xK%, would not only if a pitcher perennially over-performs (or under-performs) his walk rate but also if he happened to do so on a given year. This article will conclude by looking at how the difference in actual and expected walk rates (BB – xBB%) varied between 2014 and career numbers, lending some insight into the (un)luckiness of each pitcher.

Courtesy of FanGraphs, I constructed another set of pitching data spanning 2010 through 2014. This time, I focused primarily on what I thought would correlate with walk rate: inability to pitch in the zone and inability to incur swings on pitches out of the zone. I also throw in first-pitch strike rate: I predict that counts that start with a ball are more likely to end in a walk than those that start with a strike. Because FanGraphs’ data measures ability rather than inability — “Zone%” measures how often a pitcher hits the zone; “O-Swing%” measures how often batters swing at pitches out of the zone; “F-Strike%” measures the rate of first-pitch strikes — each variable should have a negative coefficient attached to it.

I specify a handful of variations before deciding on a final version. Instead of using split-season data (that is, each pitcher’s individual seasons from 2010 to 2014) for qualified pitchers, I use aggregated statistics because the results better fit the data by a sizable margin. This surprised me because there were about half as many observations, but it’s also not surprising because each observation is, itself, a larger sample size than before.

At one point, I tried creating my own variable: looks (non-swings) at pitches out of the zone. I created a variable by finding the percentage of pitches out of the zone (1 – Zone%) and multiplied it by how often a batter refused to swing at them (1 – O-Swing%). This version of the model predicted a nice fit, but it was slightly worse than leaving the variables separated. Also, I ran separate-but-equal regressions for PITCHf/x data and FanGraphs’ own data. The PITCHf/x data appeared to be slightly more accurate, so I proceeded using them.

The graph plots actual walk rates versus expected walk rates. The regression yielded the following equation:

xBB% = .3766176 – .2103522*O-Swing%(pfx) – .1105723*Zone%(pfx) – .3062822*F-Strike%
R-squared = .6433

Again, R-squared indicates how well the model fits the data. An R-squared of .64 is not as exciting as the R-squared I got for xK%; it means the model predicts about 64 percent of the fit, and 36 percent is explained by things I haven’t included in the model. Certainly, more variables could help explain xBB%. I am already considering combining FanGraphs’ PITCHf/x data with some of Baseball Reference‘s data, which does a great job of keeping track of the number of 3-0 counts, four-pitch walks and so on.

And again, for the reader to use the equation above to his or her benefit, one would plug in the appropriate values for a player in a given season or time frame and determine his xBB%. Then one could compare the xBB% to single-season or career BB% to derive some kind of meaningful results. And (one more) again, I have already taken the liberty of doing this for you.

Instead of including every pitcher from the sample, I narrowed it down to only pitchers with at least three years’ worth of data in order to yield some kind of statistically significant results. (Note: a three-year sample is a small sample, but three individual samples of 160+ innings is large enough to produce some arguably robust results.) “Avg BB% – xBB%” (or “diff%”) takes the average of a pitcher’s difference between actual and expected walk rates from 2010 to 2014. It indicates how well (or poorly) he performs compared to his xBB%: the lower a number, the better. This time, I included “t-score”, which measures how reliable diff% is. The key value here is 1.96; anything greater than that means his diff% is reliable. (1.00 to 1.96 is somewhat reliable; anything less than 1.00 is very unreliable.) Again, this is slightly problematic because there are five observations (years) at most, but it’s the best and simplest usable indicator of simplicity.

Thus, Mark Buehrle, Mike Leake, Hiroki Kuroda, Doug Fister, Tim Hudson, Zack Greinke, Dan Haren and Bartolo Colon can all reasonably be expected to consistently out-perform their xBB% in any given year. Likewise, Aaron Harang, Colby Lewis, Ervin Santana and Mat Latos can all reasonably be expected to under-perform their xBB%. For everyone else, their diff% values don’t mean a whole lot. For example, R.A. Dickey‘s diff% of +0.03% doesn’t mean he’s more likely than someone else to pitch exactly as good as his xBB% predicts him to; in fact, his standard deviation (StdDev) of 0.93% indicates he’s less likely than just about anyone to do so. (What it really means is there is only a two-thirds chance his diff% will be between -0.90% and +0.96%.)

