Advanced Stats - Pitching Charts: Tuesday, August 18th
Yesterday was as difficult as envisioned for starting pitching choices. Roughly half of the highly priced pitching options had a tough time last night. We may not have a similarly proportioned number of high priced pitchers tonight and there are a great many (more than usual) that get immediately discarded, but it does look better. Of course, I’m talking about the dominator John Danks. Or maybe it’s Clayton Kershaw and Jacob deGrom. Anyway, at least two of those pitchers are really good, so if you’re still feeling the pain from Cole, Kazmir, or Gray last night, let’s see what we can do to remedy the situation on Tuesday.
Don’t forget to watch for lineups, umpire assignments, and Kevin’s weather report as they are released later in the day, all of which may change the equation and help you decide between two pitchers of otherwise equal value in a pinch.
Most of the stats in these charts are pulled directly from the Fangraphs.com database. If a stat is used that you are not familiar with and want to learn more about, their glossary does a terrific job of explaining all of the advanced stats I use in these charts.
Starting Pitching Main Chart
We’re using Seamheads.com three-year park factors. Home team is in bold. Team Def = UZR/150. L2Yrs is a rolling calendar. Hm/Rd xFIP is since the start of the 2014 season. Opp team offensive stats are wRC+. Combo stats are explained below.
| Pitcher | Team | Team Def | SIERA L2Yrs | IP/GS L2Yrs | GB/FB L2Yrs | Park Run | Hm/Rd xFIP | SIERA L14 | Opp | Opp Hm/Rd | Opp L/R wRC+ | Opp L7 wRC+ | Comb K% | Comb BB% | Comb LD% | Comb HR/FB% | Comb IFFB% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | PHI | -5.4 | 3.79 | 5.84 | 1.43 | 1.01 | 2.91 | 4.43 | TOR | 98 | 107 | 72 | 19.7% | 5.9% | 19.9% | 12.1% | 12.4% |
| Adam Conley | FLA | 4.8 | 4.82 | 4.6 | 1 | 1.07 | 5.14 | 4.58 | MIL | 85 | 68 | 57 | 16.1% | 6.6% | 20.9% | 13.1% | 7.5% |
| Alex Gonzalez | TEX | 3.5 | 5.71 | 6.13 | 1.71 | 1.08 | 5.23 | 6.37 | SEA | 94 | 98 | 139 | 16.0% | 10.8% | 25.1% | 13.5% | 3.6% |
| Anibal Sanchez | DET | 4.9 | 3.67 | 6.19 | 1.18 | 1.05 | 3.61 | 4.42 | CHC | 88 | 92 | 117 | 22.6% | 8.3% | 20.9% | 15.4% | 9.3% |
| CC Sabathia | NYY | -6.6 | 3.75 | 5.95 | 1.52 | 1.02 | 3.12 | 3.8 | MIN | 75 | 94 | 113 | 20.6% | 7.0% | 22.1% | 12.4% | 13.2% |
| Chase Anderson | ARI | 3.5 | 3.99 | 5.64 | 1.24 | 0.91 | 4.09 | 2.86 | PIT | 107 | 100 | 118 | 20.4% | 6.6% | 22.4% | 11.6% | 5.7% |
| Clayton Kershaw | LOS | 2.9 | 2.23 | 7.14 | 1.84 | 0.93 | 2.38 | 2.8 | OAK | 98 | 92 | 94 | 23.3% | 6.1% | 19.0% | 8.8% | 10.2% |
| David Hale | COL | -0.7 | 4.12 | 5.69 | 1.93 | 1.4 | 4.3 | WAS | 93 | 94 | 42 | ||||||
| Edinson Volquez | KAN | 9.3 | 4.23 | 5.95 | 1.51 | 1.02 | 4.08 | 4.43 | CIN | 104 | 91 | 102 | 18.2% | 7.9% | 19.7% | 10.1% | 7.2% |
| Eduardo Rodriguez | BOS | -4 | 4.2 | 5.58 | 1.26 | 1.07 | 4.03 | 4.47 | CLE | 90 | 98 | 101 | 18.2% | 7.8% | 23.2% | 10.9% | 14.0% |
| Felix Doubront | OAK | -7.9 | 4.68 | 5.17 | 1.17 | 0.93 | 4.83 | 4.05 | LOS | 106 | 114 | 134 | 16.7% | 8.4% | 17.6% | 11.9% | 11.6% |
| Francisco Liriano | PIT | -3.9 | 3.39 | 5.83 | 2.03 | 0.91 | 3.2 | 4.45 | ARI | 94 | 98 | 109 | 22.5% | 9.4% | 22.0% | 13.2% | 13.6% |
| Garrett Richards | ANA | 2 | 3.61 | 6.35 | 1.87 | 0.91 | 3.47 | 3.12 | CHW | 89 | 92 | 77 | 22.2% | 7.0% | 19.2% | 9.5% | 10.1% |
| Hisashi Iwakuma | SEA | -3.1 | 3.1 | 6.53 | 1.77 | 1.08 | 2.91 | 2.72 | TEX | 99 | 101 | 115 | 20.2% | 6.2% | 19.1% | 10.1% | 7.8% |
| Jacob deGrom | NYM | 2 | 3.08 | 6.52 | 1.31 | 1.04 | 3.33 | 2.66 | BAL | 112 | 102 | 126 | 24.5% | 6.8% | 20.9% | 14.4% | 6.2% |
| Jake Odorizzi | TAM | 10.6 | 3.71 | 5.67 | 0.79 | 1.01 | 4.19 | 3.54 | HOU | 113 | 102 | 78 | 22.6% | 7.4% | 20.9% | 12.6% | 10.2% |
| James Shields | SDG | -7.8 | 3.49 | 6.47 | 1.28 | 0.84 | 3.49 | 3.51 | ATL | 82 | 89 | 88 | 20.7% | 7.3% | 20.1% | 11.1% | 6.6% |
| Jason Hammel | CHC | 5 | 3.44 | 5.87 | 0.99 | 1.05 | 3.7 | 3.77 | DET | 99 | 103 | 61 | 22.7% | 6.9% | 21.8% | 11.0% | 9.1% |
| John Danks | CHW | -6.6 | 4.61 | 5.94 | 1.04 | 0.91 | 4.76 | 5.26 | ANA | 104 | 90 | 82 | 17.1% | 8.4% | 21.3% | 8.6% | 11.2% |
| Jordan Zimmermann | WAS | -3 | 3.44 | 6.3 | 1.13 | 1.4 | 3.22 | 2.23 | COL | 97 | 98 | 50 | 22.7% | 5.0% | 21.0% | 8.5% | 12.6% |
| Kevin Gausman | BAL | 7.9 | 3.78 | 5.76 | 1.12 | 1.04 | 3.92 | 4.01 | NYM | 77 | 90 | 95 | 21.3% | 7.0% | 22.1% | 8.4% | 12.2% |
| Lance Lynn | STL | 1.1 | 3.71 | 6. | 1.21 | 0.98 | 3.85 | 4.16 | SFO | 108 | 114 | 114 | 20.6% | 8.0% | 22.5% | 10.6% | 9.2% |
| Matthew Wisler | ATL | -3.6 | 4.75 | 5.7 | 0.87 | 0.84 | 4.36 | 4.81 | SDG | 90 | 91 | 122 | 18.2% | 7.6% | 24.6% | 13.1% | 8.7% |
| Ryan Vogelsong | SFO | 1 | 4.28 | 5.71 | 1.14 | 0.98 | 4.56 | 3.2 | STL | 103 | 100 | 105 | 20.4% | 8.9% | 22.5% | 12.3% | 7.0% |
| Mike Pelfrey | MIN | 2.9 | 4.77 | 5.59 | 1.75 | 1.02 | 5.18 | 4.45 | NYY | 116 | 104 | 90 | 15.3% | 7.7% | 20.8% | 10.0% | 10.4% |
| R.A. Dickey | TOR | -1.8 | 4.26 | 6.51 | 1.1 | 1.01 | 4.6 | 5.02 | PHI | 88 | 84 | 88 | 17.8% | 6.6% | 21.0% | 9.7% | 13.0% |
| Raisel Iglesias | CIN | 3.8 | 3.46 | 5.61 | 1.15 | 1.02 | 3.99 | 2.15 | KAN | 94 | 103 | 115 | 20.8% | 7.0% | 20.2% | 9.9% | 7.7% |
| Scott Feldman | HOU | -1.8 | 4.32 | 6.15 | 1.6 | 1.01 | 4.08 | 4.62 | TAM | 97 | 93 | 128 | 17.4% | 6.5% | 22.5% | 11.2% | 8.4% |
| Trevor Bauer | CLE | -3 | 3.96 | 5.98 | 0.87 | 1.07 | 4.22 | 4.64 | BOS | 111 | 95 | 182 | 18.8% | 9.1% | 20.9% | 16.1% | 9.0% |
| Tyler Cravy | MIL | -5.1 | 4.85 | 5.53 | 1.07 | 1.07 | 4.99 | 5.4 | FLA | 86 | 79 | 114 | 16.9% | 8.0% | 22.4% | 13.3% | 9.0% |
Aaron Nola has experienced some growing pains in his introduction to the majors, but has been just about league average according to his peripherals with a 13.7 K-BB%, though he is allowing a great deal of hard contact (16.1 Hard-Soft%). The Blue Jays are the best offense in the game, but merely average on the road and better against LHP than RHP and in the midst of a cooling off period over the last week (17.1 K-BB%).
