Advanced Stats - Pitching Charts: Monday, June 22nd
Many times this year, so many pitchers have run so close together in expected value that it often becomes difficult to decide where to draw the line between useful and probably not worth your money. Today is not one of those days. The pitchers you really want or would even consider are pretty clear for the most part on a seven game slate and there’s a huge gap from them to the ones you want to load up your offense against with hardly a man in between. That makes my job a bit easier today, but I hope you’ll read anyway.
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 3 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Brett Oberholtzer | HOU | -4.1 | 4.25 | 6. | 0.93 | 0.91 | 4.32 | 3.46 | ANA | 105 | 95 | 101 | 17.5% | 6.8% | 18.0% | 6.6% | 9.5% |
| Clayton Kershaw | LOS | 5 | 2.32 | 7.12 | 1.78 | 1.05 | 2.56 | 1.84 | CHC | 87 | 111 | 104 | 28.5% | 7.6% | 20.1% | 10.9% | 8.1% |
| Drew Hutchison | TOR | 4.1 | 3.66 | 5.7 | 0.89 | 0.94 | 4.16 | 5.12 | TAM | 108 | 96 | 121 | 20.4% | 7.9% | 22.5% | 11.9% | 10.9% |
| Felix Hernandez | SEA | -4.9 | 2.74 | 6.66 | 2.11 | 0.85 | 2.68 | 4.69 | KAN | 103 | 105 | 148 | 18.4% | 6.5% | 19.3% | 11.7% | 10.0% |
| Hector Santiago | ANA | 1.6 | 4.33 | 5.42 | 0.65 | 0.91 | 4.7 | 3.03 | HOU | 103 | 103 | 146 | 25.0% | 8.1% | 18.0% | 15.8% | 9.5% |
| Joe Blanton | KAN | 13.9 | 3.82 | 5.31 | 1.36 | 0.85 | 5.19 | 3.14 | SEA | 94 | 86 | 69 | 19.9% | 8.2% | 18.1% | 8.4% | 6.9% |
| John Danks | CHW | -8.7 | 4.51 | 6.08 | 1.07 | 1.05 | 4.71 | 4.33 | MIN | 102 | 94 | 77 | 16.6% | 6.5% | 21.1% | 8.7% | 12.8% |
| Kevin Correia | PHI | -2.8 | 4.7 | 5.58 | 1.23 | 1.02 | 4.47 | 3.43 | NYY | 125 | 108 | 147 | 15.8% | 7.2% | 23.5% | 18.0% | 6.2% |
| Kyle Ryan | DET | 6.4 | 4.36 | 6.37 | 1.79 | 0.94 | 4.41 | 4.53 | CLE | 108 | 104 | 52 | 15.7% | 8.8% | 19.2% | 10.0% | 5.5% |
| Matt Andriese | TAM | 10.2 | 3.66 | 4.03 | 2.19 | 0.94 | 3.49 | 3.33 | TOR | 102 | 111 | 122 | 18.4% | 7.1% | 19.9% | 10.6% | 10.5% |
| Michael Pineda | NYY | -4.4 | 3.01 | 6.05 | 1.29 | 1.02 | 2.93 | 3.67 | PHI | 71 | 70 | 78 | 21.7% | 5.5% | 22.6% | 9.8% | 10.0% |
| Tommy Milone | MIN | 1.7 | 4.42 | 5.56 | 0.96 | 1.05 | 4.63 | 2.7 | CHW | 76 | 45 | 36 | 20.3% | 5.6% | 18.5% | 8.3% | 14.2% |
| Trevor Bauer | CLE | -5.5 | 3.99 | 5.86 | 0.82 | 0.94 | 4.11 | 4.8 | DET | 105 | 105 | 97 | 21.4% | 9.8% | 20.3% | 9.2% | 8.0% |
| Tsuyoshi Wada | CHC | 3.8 | 3.8 | 5.17 | 0.96 | 1.05 | 3.72 | 3.67 | LOS | 107 | 91 | 118 | 20.3% | 8.6% | 23.4% | 12.0% | 8.5% |
Clayton Kershaw leads all pitchers today in SIERA over the last two calendar years, Home/Road xFIP since the start of last season, and SIERA over the last two weeks. His 23.0 road K-BB% is much worse than his 30+% home rate, but that’s just how ridiculous he is. He easily has the top projected K% and K-BB% against the Cubs, who strike out 24.9% at home, though they are a bit better vs LHP (111 wRC+, 22.1 K%, but just 6.1 HR/FB). Kershaw did allow more than two ERs for the first time in five starts his last time out, but has double digit strikeouts in five of his last seven starts.