As with xK%, I compiled a list of fantasy-relevant starters with only two years’ worth of data that see sizable fluctuations between 2013 and 2014. Their data, at this point, is impossible (nay, ill-advised) to interpret now, but it is worth monitoring.

Name: [2013 diff%, 2014 diff%]

Miller is an interesting case: he was atrociously bad about gifting free passes in 2014, but his diff% was only marginally worse than it was in 2013. It’s possible that he was a smart buy-low for the braves — but it’s also possible that Miller not only perennially under-performs his xBB% but is also trending in the wrong direction.

Here are fantasy-relevant players with a) only 2014 data, and b) outlier diff% values:

I’m not gonna lie, I have no idea why Cobb, Corey Kluber and others show up as only having one year of data when they have two in the xK% dataset. This is something I noticed now. Their exclusion doesn’t fundamentally change the model’s fit whatsoever because it did not rely on split-season data; I’m just curious why it didn’t show up in FanGraphs’ leaderboards. Oh well.

Implications: Richards and Roark perhaps over-performed. Meanwhile, it’s possible that Odorizzi, Ross  and Ventura will improve (or regress) compared to last year. I’m excited about all of that. Richards will probably be pretty over-valued on draft day.

Implications of spring training injuries and news

We’re only a couple of days in and teams are already crying “man down!”

The Seattle Mariners’ No. 2 starter Hisashi Iwakuma strained his finger on the first day of spring training, sidelining him for four to six weeks. Considering spring training is a time for conditioning and preparing for the season (duh), Iwakuma fans and owners can only hope he will be participating in workouts with the exception of throwing to keep pace. Still, that could be legitimate four to six weeks of the season we could miss of him, even if he is healthy by Opening Day, which he is expected to be.

The New York Yankees’ ace CC Sabathia has allegedly lost more weight but, instead of simply slimming down, has added more muscle. He allegedly felt weak last year after committing to a lifestyle change that saw him lose 35-or-so pounds. It’s an interesting situation; I keep Sabathia ranked around 40th of starting pitchers, but I’ll be tracking his velocity through the spring, if possible. If he’s got some of it back, it could boost his stock. It was only two years ago that Tim Lincecum halted his routine of fast food binges and started eating healthily — right before he had the worst season of his career, and lost mph and life on his fastball. Coincidence?

Also, the Cincinnati Reds’ ace Mat Latos had surgery on his knee to clean up some stuff going on down there. (Pretty scientific, right?) It’s supposed to be minor — he’ll be up and running in 10 days — but there’s always a chance of complications, even if the probability is slim. And, like Iwakuma, one has to hope the lost time doesn’t affect his Opening Day start.

Cy Young winner Justin Verlander says he feels fine and will be ready for Opening Day. It remains to be seen how it will affect his throwing, though. One more bad year and things could start getting ugly.

And American League MVP Miguel Cabrera says he feels stronger after core surgery this offseason. Is that even possible? It could be hot air, but it’s just scary thinking about what kind of season he could have feeling perfectly healthy — and wondering how much his woes last year plagued him before they became very obvious in the latter third of the season.

Bonus coverage: Is it easy to dismiss Trevor Bauer after his rough-and-tumble stay in the bigs so far? Yes. And is it easy to dismiss the PR machine churning in Cleveland trying to make him look like he’s not a lost cause? Yes. But! Let us consider one thing: Mickey Callaway did something magical last year when he revived the careers of both Ubaldo Jimenez and Scott Kazmir. Is it out of the question that he can do the same for the third overall pick of the 2011 draft?