Anibal Sanchez has allowed at least three ERs (and usually more) in nine of his last 10 starts with 15 HRs over that span. At some point, you have to buy into the FIP and 15.7 HR/FB made worse by the lowest GB/FB of his career (1.02). The K% has remained league average at least and that could be a big deal tonight, facing the Cubs and even make him useful if the wind is blowing in the right direction. They are one of the worst home offenses in the league (23.8 K%) and below average vs RHP (24.1 K%). They’ve been hitting the ball well over the last week (20.8 HR/FB), but still striking out frequently (26.4%). A park bump makes them a neutral overall opponent.
C.C. Sabathia is coming off back to back strong starts by ERA and contact authority (-11.1 Hard-Soft%), but struck out eight in the first and just two in the most recent. He has an 18.6 K-BB%, but exactly the same HR/FB at home since last season. As I mention every time, his success will normally depend on if he’s able to hit the corners and stay away from the middle of the plate and if the umpire is going to give him those pitches. Then, from there, we look at the other particulars in determining if it’s a matchup worth pursuing. The Twins are the worst road offense (22.4 K%, 8.5 HR/FB) and below average vs RHP, making them a slightly favorable park adjusted matchup here.
Chase Anderson has had a strange season. It began well, then he forgot how to miss bats, then he started giving up HRs at a high right, like he did last season, finally he’s begun missing bats again with just one HR in three starts since the break, but 12 ERs in 15.2 IP. Which is the real pitcher here? Either one gives up a little too much hard contact for my taste, but if he can generate something close to a league average strikeout rate, he can be useful occasionally in good parks at the right price. This may be one of those situations. The Pirates obviously showed some wear last night from playing a grueling series in which they swept the Mets, but played a lot of innings over the weekend with the bats finally cooling off. They are above average at home and average vs RHP, but the park adjustment neutralizes the matchup here. The park should be able to help contain his long ball issues and give him a chance.
Clayton Kershaw has gone at least eight shutout innings with seven strikeouts in five of his last six starts. His 24.8 K-BB% on the road since last season isn’t as good as his home mark, but would still rank among league leaders this year, mark in which he actually leads the league (27.9%) overall along with a 15.5 SwStr%. Oakland is a slightly below average offense that doesn’t strike out much (16% at Home, 17.2% vs LHP), but don’t hit the ball hard (6.8 HR/FB at Home, 7.5 HR/FB vs LHP, -2.1 Hard-Soft% over the last week).They are a very favorable park adjusted matchup. It’s uneccesary to over-think it. Just try to figure out a way to afford it.
Francisco Liriano has failed to strike out more than six in seven of his last nine with a total of 13 strikeouts over his last 71 batters (14.2 IP). For the season, he still has an excellent 18.4 K-BB%, but it’s been more a random performance that stands out every once in a while than consistency. He’s making his living inducing incredibly weak contact this year (2.14 GB/FB, -5.5 Hard-Soft%). His 25.0 K% at home since last season is actually worse than his road rate, though still a great mark. Stunningly, nine of his 11 HRs have come at home, as it’s supposed to be a park that kills RH power. Arizona is an overall neutral offense that strikes out a bit more than average, but has some RH pop (12.1 HR/FB vs LHP), which may not play down as much as expected here. They have a team 25.0 Hard-Soft% over the last week, but should still be an advantageous overall matchup with a negative park adjustment here.
Garrett Richards has had the double digit SwStr% all season with the expectation that his K% would eventually rise to meet it and that’s what’s been happening over the last month, though he’s still below average for the season. He does this while maintaining a proficiency for weak contact (1.4 Hard-Soft%), despite allowing five HRs over his last five starts. His K rate rises slightly to 22% at home since last season with just a 5.6 HR/FB. The White Sox are below average on the road (14.5 K-BB%) and vs RHP (14.2 K-BB%) with just a 6.2 Hard-Soft% overall. They’ve been cold over the last week (23.0 K%) and serve as a great park adjusted matchup.
Hisashi Iwakuma is coming off a no-hitter in which he threw 116 pitches after throwing 118 pitches in his previous start. His K% and SwStr% are both up over the last month and he’s allowed just three HRs over his last seven starts after 9 over his first four. He has an 18.0 K-BB% on the road since last season, but this matchup could be a challenge for him. While the Rangers are a neutral offense at home and vs RHP, they have been hitting the ball well and get a park bump that could make them a very tough matchup tonight.
Jacob deGrom has allowed two ERs or less in 14 of his last 15 starts and no more than three with at least seven Ks in each of his last six starts, but has only twice pitched in unfavorable environments and in neither situation against an offense with this kind of power (16.6 HR/FB at Home, 15.0 HR/FB vs RHP, 19.7 HR/FB over the last week) in that span. When he’s not striking out 26.9% of the batters he faces, he has just a 1.19 GB/FB and slightly higher 9.4 HR/FB on the road. It’s possible he could find some trouble here against a strong home offense that’s been hitting the ball well and a very tough overall park adjusted matchup, but they do strike out 22.1% against RHP.
Jake Odorizzi has a slightly above average 14.7 K-BB% this season, but has really relied on a low 7.6 HR/FB with a 1.05 GB/FB in a great park for a lot of his success. Those numbers drop to a 12.2 K-BB% that’s just average with a 13.2 HR/FB on the road since last season. Obviously, this could be a problem in Houston against a strong home offense, though just neutral against RHP, and cold over the last week. This makes them a fairly neutral matchup in a neutral run environment, but they could cause problems with his HR rate, while helping his strikeout rate at the same time. There’s a lot of ways this could go and of course, we also have to consider that he hasn’t hit the seven inning mark since May and only three times this season overall.
James Shields may not be missing bats like he had early in the season, but still has an above average rate over the last month and has struck out 15 of his last 57 batters, despite allowing eight ERs and three more HRs over both starts at home. His HR issues had improved up until that point, though he still carries a 17.4 HR/FB for the season now. The Braves don’t strike out much (17.2% vs RHP), but they don’t hit for power either (7.9 HR/FB on the road, 7.7 HR/FB and 5.4 Hard-Soft% vs RHP). They are a poor offense in any situation and the top park adjusted matchup of the day.
Jason Hammel has been on a strange run. He’s allowed two ERs or less in six of his last seven starts, but hasn’t completed six innings in any of his last six starts, despite low pitch counts. Hijinks may be in play here, but he’s sustaining a career best 19.1 K-BB% this year, so something is working. Detroit is really a neutral offense on the road vs RHP, but have been ice cold over the last week (26.4 K%, 3.1 HR/FB, -7.0 Hard-Soft%). Even with an offensive park bump, they remain close to neutral here.