Drew Hutchison does not pitch well on the road (4.16 xFIP since last season) and that takes into consideration more than his HR rate, which we could forgive in many of the tough parks of the AL East since he’s in the one pitcher’s park tonight, but he has a career 12.3 K-BB% on the road, exactly five points less than his home mark. He might be one of the few pitchers whose worth I might have trouble deciding on tonight because it’s a good park for a fly ball pitcher. The Rays hit well at home and have been swinging the bats well in recent days.
Felix Hernandez bounced right back from the beating of his life two starts back to shut out the Giants for eight innings last time out, but his previous two starts also follow a similar pattern. It’s easy to call this a month of inconsistency for Felix and he did only strike out five of 31 in his most recent start. He does have a long track record, including a 2.68 xFIP at home (21.1 K-BB%) since last season and a 0.8 Hard-Soft% this year that means he’s still not being consistently squared up. The Royals have just a 15.9 K% vs RHP and have been red hot, striking out just 9.8% over the last week.
Joe Blanton was the name being practically screamed by the stats last time out, but it was mostly ignored because they don’t really understand small sample sizes and the difference between the bullpen and starting. Proving how smart I was, he allowed one ER without a walk or homer over five innings. Now the numbers love him again has he’s allowed just one HR over 20 innings. Kansas City may be the park and defense for him. He’s not pitching there tonight, but Seattle might be even better. There is much concern in a 21.3 Hard-Soft% though. He has one of the better matchups tonight that only improves with the park adjustment. The Mariners have a 23.4 K% at home and 22.8 K% vs RHP.
Matt Andriese didn’t start his last game, but still pitched four effective innings and that seems to be his role here as he generally pitches between three and five innings whenever he’s called on, whether he starts or not. It’s not a terrible idea as he hasn’t done a bad job. Perhaps it allows Tampa Bay to hide his flaws and allows him the best chance of success. He’s not missing a ton of bats, but has kept the walks down through 30.1 innings. Toronto is the 2nd best offense vs RHP and has been hitting the ball well overall recently, but the park effects could pull them down to nearly neutral.
Michael Pineda has been a little inconsistent since mid-May, but has gone at least six innings with at least eight strikeouts and two ERs or fewer in three of his last four starts and has the mother of all matchups tonight. The park helps the offense enough to bring it from incredible to just really good, but the Phillies are the 2nd worst road offense and worst vs RHP (3.9 Hard-Soft%, 7.0 HR/FB). Pineda has a 21.9 K-BB% at home as a Yankee.
Tommy Milone has allowed three ERs over his last 14 innings, striking out 13 of the 49 batters he’s faced, while walking just one and not allowing a HR for only the 2nd time in seven starts. What’s more important though, is he’s facing the White Sox. Do you know the other time he didn’t allow a HR? It was in his first start of the season against the White Sox. The White Sox are historically atrocious vs LHP (45 wRC+, 23.9 K%, 3.0 Hard-Soft%) this season and have been even more awful over the last week (-5.3 Hard-Soft%). Even with a positive park adjustment (Minnesota plays as an offensively friendly environment), this is by far the top matchup of the night. Milone has a K% well below league average, but compliments that with strong contact management skills (5.4 Hard-Soft% and averaging an IFFB per start).
Trevor Bauer bounced back with seven shutout innings against the Cubs last time out, but has walked at least three in nine of 13 starts and each of his last four. He doesn’t have a particularly good matchup tonight, but his favorable home park should bring it down to around neutral. The walks are a major concern though when his SwStr% is just average over the last month.
Tsuyoshi Wada has been about a league average pitcher this year, but faces a Dodger team that has struggled vs LHP, making him a somewhat of a sneaky borderline candidate tonight. I do have a major issue with the strikeout rate though, which seems so far out of whack that it may take him out of the running.
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
Brett Oberholtzer (.341 BABIP – 73.7 LOB% – 0.0 HR/FB) – He has just an 8.0 K-BB%.
Hector Santiago (.259 BABIP – 88.3 LOB – 10.1 HR/FB) – I won’t even quibble with the BABIP because of his defense, but that strand rate has a long way to go.