As I always say, “keep your eye on so-and-so during spring training”… But seriously, if Bauer is walking fewer than 4 BB/9 in his first few starts of the season, he will have my attention.

Six pitchers I’m not targeting in drafts

As much as it feels good to correctly bet on a bounceback, it sucks harder to be the guy who loses the coin flip. I looked at my 2012 standard 5×5 rotisserie auction draft and the list is, frankly, hilarious. The top 10 pitchers were:

  1. Clayton Kershaw ($32)
  2. Roy Halladay ($31)
  3. Justin Verlander ($26)
  4. Felix Hernandez ($26)
  5. Tim Lincecum ($24)
  6. Jered Weaver ($24)
  7. Cliff Lee ($23)
  8. Dan Haren ($21)
  9. Cole Hamels ($19)
  10. CC Sabathia ($19)

Wow. That was only two years ago. Half those names have fallen from grace — more than half if you’re in the camp that think last year was not an anomaly for Verlander and that we’ve reached the beginning of the end with him. It’s truly hard to believe that anyone thought Halladay would be the second-best pitcher in the MLB in 2012 after the numbers he put up, but it just goes to show how suddenly a pitcher’s decline can sneak up on everyone.

Humorously enough, three of the pitchers in that top 10 make my forthcoming list of pitchers who I will not be targeting in drafts. This can also be viewed as a list of the largest differences between ESPN’s and my rankings.

Justin VerlanderESPN rank: 14, My rank: 25
I have more faith in his strikeout rate, but ESPN has more faith in his overall effectiveness. Truth is, he didn’t suffer an abnormally high BAbip or anything like that. He was simply more hittable and, honestly, ESPN’s projection doesn’t make a lot of sense when you consider that fewer strikeouts should lead to a higher probability he will give up a hit. Regardless of how you feel about him, it’s the offseason surgery that freaks me out. Does that not freak YOU out? It came out of nowhere, and there are rumors he may not even be ready for Opening Day. Toss in the fact that he has a pretty rigorous offseason routine that, for the first time, he won’t be able to stick to, and you have a guy that may not only start the season but also be out of shape, relative to his standards. Unless I get him as low as 30th, he’s not worth the risk.

Shelby Miller | ESPN rank: 26, My rank: 48
This is not a testament to Miller’s abilities — he’s a very good pitcher. This time, ESPN believes more in the strikeout rate; my research leads me to bet against it, although I’m sure he has the capability to improve. The most important aspect of his game this year will be how deeply he pitches into games. I’m not banking on 200 innings, let’s put it that way. I simply believe he will be overvalued on draft day, especially if ESPN thinks he will be better than Gerrit Cole or Alex Cobb. Even if Cole doesn’t ramp up the strikeouts, I still can’t get behind them on this one (Cole struck out 10 batters per nine innings over his handful of starts and was an absolute beast. He gasses 100 mph). Miller is o-ver-ra-ted. Case closed.

Hyun-jin Ryu | ESPN rank: 31, My rank: 50
I actually think he will perform better than ESPN thinks. I also think ESPN simply underrates a lot of players. They have an audience to please, and I think intuition prevails sometimes, even if it’s wrong. Ryu is good but not elite; he pitches more to contact but keeps the ball on the ground. With that said, the strikeout rate suffers, so he’s not really a guy I want on my team. However, he’ll get wins, and that’s great. But we all knows wins are unpredictable. Ask 2012 Cliff Lee and 2013 Cole Hamels. (Or maybe just don’t pitch for the Phillies next time.) Anyway, again, another case of overrating in my opinion.

Jon Lester | ESPN rank: 37, My rank: 56
With so much pitching depth, there’s no reason to tolerate a career 1.30 WHIP and a pedestrian K/9 rate since 2012 just to bank on wins. It only takes one bad year.