Jordan Zimmermann has allowed just two ERs with 15 strikeouts and a -12.9 Hard-Soft% over his last two starts. He’s seen a significant spike in both his SwStr% and K% over the last month. Normally, I’d dismiss most pitchers in Colorado, but he has a 19.1 K-BB% on the road since last season and a career 8.4 HR/FB and faces an offense that’s been less than average at home this year without the park adjustment. With the park adjustment, a neutral and ice cold offense turns into one of the most dangerous of the night, but it keeps his price tag the same despite the K% increase.
Kevin Gausman continues to be mediocre and frustrating, allowing six runs in one outing and striking out eight in the next. With the majority of his innings as a starter now, his 14.2 K-BB% is above average, but he’s really being punished by a 66.0 LOB%. Only one of his seven HRs have come at home this year, giving him a 5.4 HR/FB in Baltimore since last season. The Mets are the 2nd worst road offense (16.1 K-BB%, 7.6 HR/FB) and remain a favorable matchup even with the park bump.
R.A. Dickey is probably doing some unsustainable thing over the last month or so, but you can’t judge knuckleballers by the conventional rules and where ever you’re pessimistic, that has to be some optimism over his SwStr% (we’ll discuss later). I’m throwing out the numbers that say to discard him and looking at the favorable matchup against a Philadelphia team that seems like they’d struggle with the knuckleball (and did less than a month ago).
Raisel Iglesias has a 24.0 K% that the Royals will surely wreak havoc with (15.7 K% vs RHP), but that doesn’t mean he’s not going to strike out anybody and even projects for a near league average rate tonight. He’s gone at least six innings now in each of his last four starts, though not much more. The Royals are a slightly unfavorable matchup because the overall run environment isn’t nearly as great as the power bump for this park.
NOT AS GOOD AS THEY LOOK
This list is reserved for pitchers who may look attractive because their ERAs are much lower than their estimators. The reason for this is almost always extreme BABIP, LOB, and/or HR/FB deviation from the norm, so we’ll just quote those stats and be done with them.
League AVG (.294 BABIP – 72.3 LOB% – 10.8 HR/FB)
Extreme deviations from league averages are italicized
Lance Lynn (.322 BABIP – 77.9 LOB% – 7.8 HR/FB) – The BABIP is close enough to his .309 career mark and consistent enough that I’m not going to expect much regression. The problem is that he’s allowed four HRs over his last four home starts and blame the summer heat, but if he’s not going to suppress power at home, he’s hardly worth paying up for, especially against the best offense on the road (and only one of two above average) and vs RHP.
Edinson Volquez (.275 BABIP – 73.3 LOB% – 7.0 HR/FB) – The HR rate is only highlighted because this is a park that favors power hitters, giving his great outfielders less room to catch up with his fly balls, as he knows from pitching here for several years, and he’s less likely to reach value with a below average K%.
Mike Pelfrey (.313 BABIP – 71.6 LOB% – 6.4 HR/FB) – Good luck with that HR rate and a 4.4 K-BB% in Yankee Stadium.
NO THANK YOU (In order from least to most offensive)
Trevor Bauer – The Red Sox don’t strike out. This could destroy his value. It’s not like he’s ever easy to project accurately even when there’s a better expectation for strikeouts.
Matthew Wisler
Alex “Chi Chi” Gonzalez
Combo K/BB Charts
These are the Combo K & BB numbers from above fleshed out. They are weighted equally in the main chart above. They probably shouldn’t be, but originally were due to size limitations. What’s the correct weighting? Who knows? But now you have all 6 components (Pitcher: L2Yrs, H/R, L14Days – Opposition: H/A, vL/R, L7Days) that make up the above numbers.
| Pitcher | Team | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | Phillies | 18.6% | 4.8% | Home | 20.5% | 2.3% | L14 Days | 15.4% | 5.8% |
| Adam Conley | Marlins | 12.2% | 6.8% | Road | 6.3% | 6.3% | L14 Days | 14.0% | 7.0% |
| Alex Gonzalez | Rangers | 9.2% | 11.6% | Home | 6.4% | 10.6% | L14 Days | 14.8% | 18.5% |
| Anibal Sanchez | Tigers | 21.6% | 6.8% | Road | 20.3% | 5.3% | L14 Days | 19.6% | 9.8% |
| CC Sabathia | Yankees | 19.6% | 6.3% | Home | 23.2% | 4.6% | L14 Days | 19.6% | 9.8% |
| Chase Anderson | Diamondbacks | 18.9% | 7.0% | Road | 17.7% | 7.5% | L14 Days | 25.0% | 4.2% |
| Clayton Kershaw | Dodgers | 31.6% | 4.7% | Road | 30.2% | 5.4% | L14 Days | 23.6% | 3.6% |
| David Hale | Rockies | 14.7% | 7.8% | Home | 14.5% | 8.1% | L14 Days | ||
| Edinson Volquez | Royals | 17.6% | 8.7% | Road | 18.1% | 8.0% | L14 Days | 14.3% | 7.1% |
| Eduardo Rodriguez | Red Sox | 18.9% | 8.1% | Home | 20.1% | 7.9% | L14 Days | 12.7% | 5.5% |
| Felix Doubront | Athletics | 14.1% | 8.4% | Home | 14.9% | 10.1% | L14 Days | 11.6% | 2.3% |
| Francisco Liriano | Pirates | 26.0% | 10.2% | Home | 25.0% | 9.7% | L14 Days | 20.0% | 13.3% |
| Garrett Richards | Angels | 21.0% | 7.8% | Home | 22.0% | 7.8% | L14 Days | 26.5% | 7.2% |
| Hisashi Iwakuma | Mariners | 21.4% | 3.9% | Road | 22.5% | 4.5% | L14 Days | 22.8% | 5.3% |
| Jacob deGrom | Mets | 26.2% | 6.3% | Road | 25.1% | 7.1% | L14 Days | 33.3% | 7.8% |
| Jake Odorizzi | Rays | 22.7% | 7.4% | Road | 19.9% | 7.6% | L14 Days | 23.5% | 3.9% |