Kyle Ryan (_.211 BABIP – 85.4 LOB% – 17.4 HR/FB) – The high HR/FB goes a little of the way towards balancing things out, but nearly enough. He has just a 5.2 K-BB%.
NO THANK YOU
Kevin Correia – I don’t care what his numbers look like through two starts. He’s pitching in Yankee Stadium.
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% |
|---|---|---|---|---|---|---|---|---|---|
| Brett Oberholtzer | Astros | 15.4% | 4.9% | Road | 16.5% | 5.6% | L14 Days | 18.5% | 3.7% |
| Clayton Kershaw | Dodgers | 30.4% | 4.7% | Road | 29.0% | 6.0% | L14 Days | 42.0% | 8.0% |
| Drew Hutchison | Blue Jays | 22.4% | 7.2% | Road | 20.0% | 7.7% | L14 Days | 19.5% | 9.8% |
| Felix Hernandez | Mariners | 26.2% | 5.9% | Home | 26.7% | 5.6% | L14 Days | 15.0% | 10.0% |
| Hector Santiago | Angels | 20.3% | 9.6% | Home | 21.3% | 10.0% | L14 Days | 30.6% | 6.1% |
| Joe Blanton | Royals | 18.1% | 6.8% | Road | 14.3% | 9.5% | L14 Days | 19.4% | 6.5% |
| John Danks | White Sox | 15.0% | 7.2% | Road | 14.6% | 8.7% | L14 Days | 13.5% | 1.9% |
| Kevin Correia | Phillies | 12.1% | 6.4% | Road | 12.4% | 6.5% | L14 Days | 17.4% | 4.4% |
| Kyle Ryan | Tigers | 11.9% | 6.8% | Road | 8.8% | 8.8% | L14 Days | 15.4% | 5.1% |
| Matt Andriese | Rays | 15.0% | 5.3% | Home | 15.6% | 4.2% | L14 Days | 18.0% | 5.1% |
| Michael Pineda | Yankees | 23.3% | 2.9% | Home | 25.0% | 3.1% | L14 Days | 22.9% | 8.3% |
| Tommy Milone | Twins | 15.9% | 7.2% | Home | 15.2% | 7.3% | L14 Days | 26.5% | 2.0% |
| Trevor Bauer | Indians | 22.3% | 9.7% | Home | 22.0% | 9.4% | L14 Days | 25.5% | 17.0% |
| Tsuyoshi Wada | Cubs | 21.1% | 7.3% | Home | 22.9% | 6.9% | L14 Days | 25.0% | 10.0% |
Combo K/BB Charts – Opponent
| Opponent | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Angels | Home | 19.9% | 7.4% | LH | 19.7% | 8.7% | L7Days | 15.0% | 10.4% |
| Cubs | Home | 24.9% | 9.4% | LH | 22.1% | 9.6% | L7Days | 22.3% | 7.6% |
| Rays | Home | 22.0% | 7.7% | RH | 20.8% | 7.3% | L7Days | 17.7% | 7.5% |
| Royals | Road | 16.7% | 5.2% | RH | 15.9% | 5.6% | L7Days | 9.8% | 6.9% |
| Astros | Road | 24.8% | 7.3% | LH | 23.7% | 8.6% | L7Days | 29.5% | 6.7% |
| Mariners | Home | 23.4% | 8.0% | RH | 22.8% | 8.2% | L7Days | 21.1% | 10.2% |
| Twins | Home | 18.4% | 6.4% | LH | 19.2% | 7.4% | L7Days | 18.7% | 7.1% |
| Yankees | Home | 18.6% | 8.5% | RH | 19.0% | 7.9% | L7Days | 15.1% | 9.6% |
| Indians | Home | 18.8% | 10.7% | LH | 16.7% | 10.3% | L7Days | 22.4% | 11.0% |