CC Sabathia | ESPN rank: 39, My rank: 41
At least ESPN and I are on the same page on this one. Still, what if it gets worse? I think 41st is a neutral projection, and with Hiroki Kuroda and Tony Cingrani following right behind, there are clearly other worthy commodities for which you can pass up Sabathia. Also, don’t forget that these rankings don’t tell you exactly how closely players are ranked together. Players within five slots or so of one another are practically interchangeable.

Dan Haren | ESPN rank: 44, My rank: 73
Let me make my official declaration: Dan Haren’s strikeout rate is NOT back — I repeat, NOT back! ESPN only sees a slight regression, but I dug deeper into PITCHf/x data and basically revealed Haren’s strikeout rate in 2013 was anomalous. I truly think he is more likely to record fewer than seven strikeouts per nine (aka 6.9 K/9) than 7.7 K/9 as expected by ESPN. Be warned, friends. The Dodgers will make his win column tolerable, but only if he pitches somewhat respectably — and I don’t know if he’s capable of doing that. As I’ve said a hundred times already, there’s simply too much volatility here.

Honorable Mentions:
Julio Teheran – He’s good, but I’d rather another owner jump the gun on him (which I can almost guarantee will happen) and pass up on better talent for him.
Jeff Samardzija – Serious question: has he ever won more than nine games? (Also, not coincidentally, a rhetorical question.)
Zack Wheeler – ESPN is really bullish on him. Maybe I’ll be the guy who misses the breakout year, but he finished 2013 with a 4.1 BB/9. He walked 5+ guys in four starts, and failed to strike out more batters than he walked in five. That’s simply unacceptable, and command does not shore up overnight.

The role of luck in fantasy baseball

I apologize for being that guy that ruins that ooey gooey feeling you get when think about the fantasy league you won last year. As much as you want to think you are a fantasy master — perhaps even a fantasy god — you should acknowledge that you probably benefited from a good deal of luck. Sure, for your sake, I will admit you made a great pick with Max Scherzer in the fifth round. But did you, in all your mastery, predict he would win 21 games?

Don’t say yes. You didn’t. And frankly, you would be crazy to say he’ll do it again.

I focus primarily on pitching in this blog, and let it be known that pitchers are not exempt from luck in the realm of fantasy baseball. If you’re playing in a standard rotisserie league, you probably have a wins category. In a points league, you likely award points for wins.

Wins. Arguably the most arbitrary statistic in baseball. Let’s not have that discussion, though, and instead simply accept the win as it is. The win has the most drastic uncontrollable effect on a fantasy pitcher’s value. (ERA and WHIP experiences similar statistical fluctuations, but at least they aren’t arbitrary.)

I had an idea, but before I proceed, let me interject: if you’re drafting for wins, you’re doing it wrong. But, as I said, you can’t ignore wins.

But let’s say you did, and drafted strictly on talent, or “stuff” (which, here, factors in a pitcher’s durability). How would the top 30 pitchers change? Here’s my “stuff” list, which you can compare with the base projections:

  1. Clayton Kershaw
  2. Adam Wainwright
  3. Felix Hernandez
  4. Max Scherzer
  5. Cliff Lee
  6. Yu Darvish
  7. Chris Sale
  8. Cole Hamels
  9. Jose Fernandez
  10. Madison Bumgarner
  11. Stephen Strasburg
  12. David Price
  13. Justin Verlander
  14. Alex Cobb
  15. Homer Bailey
  16. Mat Latos
  17. Gerrit Cole
  18. Michael Wacha
  19. Anibal Sanchez
  20. James Shields
  21. Danny Salazar
  22. Marco Estrada
  23. A.J. Burnett
  24. Corey Kluber
  25. Brandon Beachy
  26. Zack Greinke
  27. Matt Cain
  28. Sonny Gray
  29. Hisashi Iwakuma
  30. Gio Gonzalez

Here are the five players with the biggest positive change and a breakdown of each:

  1. Brandon Beachy, up 23 spots
    His injury history has weakened his wins column projection. Consequently, the number of innings Beachy is expected to throw is significantly less than a full season. But if he managed to stay healthy for the full year (say, 200 innings)? He’s a top-1o pick based on pure stuff. If you draft with the philosophy that you can always find a viable replacement on waivers, Beachy could be your big sleeper.
  2. Marco Estrada, up 22 spots
    Estrada’s diminished expected wins is more a function of his terrible team than ability. Estrada has underperformed the past two years, Ricky Nolasco style, but if he can pull it together, he’s a top-30 pitcher based on “stuff.” And hey, maybe he can luck into some extra wins. However, if he can’t pull it together — Ricky Nolasco style — he’ll be relegated to fringe starter.
  3. Danny Salazar, up 9 spots
    Salazar has immense potential. His injury history led the Indians to cap his per-game pitch count last year, and that has been factored into his projection. But if he’s a full-time, 200-inning starter? He’s a top-25 starter with top-15 upside. Again, this is in terms of “stuff”. But is Ivan Nova better than Felix Hernandez because he can magically win more games? Of course not. Among a slew of young studs, including Jose Fernandez, Shelby Miller, Michael Wacha and so on, Salazar is a diamond in the rough.
  4. A.J. Burnett, up 8 spots
    His projection is already plenty good. But you saw how many games he won in 2013. Anything can happen.
  5. Corey Kluber, up 8 spots
    Most people were probably scratching their heads when they saw Kluber’s name listed above. Frankly, I’m in love with him, and it’s because he’s a stud with a great K/BB ratio. I understand why someone may be inclined to dismiss it as an aberration, but his swinging strike and contact rates are truly excellent. Even if they regress, he should be a draft-day target.

Here are the three starting pitchers with the biggest negative change.

  1. Anibal Sanchez, down 10 spots
    He’s great, but he also plays for a great team. Call it Max Scherzer syndrome. He carries as big a risk as any other player to pitch great but only win five or six games, as do the next two players.
  2. Hisashi Iwakuma, down 6 spots
  3. Zack Greinke, down 4 spots

Let me be clear that although I created a hypothetical scenario where wins didn’t exist, I don’t advocate for blindly drafting based on “stuff.” It’s important to acknowledge that certain players have a much better chance to win than others. Chris Sale of the Chicago White Sox could win 17 games just as easily as he could win seven. It’s about playing the odds — and unless a pitcher truly pitches terribly, don’t blame the so-called experts for your bad luck. He probably put his money where his mouth is, too, and is suffering along with you.

Here is a more comprehensive list of pitchers ranked by “stuff,” if that’s the way you sculpt your strategy:

  1. Clayton Kershaw
  2. Adam Wainwright
  3. Felix Hernandez
  4. Max Scherzer
  5. Cliff Lee
  6. Yu Darvish
  7. Chris Sale
  8. Cole Hamels
  9. Jose Fernandez
  10. Madison Bumgarner
  11. Stephen Strasburg
  12. David Price
  13. Justin Verlander
  14. Alex Cobb
  15. Homer Bailey
  16. Mat Latos
  17. Gerrit Cole
  18. Michael Wacha
  19. Anibal Sanchez
  20. James Shields
  21. Danny Salazar
  22. Marco Estrada
  23. A.J. Burnett
  24. Corey Kluber
  25. Brandon Beachy
  26. Zack Greinke
  27. Matt Cain
  28. Sonny Gray
  29. Hisashi Iwakuma
  30. Gio Gonzalez
  31. Doug Fister
  32. Jordan Zimmermann
  33. Alex Wood
  34. Kris Medlen
  35. Jeff Samardzija
  36. Mike Minor
  37. Jake Peavy
  38. Kevin Gausman
  39. Tyson Ross
  40. Patrick Corbin
  41. Lance Lynn
  42. Francisco Liriano
  43. Andrew Cashner
  44. Ricky Nolasco
  45. CC Sabathia
  46. Hiroki Kuroda
  47. Tim Lincecum
  48. Tim Hudson
  49. Jered Weaver
  50. Shelby Miller
  51. Clay Buchholz
  52. Tony Cingrani
  53. Matt Garza
  54. John Lackey
  55. Ubaldo Jimenez
  56. Justin Masterson
  57. Julio Teheran
  58. R.A. Dickey
  59. A.J. Griffin
  60. Hyun-Jin Ryu
  61. Dan Haren
  62. Johnny Cueto
  63. C.J. Wilson
  64. Ian Kennedy
  65. Chris Archer
  66. Kyle Lohse
  67. Scott Kazmir
  68. Carlos Martinez
  69. Jon Lester
  70. Ervin Santana
  71. Jose Quintana
  72. Derek Holland
  73. Garrett Richards
  74. Dan Straily
  75. Tyler Skaggs