| James Shields | Padres | 22.2% | 6.2% | Home | 22.1% | 5.8% | L14 Days | 26.3% | 8.8% |
| Jason Hammel | Cubs | 22.7% | 5.6% | Home | 21.1% | 5.4% | L14 Days | 23.7% | 7.9% |
| John Danks | White Sox | 15.1% | 7.7% | Road | 14.5% | 8.5% | L14 Days | 14.8% | 11.1% |
| Jordan Zimmermann | Nationals | 20.9% | 3.9% | Road | 22.8% | 3.7% | L14 Days | 31.9% | 2.1% |
| Kevin Gausman | Orioles | 20.7% | 7.4% | Home | 17.9% | 6.8% | L14 Days | 21.4% | 7.1% |
| Lance Lynn | Cardinals | 22.5% | 8.3% | Home | 21.0% | 7.7% | L14 Days | 21.6% | 10.8% |
| Matthew Wisler | Braves | 14.7% | 7.2% | Road | 16.3% | 6.8% | L14 Days | 16.0% | 10.0% |
| Ryan Vogelsong | Giants | 17.7% | 8.2% | Road | 17.4% | 9.3% | L14 Days | 32.6% | 11.6% |
| Mike Pelfrey | Twins | 12.4% | 8.3% | Road | 7.7% | 8.4% | L14 Days | 13.0% | 4.4% |
| R.A. Dickey | Blue Jays | 17.8% | 7.8% | Road | 15.3% | 7.7% | L14 Days | 13.5% | 7.7% |
| Raisel Iglesias | Reds | 24.0% | 6.7% | Home | 22.9% | 7.9% | L14 Days | 32.6% | 4.7% |
| Scott Feldman | Astros | 14.3% | 6.6% | Home | 12.9% | 5.0% | L14 Days | 14.9% | 6.4% |
| Trevor Bauer | Indians | 22.3% | 9.3% | Road | 22.5% | 9.8% | L14 Days | 19.2% | 10.6% |
| Tyler Cravy | Brewers | 15.5% | 9.7% | Home | 13.7% | 5.9% | L14 Days | 15.9% | 13.6% |
Combo K/BB Charts – Opponent
| Opponent | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Blue Jays | Road | 20.9% | 7.9% | RH | 19.2% | 8.4% | L7Days | 23.4% | 6.3% |
| Brewers | Home | 20.5% | 7.4% | LH | 20.6% | 7.1% | L7Days | 23.1% | 4.9% |
| Mariners | Road | 20.2% | 7.4% | RH | 21.7% | 8.2% | L7Days | 23.5% | 8.4% |
| Cubs | Home | 23.8% | 9.5% | RH | 24.1% | 8.9% | L7Days | 26.4% | 9.7% |
| Twins | Road | 22.4% | 6.8% | LH | 19.9% | 7.1% | L7Days | 18.9% | 7.3% |
| Pirates | Home | 19.4% | 7.1% | RH | 20.5% | 6.9% | L7Days | 20.7% | 7.1% |
| Athletics | Home | 16.0% | 7.5% | LH | 17.2% | 8.4% | L7Days | 21.4% | 6.8% |
| Nationals | Road | 22.3% | 7.7% | RH | 21.3% | 8.1% | L7Days | 26.7% | 4.8% |
| Reds | Home | 18.6% | 8.8% | RH | 19.2% | 7.8% | L7Days | 21.4% | 6.7% |
| Indians | Road | 18.8% | 8.6% | LH | 18.7% | 9.2% | L7Days | 19.7% | 7.5% |
| Dodgers | Road | 20.5% | 9.8% | LH | 20.4% | 9.4% | L7Days | 18.6% | 10.5% |
| Diamondbacks | Road | 20.9% | 7.5% | LH | 21.2% | 8.7% | L7Days | 21.6% | 6.9% |
| White Sox | Road | 20.1% | 5.6% | RH | 20.6% | 6.4% | L7Days | 23.0% | 7.4% |
| Rangers | Home | 18.8% | 8.4% | RH | 19.1% | 7.8% | L7Days | 16.7% | 7.0% |
| Orioles | Home | 20.5% | 6.7% | RH | 22.1% | 6.9% | L7Days | 19.8% | 5.8% |
| Astros | Home | 23.8% | 9.1% | RH | 23.7% | 7.6% | L7Days | 22.1% | 8.8% |
| Braves | Road | 18.0% | 6.7% | RH | 17.2% | 7.2% | L7Days | 18.2% | 8.9% |
| Tigers | Road | 22.2% | 7.1% | RH | 20.0% | 6.8% | L7Days | 26.4% | 8.6% |
| Angels | Home | 20.1% | 7.7% | LH | 18.8% | 8.4% | L7Days | 19.2% | 7.0% |
| Rockies | Home | 18.0% | 7.2% | RH | 20.3% | 6.2% | L7Days | 22.0% | 6.8% |
| Mets | Road | 22.6% | 6.5% | RH | 20.7% | 7.4% | L7Days | 24.6% | 6.8% |
| Giants | Road | 18.7% | 7.0% | RH | 18.1% | 7.1% | L7Days | 21.4% | 7.3% |
| Padres | Home | 22.9% | 6.4% | RH | 21.6% | 6.7% | L7Days | 17.9% | 8.3% |
| Cardinals | Home | 18.5% | 8.5% | RH | 18.9% | 7.6% | L7Days | 17.2% | 8.4% |
| Yankees | Home | 19.1% | 9.0% | RH | 19.1% | 8.3% | L7Days | 20.6% | 8.0% |
| Phillies | Home | 18.9% | 6.4% | RH | 19.6% | 5.6% | L7Days | 21.9% | 4.3% |
| Royals | Road | 16.6% | 5.3% | RH | 15.7% | 6.2% | L7Days | 13.1% | 11.0% |
| Rays | Road | 21.0% | 7.4% | RH | 22.0% | 7.0% | L7Days | 19.5% | 6.5% |
| Red Sox | Home | 17.0% | 7.8% | RH | 16.7% | 7.7% | L7Days | 15.1% | 9.2% |
| Marlins | Road | 20.3% | 6.0% | RH | 19.6% | 6.4% | L7Days | 16.3% | 6.3% |
Combo Batted Ball Charts
See the explanation for the K/BB chart above.
| Pitcher | Team | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | Phillies | 20.7% | 13.3% | 10.0% | Home | 20.6% | 22.2% | 11.1% | L14 Days | 23.7% | 0.0% | 14.3% |
| Adam Conley | Marlins | 20.7% | 13.0% | 17.4% | Road | 21.4% | 20.0% | 0.0% | L14 Days | 21.2% | 15.4% | 7.7% |
| Alex Gonzalez | Rangers | 23.8% | 8.9% | 2.2% | Home | 23.7% | 11.8% | 0.0% | L14 Days | 38.9% | 16.7% | 0.0% |
| Anibal Sanchez | Tigers | 19.9% | 10.0% | 10.8% | Road | 19.7% | 13.2% | 6.1% | L14 Days | 19.4% | 26.7% | 6.7% |
| CC Sabathia | Yankees | 23.3% | 17.1% | 9.5% | Home | 24.2% | 18.6% | 10.2% | L14 Days | 23.5% | 0.0% | 33.3% |
| Chase Anderson | Diamondbacks | 23.9% | 12.3% | 8.5% | Road | 25.4% | 13.6% | 7.8% | L14 Days | 25.0% | 12.5% | 0.0% |
| Clayton Kershaw | Dodgers | 20.6% | 8.4% | 12.1% | Road | 19.8% | 8.3% | 15.0% | L14 Days | 18.9% | 11.1% | 0.0% |
| David Hale | Rockies | 18.3% | 11.9% | 8.2% | Home | 19.2% | 13.2% | 7.9% | L14 Days | |||
| Edinson Volquez | Royals | 18.7% | 9.2% | 6.1% | Road | 19.3% | 12.8% | 8.1% | L14 Days | 15.9% | 0.0% | 7.1% |
| Eduardo Rodriguez | Red Sox | 22.8% | 12.3% | 16.0% | Home | 22.2% | 13.6% | 13.6% | L14 Days | 23.8% | 16.7% | 25.0% |
| Felix Doubront | Athletics | 19.3% | 10.3% | 11.9% | Home | 15.2% | 16.4% | 11.5% | L14 Days | 8.1% | 6.7% | 20.0% |
| Francisco Liriano | Pirates | 21.1% | 12.1% | 8.7% | Home | 19.7% | 16.3% | 8.2% | L14 Days | 28.6% | 20.0% | 40.0% |
| Garrett Richards | Angels | 19.0% | 7.8% | 9.5% | Home | 19.3% | 5.6% | 10.4% | L14 Days | 16.7% | 11.8% | 11.8% |
| Hisashi Iwakuma | Mariners | 19.7% | 13.5% | 8.1% | Road | 21.6% | 12.2% | 9.8% | L14 Days | 15.0% | 0.0% | 0.0% |