| Blue Jays | Road | 21.6% | 7.5% | RH | 19.7% | 8.5% | L7Days | 20.6% | 11.8% |
| Phillies | Road | 19.8% | 5.7% | RH | 19.3% | 5.8% | L7Days | 19.9% | 6.9% |
| White Sox | Road | 19.2% | 5.5% | LH | 23.9% | 5.6% | L7Days | 21.3% | 6.1% |
| Tigers | Road | 21.1% | 8.3% | RH | 19.0% | 7.2% | L7Days | 18.5% | 7.1% |
| Dodgers | Road | 19.4% | 10.4% | LH | 20.3% | 8.4% | L7Days | 13.1% | 8.5% |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Brett Oberholtzer | Astros | 20.5% | 5.2% | 9.1% | Road | 19.8% | 3.4% | 7.7% | L14 Days | 7.1% | 0.0% | 13.3% |
| Clayton Kershaw | Dodgers | 21.4% | 8.4% | 11.1% | Road | 19.8% | 7.0% | 15.0% | L14 Days | 12.5% | 20.0% | 0.0% |
| Drew Hutchison | Blue Jays | 20.7% | 10.3% | 10.3% | Road | 20.5% | 10.4% | 11.4% | L14 Days | 27.6% | 17.6% | 17.6% |
| Felix Hernandez | Mariners | 18.5% | 11.9% | 9.2% | Home | 17.4% | 13.0% | 6.5% | L14 Days | 13.3% | 20.0% | 10.0% |
| Hector Santiago | Angels | 18.9% | 8.8% | 13.4% | Home | 17.6% | 8.5% | 12.1% | L14 Days | 10.0% | 21.1% | 5.3% |
| Joe Blanton | Royals | 21.5% | 19.7% | 5.3% | Road | 18.8% | 0.0% | 0.0% | L14 Days | 8.7% | 0.0% | 16.7% |
| John Danks | White Sox | 21.0% | 12.2% | 8.2% | Road | 21.3% | 9.4% | 9.9% | L14 Days | 22.0% | 5.9% | 29.4% |
| Kevin Correia | Phillies | 22.3% | 9.7% | 6.2% | Road | 18.2% | 8.2% | 5.2% | L14 Days | 38.2% | 40.0% | 0.0% |
| Kyle Ryan | Tigers | 13.8% | 13.8% | 3.4% | Road | 14.3% | 7.7% | 7.7% | L14 Days | 17.2% | 20.0% | 0.0% |
| Matt Andriese | Rays | 19.4% | 11.5% | 7.7% | Home | 24.0% | 15.8% | 10.5% | L14 Days | 20.7% | 0.0% | 0.0% |
| Michael Pineda | Yankees | 19.3% | 8.1% | 10.6% | Home | 17.7% | 9.1% | 12.5% | L14 Days | 27.3% | 20.0% | 10.0% |
| Tommy Milone | Twins | 20.7% | 11.7% | 13.4% | Home | 17.9% | 9.6% | 14.4% | L14 Days | 11.4% | 6.7% | 26.7% |
| Trevor Bauer | Indians | 21.7% | 8.8% | 8.8% | Home | 22.3% | 8.2% | 9.6% | L14 Days | 11.1% | 6.7% | 6.7% |
| Tsuyoshi Wada | Cubs | 23.2% | 9.8% | 9.8% | Home | 18.6% | 8.8% | 11.8% | L14 Days | 26.9% | 12.5% | 12.5% |
Combo Batted Ball Charts – Opponent
| Opponent | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Angels | Home | 22.1% | 11.7% | 10.1% | LH | 20.1% | 10.5% | 9.8% | L7Days | 18.3% | 8.5% | 7.0% |
| Cubs | Home | 22.4% | 9.8% | 11.3% | LH | 24.6% | 6.1% | 5.1% | L7Days | 19.9% | 14.1% | 6.3% |
| Rays | Home | 21.8% | 10.1% | 10.5% | RH | 21.7% | 9.6% | 10.3% | L7Days | 22.7% | 13.6% | 5.1% |