Early SP rankings for 2014

I wouldn’t say pitching is deep, but I’m surprised by the pitchers who didn’t make my top 60.

Note: I have deemed players highlighted in pink undervalued and worthy of re-rank. Do not be alarmed just yet by what you may perceive to be a low ranking.

2014 STARTING PITCHERS

  1. Clayton Kershaw
  2. Adam Wainwright
  3. Max Scherzer
  4. Yu Darvish
  5. Felix Hernandez
  6. Cliff Lee
  7. Stephen Strasburg
  8. Jose Fernandez
  9. Cole Hamels
  10. Justin Verlander
  11. Anibal Sanchez
  12. Chris Sale
  13. Mat Latos
  14. Madison Bumgarner
  15. Alex Cobb
  16. Homer Bailey
  17. Gerrit Cole
  18. Zack Greinke
  19. David Price
  20. James Shields
  21. Jordan Zimmermann
  22. Michael Wacha
  23. Danny Salazar
  24. Jered Weaver
  25. A.J. Burnett *contingent on if he retires
  26. Kris Medlen
  27. Mike Minor
  28. Jake Peavy
  29. Corey Kluber
  30. Lance Lynn
  31. Matt Cain
  32. Hisashi Iwakuma
  33. CC Sabathia
  34. Gio Gonzalez
  35. Doug Fister
  36. Patrick Corbin
  37. Francisco Liriano
  38. Sonny Gray
  39. Ricky Nolasco
  40. Hiroki Kuroda
  41. Tim Hudson
  42. Marco Estrada
  43. Shelby Miller
  44. Trevor Rosenthal
  45. Tony Cingrani
  46. A.J. Griffin
  47. Brandon Beachy
  48. Tim Lincecum
  49. Clay Buchholz
  50. Ubaldo Jimenez
  51. Alex Wood
  52. Julio Teheran
  53. Tyson Ross
  54. Hyun-jin Ryu
  55. Matt Garza
  56. Andrew Cashner
  57. Johnny Cueto
  58. C.J. Wilson
  59. John Lackey
  60. Justin Masterson
  61. R.A. Dickey
  62. Kevin Gausman
  63. Jon Lester
  64. Dan Haren
  65. Ervin Santana
  66. Derek Holland
  67. Chris Archer
  68. Jeff Samardzija
  69. Bartolo Colon
  70. Ivan Nova
  71. Matt Moore
  72. Ian Kennedy
  73. Dan Straily
  74. Rick Porcello
  75. Jarrod Parker
  76. Carlos Martinez
  77. Jeremy Hellickson
  78. Kyle Lohse
  79. Scott Kazmir
  80. Jason Vargas
  81. Tommy Milone
  82. Wade Miley
  83. Dillon Gee
  84. Brandon Workman
  85. Chris Tillman
  86. Zack Wheeler
  87. Yovani Gallardo
  88. Miguel Gonzalez
  89. Jose Quintana
  90. Garrett Richards
  91. Robbie Erlin
  92. Felix Doubront
  93. Jhoulys Chacin
  94. Jonathon Niese
  95. Chris Capuano
  96. Nick Tepesch
  97. Alexi Ogando
  98. Bronson Arroyo
  99. Travis Wood
  100. Trevor Cahill
  101. Tyler Skaggs
  102. Randall Delgado
  103. Martin Perez
  104. Mike Leake
  105. Carlos Villanueva
  106. Todd Redmond
  107. Brandon Maurer
  108. Tyler Lyons
  109. Ryan Vogelsong
  110. Zach McAllister
  111. Wily Peralta
  112. Brett Oberholtzer
  113. Erik Johnson
  114. Jorge De La Rosa
  115. Paul Maholm
  116. Hector Santiago
  117. Burch Smith
  118. Jeff Locke
  119. Joe Kelly
  120. Jason Hammel
  121. Jake Odorizzi
  122. Danny Hultzen
  123. Anthony Ranaudo
  124. Archie Bradley
  125. Rafael Montero
  126. James Paxton
  127. Taijuan Walker
  128. Yordano Ventura