| Jacob deGrom | Mets | 21.8% | 7.2% | 8.8% | Road | 19.2% | 9.4% | 6.5% | L14 Days | 25.0% | 18.2% | 0.0% |
| Jake Odorizzi | Rays | 21.7% | 8.2% | 9.5% | Road | 23.0% | 13.2% | 5.4% | L14 Days | 24.3% | 11.1% | 11.1% |
| James Shields | Padres | 21.6% | 11.2% | 10.8% | Home | 22.8% | 11.3% | 6.2% | L14 Days | 20.0% | 20.0% | 0.0% |
| Jason Hammel | Cubs | 22.0% | 11.4% | 6.3% | Home | 21.4% | 11.5% | 7.0% | L14 Days | 24.0% | 18.2% | 9.1% |
| John Danks | White Sox | 20.6% | 10.1% | 8.4% | Road | 20.7% | 10.2% | 9.6% | L14 Days | 25.6% | 0.0% | 18.8% |
| Jordan Zimmermann | Nationals | 22.9% | 7.0% | 12.9% | Road | 23.8% | 9.0% | 16.3% | L14 Days | 16.1% | 0.0% | 15.4% |
| Kevin Gausman | Orioles | 21.3% | 7.3% | 12.6% | Home | 21.8% | 5.4% | 15.1% | L14 Days | 25.0% | 5.6% | 5.6% |
| Lance Lynn | Cardinals | 21.1% | 7.3% | 11.5% | Home | 18.5% | 4.9% | 10.3% | L14 Days | 30.4% | 16.7% | 16.7% |
| Matthew Wisler | Braves | 25.9% | 10.7% | 14.7% | Road | 30.0% | 14.6% | 17.1% | L14 Days | 36.1% | 20.0% | 0.0% |
| Ryan Vogelsong | Giants | 23.1% | 9.8% | 7.2% | Road | 23.3% | 14.8% | 6.0% | L14 Days | 20.8% | 20.0% | 0.0% |
| Mike Pelfrey | Twins | 21.7% | 7.7% | 8.8% | Road | 19.8% | 10.9% | 9.4% | L14 Days | 24.3% | 0.0% | 16.7% |
| R.A. Dickey | Blue Jays | 20.3% | 10.8% | 12.6% | Road | 20.2% | 8.5% | 14.7% | L14 Days | 14.6% | 10.5% | 26.3% |
| Raisel Iglesias | Reds | 21.8% | 10.0% | 10.0% | Home | 18.3% | 7.9% | 10.5% | L14 Days | 15.4% | 14.3% | 0.0% |
| Scott Feldman | Astros | 22.6% | 10.5% | 7.2% | Home | 22.8% | 12.4% | 8.3% | L14 Days | 21.6% | 13.3% | 0.0% |
| Trevor Bauer | Indians | 21.6% | 11.2% | 10.3% | Road | 20.3% | 9.8% | 10.4% | L14 Days | 25.8% | 38.5% | 7.7% |
| Tyler Cravy | Brewers | 23.7% | 14.3% | 10.7% | Home | 20.0% | 11.1% | 11.1% | L14 Days | 22.6% | 25.0% | 0.0% |
Combo Batted Ball Charts – Opponent
| Opponent | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Blue Jays | Road | 19.0% | 12.7% | 14.1% | RH | 18.8% | 14.1% | 12.8% | L7Days | 16.4% | 10.2% | 12.2% |
| Brewers | Home | 21.3% | 11.4% | 6.9% | LH | 18.2% | 11.2% | 5.4% | L7Days | 22.4% | 7.3% | 7.3% |
| Mariners | Road | 19.5% | 13.4% | 7.4% | RH | 20.1% | 12.5% | 6.4% | L7Days | 24.8% | 17.5% | 5.3% |
| Cubs | Home | 21.6% | 10.5% | 11.1% | RH | 20.2% | 11.4% | 9.6% | L7Days | 24.6% | 20.8% | 11.3% |
| Twins | Road | 19.1% | 8.5% | 10.8% | LH | 19.6% | 11.4% | 8.8% | L7Days | 22.8% | 18.8% | 6.3% |
| Pirates | Home | 21.4% | 11.4% | 5.8% | RH | 20.8% | 9.9% | 6.9% | L7Days | 17.6% | 9.9% | 4.9% |
| Athletics | Home | 19.3% | 6.8% | 11.4% | LH | 18.0% | 7.5% | 12.0% | L7Days | 17.1% | 10.8% | 10.8% |
| Nationals | Road | 22.2% | 13.2% | 9.5% | RH | 20.8% | 12.8% | 9.3% | L7Days | 21.0% | 9.8% | 5.9% |
| Reds | Home | 22.9% | 12.8% | 8.5% | RH | 20.9% | 10.0% | 8.8% | L7Days | 20.4% | 15.6% | 4.4% |
| Indians | Road | 20.3% | 9.9% | 10.1% | LH | 23.5% | 7.4% | 6.5% | L7Days | 26.3% | 5.5% | 12.7% |
| Dodgers | Road | 21.3% | 13.6% | 9.1% | LH | 22.4% | 11.8% | 7.0% | L7Days | 19.4% | 12.7% | 9.9% |
| Diamondbacks | Road | 20.2% | 10.9% | 9.8% | LH | 18.8% | 12.1% | 8.7% | L7Days | 23.3% | 7.7% | 6.2% |
| White Sox | Road | 21.7% | 9.6% | 10.5% | RH | 21.5% | 11.5% | 9.6% | L7Days | 17.2% | 10.6% | 8.5% |
| Rangers | Home | 19.5% | 11.3% | 8.6% | RH | 18.9% | 10.9% | 8.6% | L7Days | 19.9% | 12.9% | 11.4% |
| Orioles | Home | 20.9% | 16.6% | 7.8% | RH | 20.7% | 15.0% | 9.4% | L7Days | 17.5% | 19.7% | 4.5% |
| Astros | Home | 18.3% | 17.8% | 9.9% | RH | 20.2% | 14.8% | 11.3% | L7Days | 17.6% | 10.3% | 13.8% |
| Braves | Road | 22.0% | 7.9% | 8.7% | RH | 21.8% | 7.7% | 9.5% | L7Days | 12.4% | 8.3% | 4.2% |
| Tigers | Road | 21.9% | 11.4% | 7.7% | RH | 21.6% | 10.4% | 8.8% | L7Days | 19.8% | 3.1% | 15.6% |
| Angels | Home | 21.7% | 12.2% | 10.4% | LH | 18.4% | 10.3% | 11.0% | L7Days | 20.9% | 8.7% | 8.7% |
| Rockies | Home | 22.7% | 13.1% | 8.7% | RH | 21.4% | 14.4% | 9.3% | L7Days | 19.0% | 7.5% | 13.2% |
| Mets | Road | 23.2% | 7.6% | 11.1% | RH | 22.5% | 9.8% | 12.4% | L7Days | 18.9% | 14.5% | 16.4% |
| Giants | Road | 22.3% | 12.7% | 6.0% | RH | 21.4% | 11.0% | 7.0% | L7Days | 21.3% | 11.1% | 3.7% |
| Padres | Home | 19.5% | 11.1% | 6.9% | RH | 19.3% | 10.2% | 8.1% | L7Days | 16.8% | 11.9% | 5.1% |
| Cardinals | Home | 22.2% | 8.4% | 8.9% | RH | 22.5% | 9.3% | 9.8% | L7Days | 23.1% | 11.5% | 9.8% |
| Yankees | Home | 19.3% | 14.8% | 11.4% | RH | 20.9% | 13.7% | 9.0% | L7Days | 18.9% | 13.1% | 7.1% |
| Phillies | Home | 21.9% | 9.4% | 8.1% | RH | 22.5% | 8.4% | 8.6% | L7Days | 26.7% | 10.3% | 7.7% |
| Royals | Road | 22.9% | 8.7% | 9.8% | RH | 21.3% | 9.0% | 9.7% | L7Days | 21.3% | 9.2% | 6.2% |
| Rays | Road | 21.5% | 9.9% | 9.9% | RH | 21.6% | 9.6% | 9.1% | L7Days | 24.9% | 11.4% | 15.9% |
| Red Sox | Home | 20.7% | 11.4% | 9.3% | RH | 20.3% | 9.5% | 10.6% | L7Days | 16.9% | 16.2% | 5.4% |
| Marlins | Road | 22.0% | 11.1% | 8.5% | RH | 20.2% | 9.4% | 8.6% | L7Days | 25.7% | 8.7% | 15.2% |
K/SwStr Chart (2015 LG AVG – 20.2 K% – 9.8 SwStr% – 2.06 K/SwStr)
Getting called strikeouts can be a skill, but it’s usually not a sustainable one at a large deviation from the league rate (catcher framing and other factors may make some difference here). K% correlates heavily with SwStr% though. Look for a large difference and you might find a potential adjustment before anyone else.