| Royals | Road | 24.0% | 9.7% | 10.3% | RH | 22.2% | 8.3% | 10.8% | L7Days | 20.6% | 7.2% | 13.3% |
| Astros | Road | 23.5% | 12.9% | 11.5% | LH | 20.0% | 14.7% | 9.8% | L7Days | 17.7% | 29.0% | 4.8% |
| Mariners | Home | 20.9% | 10.7% | 7.2% | RH | 19.8% | 9.9% | 6.5% | L7Days | 18.7% | 9.8% | 5.9% |
| Twins | Home | 21.6% | 10.0% | 10.3% | LH | 19.9% | 9.4% | 9.9% | L7Days | 20.5% | 5.4% | 8.9% |
| Yankees | Home | 20.0% | 16.8% | 9.3% | RH | 21.4% | 14.1% | 8.1% | L7Days | 21.0% | 19.4% | 8.3% |
| Indians | Home | 22.7% | 8.2% | 10.8% | LH | 22.3% | 7.5% | 6.2% | L7Days | 24.6% | 2.5% | 5.0% |
| Blue Jays | Road | 19.8% | 10.8% | 14.2% | RH | 18.9% | 13.1% | 13.7% | L7Days | 16.8% | 12.3% | 16.9% |
| Phillies | Road | 23.5% | 4.5% | 10.7% | RH | 22.9% | 7.0% | 9.5% | L7Days | 24.7% | 10.3% | 6.9% |
| White Sox | Road | 21.3% | 7.4% | 11.5% | LH | 20.9% | 8.4% | 9.6% | L7Days | 18.8% | 5.8% | 9.6% |
| Tigers | Road | 22.1% | 10.5% | 5.8% | RH | 22.1% | 8.9% | 7.9% | L7Days | 22.7% | 12.1% | 9.1% |
| Dodgers | Road | 20.7% | 15.5% | 7.5% | LH | 24.2% | 9.9% | 6.3% | L7Days | 27.0% | 15.2% | 3.0% |
K/SwStr Chart (2015 LG AVG – 20.2 K% – 9.6 SwStr% – 2.10 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% |
|---|---|---|---|---|---|---|---|
| Brett Oberholtzer | HOU | 16.1% | 7.7% | 2.09 | 15.3% | 7.4% | 2.07 |
| Clayton Kershaw | LOS | 32.8% | 15.1% | 2.17 | 38.0% | 17.8% | 2.13 |
| Drew Hutchison | TOR | 19.9% | 9.0% | 2.21 | 20.9% | 8.1% | 2.58 |
| Felix Hernandez | SEA | 24.4% | 10.7% | 2.28 | 22.4% | 10.7% | 2.09 |
| Hector Santiago | ANA | 22.6% | 8.8% | 2.57 | 24.3% | 8.6% | 2.83 |
| Joe Blanton | KAN | 21.0% | 11.1% | 1.89 | 23.4% | 12.1% | 1.93 |
| John Danks | CHW | 16.1% | 8.7% | 1.85 | 15.6% | 9.9% | 1.58 |
| Kevin Correia | PHI | 17.4% | 8.4% | 2.07 | 17.4% | 8.4% | 2.07 |
| Kyle Ryan | DET | 13.0% | 7.2% | 1.81 | 13.0% | 7.2% | 1.81 |
| Matt Andriese | TAM | 15.0% | 8.0% | 1.88 | 18.0% | 6.5% | 2.77 |
| Michael Pineda | NYY | 25.8% | 11.5% | 2.24 | 25.2% | 11.5% | 2.19 |
| Tommy Milone | MIN | 15.0% | 6.8% | 2.21 | 17.6% | 7.3% | 2.41 |
| Trevor Bauer | CLE | 24.4% | 10.2% | 2.39 | 23.5% | 9.3% | 2.53 |
| Tsuyoshi Wada | CHC | 24.4% | 6.3% | 3.87 | 20.2% | 5.5% | 3.67 |
Tsuyoshi Wada is our only complaint today. Miguel Montero (+6.7 RAA) is a terrific framer, but nobody is this good. He had a much higher SwStr last year (8.6%) with a much lower K rate (19.7%). He’s exceeded even a 6.0 SwStr% only once in his last five starts.