What’s wrong with CC?

New York Yankees pitcher CC Sabathia was pummeled for a fourth straight game Friday, giving up five earned on 11 hits. He has now allowed 27 runs (22 earned) in his last four starts spanning 19 2/3 innings, pushing his ERA up to a whopping 4.78.

That’s horrifying.

What’s wrong with him? Before coming to any conclusions, let’s look at a variety of metrics and measurements.

  • His FIP is 4.19 and his xFIP 3.61, significantly lower than his ERA. That’s comforting.
  • His BAbip is slightly inflated, at .315.
  • His HR/9 rate has ballooned to 1.41, the first time in his career it is greater than one, and his HR/FB rate is at 14.9 percent (according to FanGraphs), almost 6 percent higher than his career mark. Pair this information with a slightly depressed LOB% and it makes sense why he keeps giving up runs.
  • His K/9 and BB/9 rates are down, but they’re nothing abnormal, as both are better than the marks he put up in 2009 or 2010 when he was in the running for AL Cy Young. Again, comforting.
  • His fastball is down about 1.5 mph… According to FanGraphs’ pitch values, it’s arguably the second-worst fastball in Major League Baseball at -14.7 runs above average, behind only the truly awful Joe Blanton. Uh oh.
  • However, it looks like his fastball was pretty bad last year (at -11.9 runs above average) but still had an admirable year. His slider was much better last year, though.
  • He’s throwing first-pitch strikes at the second-highest rate of his career.
  • Batter contact rates are down inside the zone, but up outside the zone. Weird.
  • His run support has dropped by almost two full runs per game. That doesn’t help his win total, but it also doesn’t affect his ERA.

So… What does it all mean? I don’t know. Honestly. Sabathia’s xFIP indicates he’s running into some bad luck, as does his BAbip, HR/9 and HR/FB rates. But there’s a lot of talk about his declining velocity and his fastball becoming more hittable. If a pitcher is easier to hit, more balls will be put into play and BAbip may increase naturally as the batter is better able to square up the ball. However, none of his other peripherals really indicate anything is wrong. The percentage of pitches inducing contact, swinging strikes, swings in the zone and swings outside the zone fluctuate yearly, and his 2013 numbers are not abnormal. His WHIP is high, but it’s elevated somewhat by his inability to go as deep into games (down from about 7.1 IP per game in 2012 to about 6.6 IP in 2013) and the lofty BAbip.

Ultimately, if your league’s trade deadline hasn’t yet come and gone , I still wouldn’t look at Sabathia as a buy-low candidate. Even if his ratios regress to something more tolerable, his lack of run support will render any improvements meaningless. However, I don’t see why Sabathia shouldn’t bounce back next year. I don’t know if I would rank him as highly as he was in 2013, but I doubt many experts will anyway. And unless his fastball has suddenly failed him a la Tim Lincecum, I see Sabathia returning to form..

One last note: Sabathia’s “pace,” or average time between pitches as measured by FanGraphs, is 22.6, the lowest of his career. Maybe all he needs to do is slow down his game.

Take a breather, CC.