| Pitcher | Team | K% Season | SwStr% Season | K%/SwStr% | K% L30 Days | SwStr% L30 Days | K%/SwStr% |
|---|---|---|---|---|---|---|---|
| Aaron Nola | PHI | 18.6% | 9.1% | 2.04 | 18.6% | 9.1% | 2.04 |
| Adam Conley | FLA | 12.2% | 6.7% | 1.82 | 14.0% | 8.4% | 1.67 |
| Alex Gonzalez | TEX | 9.2% | 6.2% | 1.48 | 14.8% | 5.2% | 2.85 |
| Anibal Sanchez | DET | 20.9% | 9.4% | 2.22 | 20.3% | 9.4% | 2.16 |
| CC Sabathia | NYY | 19.0% | 8.9% | 2.13 | 18.1% | 8.7% | 2.08 |
| Chase Anderson | ARI | 16.2% | 7.2% | 2.25 | 21.4% | 8.4% | 2.55 |
| Clayton Kershaw | LOS | 32.7% | 15.5% | 2.11 | 32.9% | 15.4% | 2.14 |
| David Hale | COL | 17.0% | 11.0% | 1.55 | |||
| Edinson Volquez | KAN | 17.4% | 9.7% | 1.79 | 17.1% | 9.4% | 1.82 |
| Eduardo Rodriguez | BOS | 18.9% | 7.9% | 2.39 | 14.2% | 6.7% | 2.12 |
| Felix Doubront | OAK | 12.5% | 8.0% | 1.56 | 10.8% | 7.7% | 1.40 |
| Francisco Liriano | PIT | 27.2% | 14.0% | 1.94 | 25.5% | 12.6% | 2.02 |
| Garrett Richards | ANA | 19.2% | 11.0% | 1.75 | 21.3% | 10.7% | 1.99 |
| Hisashi Iwakuma | SEA | 20.4% | 10.3% | 1.98 | 23.3% | 11.8% | 1.97 |
| Jacob deGrom | NYM | 26.9% | 12.1% | 2.22 | 32.5% | 13.6% | 2.39 |
| Jake Odorizzi | TAM | 20.8% | 9.8% | 2.12 | 24.2% | 9.5% | 2.55 |
| James Shields | SDG | 25.9% | 13.0% | 1.99 | 23.1% | 11.4% | 2.03 |
| Jason Hammel | CHC | 24.3% | 10.6% | 2.29 | 19.2% | 9.6% | 2.00 |
| John Danks | CHW | 16.4% | 8.8% | 1.86 | 18.1% | 8.9% | 2.03 |
| Jordan Zimmermann | WAS | 18.8% | 8.1% | 2.32 | 23.6% | 10.4% | 2.27 |
| Kevin Gausman | BAL | 20.5% | 11.1% | 1.85 | 19.9% | 11.4% | 1.75 |
| Lance Lynn | STL | 25.0% | 9.7% | 2.58 | 22.4% | 11.2% | 2.00 |
| Matthew Wisler | ATL | 14.7% | 7.6% | 1.93 | 12.4% | 7.2% | 1.72 |
| Ryan Vogelsong | SFO | 18.4% | 5.8% | 3.17 | 28.8% | 7.9% | 3.65 |
| Mike Pelfrey | MIN | 11.3% | 5.2% | 2.17 | 10.3% | 4.7% | 2.19 |
| R.A. Dickey | TOR | 14.8% | 9.3% | 1.59 | 16.6% | 9.4% | 1.77 |
| Raisel Iglesias | CIN | 24.0% | 10.7% | 2.24 | 27.6% | 10.7% | 2.58 |
| Scott Feldman | HOU | 13.6% | 6.8% | 2.00 | 11.1% | 7.3% | 1.52 |
| Trevor Bauer | CLE | 23.2% | 10.4% | 2.23 | 22.7% | 9.7% | 2.34 |
| Tyler Cravy | MIL | 15.5% | 7.0% | 2.21 | 15.9% | 9.3% | 1.71 |
R.A. Dickey – It seems about right that the only season long outlier we care about today is a knuckleballer. His SwStr% is right in line with two years ago when he had an 18.8 K% and we’ve seen a slight rise in K% without a change in his SwStr% over the last month. I would imagine it’s difficult to frame a knuckleball though and perhaps that’s part of why Russell Martin is merely average (+1.1 RAA) in that respect this year.
ERA Estimators Chart (2015 LG AVG – 3.85 ERA – 3.78 SIERA – 3.85 xFIP – 3.85 FIP)
How a pitcher’s ERA matches up against his defense independent estimators.
| Pitcher | Team | Season ERA | Season SIERA | DIFF | Season xFIP | DIFF | Season FIP | DIFF | ERA L30 | SIERA L30 | DIFF | xFIP L30 | DIFF | FIP L30 | DIFF |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | PHI | 4.25 | 3.78 | -0.47 | 3.81 | -0.44 | 4.12 | -0.13 | 4.25 | 3.79 | -0.46 | 3.81 | -0.44 | 4.12 | -0.13 |
| Adam Conley | FLA | 5 | 4.82 | -0.18 | 4.93 | -0.07 | 5.27 | 0.27 | 6 | 4.41 | -1.59 | 4.72 | -1.28 | 5.11 | -0.89 |
| Alex Gonzalez | TEX | 4.22 | 5.71 | 1.49 | 5.23 | 1.01 | 4.99 | 0.77 | 7.94 | 6.37 | -1.57 | 5.85 | -2.09 | 6.64 | -1.3 |
| Anibal Sanchez | DET | 4.95 | 3.94 | -1.01 | 3.94 | -1.01 | 4.65 | -0.3 | 6.6 | 3.95 | -2.65 | 4.01 | -2.59 | 6.11 | -0.49 |
| CC Sabathia | NYY | 5.23 | 3.78 | -1.45 | 3.68 | -1.55 | 4.66 | -0.57 | 4.4 | 3.84 | -0.56 | 3.7 | -0.7 | 5.03 | 0.63 |
| Chase Anderson | ARI | 4.31 | 4.2 | -0.11 | 4.09 | -0.22 | 4.1 | -0.21 | 6.89 | 3.11 | -3.78 | 2.87 | -4.02 | 2.79 | -4.1 |
| Clayton Kershaw | LOS | 2.39 | 2.21 | -0.18 | 2.09 | -0.3 | 2.19 | -0.2 | 0.92 | 1.89 | 0.97 | 1.99 | 1.07 | 1.44 | 0.52 |
| David Hale | COL | 5.69 | 3.96 | -1.73 | 3.94 | -1.75 | 5.23 | -0.46 | |||||||
| Edinson Volquez | KAN | 3.27 | 4.37 | 1.1 | 4.26 | 0.99 | 3.77 | 0.5 | 3.21 | 4.52 | 1.31 | 4.41 | 1.2 | 3.7 | 0.49 |
| Eduardo Rodriguez | BOS | 4.83 | 4.2 | -0.63 | 4.12 | -0.71 | 4.31 | -0.52 | 7.36 | 4.87 | -2.49 | 4.8 | -2.56 | 5.72 | -1.64 |
| Felix Doubront | OAK | 4.59 | 3.7 | -0.89 | 3.98 | -0.61 | 3.44 | -1.15 | 4.66 | 4.42 | -0.24 | 4.65 | -0.01 | 3.63 | -1.03 |
| Francisco Liriano | PIT | 3.19 | 3.15 | -0.04 | 2.94 | -0.25 | 3.09 | -0.1 | 4.35 | 3.42 | -0.93 | 3.07 | -1.28 | 2.87 | -1.48 |
| Garrett Richards | ANA | 3.55 | 3.96 | 0.41 | 3.87 | 0.32 | 3.76 | 0.21 | 3.59 | 3.7 | 0.11 | 3.6 | 0.01 | 3.79 | 0.2 |
| Hisashi Iwakuma | SEA | 3.86 | 3.33 | -0.53 | 3.31 | -0.55 | 4.2 | 0.34 | 2.93 | 2.82 | -0.11 | 2.89 | -0.04 | 2.81 | -0.12 |
| Jacob deGrom | NYM | 2.03 | 2.97 | 0.94 | 2.95 | 0.92 | 2.62 | 0.59 | 1.64 | 2.46 | 0.82 | 2.44 | 0.8 | 2.5 | 0.86 |
| Jake Odorizzi | TAM | 3.09 | 3.81 | 0.72 | 3.84 | 0.75 | 3.35 | 0.26 | 3.94 | 3.33 | -0.61 | 3.52 | -0.42 | 3.11 | -0.83 |
| James Shields | SDG | 3.89 | 3.42 | -0.47 | 3.43 | -0.46 | 4.18 | 0.29 | 3.77 | 3.63 | -0.14 | 3.57 | -0.2 | 3.91 | 0.14 |
| Jason Hammel | CHC | 3.1 | 3.33 | 0.23 | 3.41 | 0.31 | 3.41 | 0.31 | 4.13 | 4.32 | 0.19 | 4.29 | 0.16 | 4.73 | 0.6 |
| John Danks | CHW | 4.58 | 4.55 | -0.03 | 4.6 | 0.02 | 4.2 | -0.38 | 3.3 | 4.49 | 1.19 | 4.53 | 1.23 | 3.11 | -0.19 |
| Jordan Zimmermann | WAS | 3.34 | 3.84 | 0.5 | 3.8 | 0.46 | 3.23 | -0.11 | 3.58 | 3.21 | -0.37 | 3.13 | -0.45 | 2.92 | -0.66 |
| Kevin Gausman | BAL | 4.48 | 3.81 | -0.67 | 4.1 | -0.38 | 3.79 | -0.69 | 4.05 | 3.83 | -0.22 | 3.83 | -0.22 | 3.68 | -0.37 |