ERA Estimators Chart (2015 LG AVG – 3.88 ERA – 3.80 SIERA – 3.88 xFIP – 3.88 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Brett Oberholtzer | HOU | 2.73 | 4.36 | 1.63 | 4.24 | 1.51 | 2.76 | 0.03 | 2.7 | 4.4 | 1.7 | 4.33 | 1.63 | 2.72 | 0.02 |
| Clayton Kershaw | LOS | 3.29 | 2.3 | -0.99 | 2.13 | -1.16 | 2.57 | -0.72 | 1.56 | 1.87 | 0.31 | 1.93 | 0.37 | 2.09 | 0.53 |
| Drew Hutchison | TOR | 5.33 | 3.84 | -1.49 | 3.83 | -1.5 | 4.02 | -1.31 | 4.08 | 3.64 | -0.44 | 3.6 | -0.48 | 3.76 | -0.32 |
| Felix Hernandez | SEA | 3.08 | 3.07 | -0.01 | 3.05 | -0.03 | 3.64 | 0.56 | 4.25 | 3.69 | -0.56 | 3.43 | -0.82 | 4.1 | -0.15 |
| Hector Santiago | ANA | 2.77 | 4.06 | 1.29 | 4.51 | 1.74 | 4.39 | 1.62 | 3.51 | 3.76 | 0.25 | 4.44 | 0.93 | 4.87 | 1.36 |
| Joe Blanton | KAN | 1.8 | 2.93 | 1.13 | 3.11 | 1.31 | 2.5 | 0.7 | 1.69 | 2.83 | 1.14 | 3.09 | 1.4 | 1.79 | 0.1 |
| John Danks | CHW | 5.04 | 4.43 | -0.61 | 4.45 | -0.59 | 4.51 | -0.53 | 4.94 | 4.05 | -0.89 | 3.76 | -1.18 | 3.49 | -1.45 |
| Kevin Correia | PHI | 1.69 | 3.41 | 1.72 | 2.82 | 1.13 | 4.6 | 2.91 | 1.69 | 3.43 | 1.74 | 2.82 | 1.13 | 4.6 | 2.91 |
| Kyle Ryan | DET | 3.26 | 4.8 | 1.54 | 4.66 | 1.4 | 5.69 | 2.43 | 3.26 | 4.8 | 1.54 | 4.66 | 1.4 | 5.69 | 2.43 |
| Matt Andriese | TAM | 3.26 | 3.65 | 0.39 | 3.77 | 0.51 | 3.86 | 0.6 | 0 | 3.33 | 3.33 | 3.28 | 3.28 | 2.27 | 2.27 |
| Michael Pineda | NYY | 3.54 | 2.65 | -0.89 | 2.57 | -0.97 | 2.68 | -0.86 | 3.94 | 3.09 | -0.85 | 2.93 | -1.01 | 3.94 | 0 |
| Tommy Milone | MIN | 3.67 | 4.64 | 0.97 | 4.59 | 0.92 | 5.29 | 1.62 | 2.37 | 3.71 | 1.34 | 3.66 | 1.29 | 4.1 | 1.73 |
| Trevor Bauer | CLE | 3.22 | 3.98 | 0.76 | 4.15 | 0.93 | 3.61 | 0.39 | 3.09 | 4.14 | 1.05 | 4.31 | 1.22 | 4.2 | 1.11 |
| Tsuyoshi Wada | CHC | 3.68 | 3.63 | -0.05 | 3.57 | -0.11 | 4.06 | 0.38 | 3.65 | 4.19 | 0.54 | 3.97 | 0.32 | 4.2 | 0.55 |
Clayton Kershaw now has a BABIP (.307) within the normally expected range and not too far from his team’s allowed mark, but with exceptional indicators in the BABIP chart below, I’d expect further improvement in that area. His 16.7 HR/FB is more than double any mark he’s had since 2008. Further improvement to his BABIP and HR/FB should also lift a 71.3 LOB%.
Drew Hutchison has decreased both his BABIP and HR/FB very slightly over the last month, but has seen significant improvement to his LOB%. Each of those numbers are still slightly out of an accepted range for the season though, which is why we still see a large gap between his season ERA and estimators. The HR’s could be an issue in Toronto and while he has some great indicators and defensive help on the BABIP, his 25.1 LD% has to improve.
Michael Pineda has an 11.8 HR/FB, which is appropriate for Yankee Stadium, but a 1.78 GB/FB, which helps keep those HRs down. The .335 BABIP is more of an issue here. It comes with a normal LD rate (19.9%), but 30.3% of his batted balls have been hit hard. That’s not the worst mark in the league, but it is worse than the average. When we combine that with otherwise mediocre indicators and not much help from the defense, it’s not terribly surprising what we see here, though there’s still some room for improvement.
Tommy Milone has a .246 BABIP, 80.9 LOB%, and 14.8 HR/FB, all of which could see adjustment one way or another. For a guy with exactly a 1.0 GB/FB, that HR rate represents trouble and although Minnesota plays up for offense, it doesn’t for power, so that’s got to be concerning. The lower BABIP makes some sense as he picks up a little more than one free out on a pop up per start and only allows hard contact on 24.6% of batted balls. He may be able to maintain somewhat of a lower BABIP, but expect his future ERA to trend closer to four and potentially above with just a 7.5 K-BB% to add to the equation. I would only attempt to use him in the best of matchups (like today) and never in a power friendly park.