| Lance Lynn | STL | 2.95 | 3.53 | 0.58 | 3.53 | 0.58 | 3.11 | 0.16 | 3.65 | 3.99 | 0.34 | 4.15 | 0.5 | 4.28 | 0.63 |
| Matthew Wisler | ATL | 4.74 | 4.75 | 0.01 | 4.69 | -0.05 | 4.63 | -0.11 | 6.43 | 5.02 | -1.41 | 4.86 | -1.57 | 5.25 | -1.18 |
| Ryan Vogelsong | SFO | 4.15 | 4.48 | 0.33 | 4.51 | 0.36 | 4.76 | 0.61 | 4.15 | 3.02 | -1.13 | 3.19 | -0.96 | 3.88 | -0.27 |
| Mike Pelfrey | MIN | 3.7 | 4.58 | 0.88 | 4.46 | 0.76 | 3.95 | 0.25 | 2.7 | 4.61 | 1.91 | 4.42 | 1.72 | 3.47 | 0.77 |
| R.A. Dickey | TOR | 3.96 | 4.75 | 0.79 | 4.73 | 0.77 | 4.63 | 0.67 | 1.49 | 4.31 | 2.82 | 4.39 | 2.9 | 3.16 | 1.67 |
| Raisel Iglesias | CIN | 4.7 | 3.45 | -1.25 | 3.66 | -1.04 | 3.53 | -1.17 | 3.56 | 3.01 | -0.55 | 3.32 | -0.24 | 3.77 | 0.21 |
| Scott Feldman | HOU | 4.17 | 4.25 | 0.08 | 3.89 | -0.28 | 4.22 | 0.05 | 2.93 | 4.67 | 1.74 | 4.32 | 1.39 | 4.48 | 1.55 |
| Trevor Bauer | CLE | 4.35 | 3.98 | -0.37 | 4.12 | -0.23 | 4.59 | 0.24 | 5.46 | 3.92 | -1.54 | 3.9 | -1.56 | 6.27 | 0.81 |
| Tyler Cravy | MIL | 5.55 | 4.85 | -0.7 | 4.67 | -0.88 | 5.16 | -0.39 | 9.64 | 5.4 | -4.24 | 5.37 | -4.27 | 7.72 | -1.92 |
Anibal Sanchez would likely be a little less than league average with a normalized HR rate or even better with his career 8.6 HR/FB. His 13.5 K-BB% is actually a touch better than his career mark, though is worst mark since 2010. It’s all in the 15.7 HR/FB more accurately measured by his FIP than other estimators though. It’s frustrating because his issues have been difficult to figure out. There’s no direct action that anyone has been able to point to and say that’s what’s wrong. He’s allowed more than twice as many HRs this year as the last 308 innings combined over the two previous seasons.
C.C. Sabathia has league average peripheral stats, but it’s clearly not as easy as expecting everything else to regress to league average with his clearly diminished arsenal of weapons at this point. What the underlying numbers do show, however, is that the proper deployment of those remaining weapons can still lead to some modicum of success. The easy one is a 15+ HR/FB in each of the first four months of the season, none over his last two starts. His BABIP has been above .300 every month this season as well. His indicators (IFFB%, Z-Contact%) are both well worse than his career average, though his LD% is exactly where it’s been the last few years, when his BABIP has also been above .300. Clearly, he’s going to have get batters to chase off the plate because the pitches he throws over it often get hit hard. Easier said than done.
Chase Anderson – It’s just three starts totaling 15.2 IP over the last month, but he’s registered a 17.1 K-BB% with a 10.0 HR/FB and 2.5 GB/FB (23.5 Hard%). That’s the good. The bad? A .440 BABIP, 28.6 LD%, 2.0 Soft%, and 58.6 LOB%. Of course, he has to generate more weak contact, though he hasn’t allowed too much hard contact and a lot of ground balls with a very good K-BB%. A lot of this is going to regress, but which numbers and which way? Unfortunately, we don’t have the time to dig deeper today and see if some sort of change has been made recently.
Hisashi Iwakuma sees a big difference between his FIP and other estimators due to his 18.8 HR/FB, which has seen better days after a rough start as mentioned above. His ERA still runs a bit below his FIP due the unsustainably low .244 BABIP. He has a 16.0 LD%, but otherwise no helpful indicators and really needs his HR rate to remain somewhat stable to be an effective pitcher.
Jacob deGrom has an elite 21.9 K-BB% and a defense that puts a lot of effort into positioning with reasonable indicators (IFFB%, Z-Contact%, LD%), though none that are elite and point towards an ability to sustain a particularly low BABIP or the 81.6 LD% that comes with it.
Jake Odorizzi has a 7.6 HR/FB in a great park, keeping his ERA closer to his FIP with a reduced strikeout rate this year. He’s not at home or in a great park for a fly ball pitcher today.
Kevin Gausman – The 66.0 LOB% makes everything look off with nothing else out of line and a strong SwStr% that might suggest something more than a league average strikeout rate. His approach might drive you mad at times, but the talent is definitely there for more and strand rates are probably the easiest problem to correct. He’s have the 3rd lowest mark in the league with the innings to qualify.
R.A. Dickey has some great indicators and a history of low BABIPs (between .257 and .278 each of the last six years) including a 2.0 Hard-Soft% because a knuckle ball is a heck of a thing to try to square up, but the .218 BABIP and 83.7 LOB% with just a 4.8 HR/FB over his last seven starts is not a sustainable thing even for a pitcher with a non-conformist skill set.
Raisel Iglesias has suffered the consequences of a .311 BABIP and 68.4 LOB%. The BABIP doesn’t sound like much, but the Reds have a reputation for defensive suppression and none of his indicators are out of line, which suggests improvement. That should make his 17.3 K-BB% play up and drop his ERA.
BABIP Chart (2015 LG AVG – .295 BABIP – 9.4 IFFB% – 86.9 Z-Contact%)
A couple of years ago, both Dan Rosencheck and Steve Staude separately found that high Infield Fly Ball (IFFB) rates and low Zone Contact (Z-Contact) rates correlated well with lower BABIP for pitchers. I won’t pretend to know how much of the variation in BABIP can be explained by these factors, but since they seem to have some effect, here they are. See if you can use it to your advantage.
It’s presented as the difference between team and pitcher BABIP allowed because team defense can explain a lot of the variance from league average on its own. For example, if a pitcher has a much lower BABIP than his team’s allowed (red), then you look for some factors that may support it and maybe you’re onto something (check batted ball profile too).
| Pitcher | Team | Team BABIP | Pitcher BABIP | Diff | Pitcher IFFB% | Pitcher Zcontact |
|---|---|---|---|---|---|---|
| Aaron Nola | PHI | 0.321 | 0.292 | -0.029 | 10.0% | 88.9% |
| Adam Conley | FLA | 0.291 | 0.268 | -0.023 | 17.4% | 88.6% |
| Alex Gonzalez | TEX | 0.296 | 0.228 | -0.068 | 2.2% | 89.6% |
| Anibal Sanchez | DET | 0.302 | 0.277 | -0.025 | 12.4% | 85.5% |
| CC Sabathia | NYY | 0.299 | 0.330 | 0.031 | 8.5% | 89.7% |
| Chase Anderson | ARI | 0.290 | 0.300 | 0.01 | 7.6% | 88.6% |
| Clayton Kershaw | LOS | 0.300 | 0.285 | -0.015 | 12.2% | 77.9% |
| David Hale | COL | 0.314 | 0.305 | -0.009 | 3.6% | 85.5% |
| Edinson Volquez | KAN | 0.279 | 0.275 | -0.004 | 4.9% | 86.5% |
| Eduardo Rodriguez | BOS | 0.309 | 0.277 | -0.032 | 16.0% | 88.3% |
| Felix Doubront | OAK | 0.284 | 0.342 | 0.058 | 16.1% | 90.8% |
| Francisco Liriano | PIT | 0.305 | 0.279 | -0.026 | 11.6% | 82.9% |
| Garrett Richards | ANA | 0.280 | 0.269 | -0.011 | 10.1% | 88.2% |
| Hisashi Iwakuma | SEA | 0.296 | 0.244 | -0.052 | 6.3% | 91.7% |
| Jacob deGrom | NYM | 0.281 | 0.247 | -0.034 | 9.7% | 85.4% |
| Jake Odorizzi | TAM | 0.279 | 0.274 | -0.005 | 9.2% | 86.1% |
| James Shields | SDG | 0.296 | 0.306 | 0.01 | 10.9% | 84.0% |
| Jason Hammel | CHC | 0.290 | 0.265 | -0.025 | 4.4% | 86.7% |
| John Danks | CHW | 0.315 | 0.309 | -0.006 | 9.8% | 86.8% |
| Jordan Zimmermann | WAS | 0.309 | 0.306 | -0.003 | 12.4% | 89.7% |
| Kevin Gausman | BAL | 0.289 | 0.282 | -0.007 | 16.9% | 84.0% |
| Lance Lynn | STL | 0.288 | 0.323 | 0.035 | 11.6% | 86.3% |
| Matthew Wisler | ATL | 0.306 | 0.321 | 0.015 | 14.7% | 90.2% |
| Ryan Vogelsong | SFO | 0.286 | 0.274 | -0.012 | 5.6% | 92.3% |
| Mike Pelfrey | MIN | 0.298 | 0.313 | 0.015 | 7.3% | 93.0% |
| R.A. Dickey | TOR | 0.280 | 0.257 | -0.023 | 13.6% | 83.2% |
| Raisel Iglesias | CIN | 0.282 | 0.311 | 0.029 | 10.0% | 88.1% |
| Scott Feldman | HOU | 0.283 | 0.293 | 0.01 | 6.3% | 90.7% |
| Trevor Bauer | CLE | 0.292 | 0.265 | -0.027 | 14.0% | 88.0% |
| Tyler Cravy | MIL | 0.300 | 0.315 | 0.015 | 10.7% | 88.1% |
Aaron Nola – I really had to double check this because I thought I had copied the the wrong page, but the Phillies really are allowing opposing hitters a .321 BABIP. It’s really ridiculous that you have to wonder if a pitcher with league average indicators and a league average BABIP is capable of sustaining such because his defense is so bad, but that’s what’s happening here.
Francisco Liriano has all of the characteristics you look for in a low BABIP, including an elite Z-Contact%. He generates an average LD%, but tons of weak ground balls. Considering the Pirates groom pitchers for this kind of batted ball profile and shift regularly, it’s surprising that their team BABIP is this high or his BABIP would likely be better.
Pitcher Notes & Summary
Here we rank pitchers by value tiers with their overall rank in parenthesis next to the name for the top five to ten. These are not hard and rigid rankings. Everything is fluid and can changed depending on ever evolving situations throughout the day. This is the more opinionated part. If there are questions, it’ll help show you where my imaginary boundaries are drawn.
Value Tier One
Raisel Iglesias (5t) – So the Royals will hurt his K%. That’s fine. So if it goes from 24.0% to 20%, is that still worth a lower half of the board price for six innings in an otherwise average spot? Don’t forget that KC loses a big middle of the order bat in the NL too with the pitcher spot maybe adding another strikeout.
Value Tier Two
Kevin Gausman has had some success keeping the ball in the park at home and while I’m not sure that’s sustainable, the Mets are a terrible road offense and though the offense should play up a bit here, still a favorable matchup. I expect a slightly above average K% tonight and in a decent matchup, that’s worth much more than his low price tag.
Clayton Kershaw (1 – with a massive gap to #2) maxes out the price scale on several sites tonight. Find a way to fit him in cash games on single pitcher sites, while perhaps taking on more risk (as in the above two pitchers?) on multi-pitcher sites.
Value Tier Two A
C.C. Sabathia – This depends on some favorable circumstances, so check your umpire assignment. If we find it to be favorable, the Twins are a terrible road team with a 22.4 K% away from home. He has a good chance of being worth more than his low cost, especially on DraftKings. If the umpire assignment is neutral, he drops to the next tier and if negative, down to a discard.
Garrett Richards (2) hasn’t realized any of the benefits that go with it in his ERA yet, but his strikeout rate has finally begun to creep up in addition to his ability to generate weak contact frequently. Add this to a very favorable matchup and I think he’s the guy I’m paying up for after Kershaw when factoring in cost.
Value Tier Three
Chase Anderson might look a bit risky, but the park should benefit him as a HR prone pitcher and there has been some positive evidence in his K% over the last few starts, while the BABIP and strand rate have pummeled him. I think he has the upside of a quality start in a decent spot at a very low price, though with a lot of risk and less upside than some pitchers above.
James Shields (4) has a reasonable price tag in a good park against the Braves. The good park hasn’t kept balls from exiting on him all season, but the Atlanta offense might even if it causes a dip in his projected K%. I still think he gets to about league average, which should be good enough here.
Aaron Nola – The Blue Jays are cold and merely an average looking matchup here on the road vs a RHP. Aaron Nola has had a few struggles, but his underlying numbers are about league average, though he comes in at a below average price. When you have a situation that looks perfectly average at a below average price, you have identified a situation with potential value.
Jason Hammel has some great numbers this year and catches a slumping Detroit team without a DH. I can’t push him any higher though because he might get yanked in the 5th inning for no obvious reason.
Value Tier Four – These guys seem basically in line with their price tag. They are either useable and shouldn’t hurt you too much, but might not help you much either or have such a wide range of outcomes that you can’t see much benefit beyond the risk.
Hisashi Iwakuma (5t) – The obvious drawbacks are a park which may be favorable for long ball conditions tonight and the amount of pitches he’s thrown in his last two starts.
Francisco Liriano (5t) – While the weak ground balls have been consistent, he’s mixed more HR’s than you’d like at home with less consistency in his strikeout totals and comes at a high price against a team with some dangerous RH power. The lack of trust in his strikeout numbers are incredibly frustrating here.
Jacob deGrom (3) – I actually have him right on par with Kershaw in terms of K% for the top mark tonight, but he has the much more dangerous matchup at what looks to be possibly his highest cost of the season.
Anibal Sanchez – Bombs away, but maybe quite a few strikeouts too?
Jordan Zimmermann – I’m not strongly advocating his use tonight obviously, but I think the lack of price increase due to Colorado that should come with his better performance in recent starts kind of neutralizes his value here and doesn’t really make him an auto-discard like most times in Colorado.
Jake Odorizzi – There’s a lot of interesting ways this could go with the potential for strikeouts and HRs for a pitcher who hasn’t been very proficient at piling up either this year. Interesting is not always good once you get towards the top half of the board.
You can find me on twitter @FreelanceBBall for any questions, comments, or insults.
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