Trevor Bauer has an above average IFFB% and low 17.5 LD%, but he pitches for Cleveland, a team who it often seems forgets to take their gloves into the field with them and that’s with an improvement this year. I wouldn’t have a much of a problem here on a good defensive team, but just don’t see how this is sustainable with Cleveland. I have less of an issue with a 7.2 HR/FB as Cleveland is a park tough on RH, but not LH power, so maybe we see that come up a little towards his 8.7 HR/FB last year. As an extreme fly ball pitcher (0.79 HR/FB), that could get him to around 20 HRs, but might also be another reason his BABIP is lower (infield rarely touches the ball with a 36.5 GB% and above average K rate.
BABIP Chart (2015 LG AVG – .293 BABIP – 9.5 IFFB% – 86.8 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 |
|---|---|---|---|---|---|---|
| Brett Oberholtzer | HOU | 0.280 | 0.341 | 0.061 | 10.7% | 91.7% |
| Clayton Kershaw | LOS | 0.296 | 0.307 | 0.011 | 11.1% | 76.4% |
| Drew Hutchison | TOR | 0.280 | 0.325 | 0.045 | 15.7% | 85.8% |
| Felix Hernandez | SEA | 0.284 | 0.241 | -0.043 | 14.5% | 87.7% |
| Hector Santiago | ANA | 0.277 | 0.259 | -0.018 | 13.4% | 86.1% |
| Joe Blanton | KAN | 0.275 | 0.300 | 0.025 | 16.7% | 89.7% |
| John Danks | CHW | 0.322 | 0.317 | -0.005 | 12.1% | 84.5% |
| Kevin Correia | PHI | 0.308 | 0.294 | -0.014 | 0.0% | 91.7% |
| Kyle Ryan | DET | 0.285 | 0.211 | -0.074 | 0.0% | 87.9% |
| Matt Andriese | TAM | 0.280 | 0.314 | 0.034 | 7.7% | 85.3% |
| Michael Pineda | NYY | 0.305 | 0.335 | 0.03 | 8.8% | 85.7% |
| Tommy Milone | MIN | 0.296 | 0.246 | -0.05 | 14.8% | 89.7% |
| Trevor Bauer | CLE | 0.316 | 0.263 | -0.053 | 12.4% | 88.0% |
| Tsuyoshi Wada | CHC | 0.295 | 0.299 | 0.004 | 11.1% | 87.8% |
Felix Hernandez has a strong, or at least well positioned, defense behind him, which he combines with a 2.53 GB/FB and 17.4 LD% that isn’t much lower than his career average. In addition he has a better than average and in fact elite IFFB% for the first time in his career on the few fly balls he does allow. With a 0.8 Hard-Soft%, the expectation is that most of those ground balls are weakly hit. It’s difficult to buy into a BABIP this low, but this is the blueprint to sustain such a thing.
Pitcher Notes & Summary
Clayton Kershaw is the clear top of the class tonight. He’s in a tougher environment against a team that hits LHP well, so there’s the potential for a HR or even two tonight, but his K rate potential rises as well against Cubs.
Felix Hernandez should be fine at home, but takes on the low strikeout Royals after not having exceeded six Ks in any of his last four starts. Where it’s tough to expect more than a league average K%, it’s a dilemma to decide whether or not to pay such a high price. In fact, I have him as the #3 overall pitcher tonight behind both Kershaw and Pineda.
Joe Blanton – I ignored the numbers due to sample size last time and they still exist with only one start, but he’s always had a great K/BB ratio, is in a great park, has a great outfield defense, and shows up at or near minimum price across the board. I really don’t have much of a problem with a dumpster diving special here.
Matt Andriese would be my other dumpster diving option tonight. The issue would be Tampa Bay not allowing him to go deep enough for a win, but four or five innings at max effort could be worth the minimum here.
Michael Pineda has pitched well in three of his last four starts and has a great matchup even in a tough park. He’s struck out 17 of his last 50 at Yankee Stadium, allowing just two runs over 13.1 IP against better teams (because everyone is better than the Phillies). As mentioned, I have Pineda far behind Kershaw, but ahead of Felix as my #2 overall tonight and a solid value across the board.
Tommy Milone has an absurdly amazing matchup against the White Sox. Anyone who can reach the plate with their left hand would have an amazing matchup against the White Sox. Milone has a lot of future regression in his profile, but is affordable and should be worthwhile tonight. The White Sox are so bad vs LHP, that I’d put his value (not overall expectation of course) on par with Kershaw tonight.
Trevor Bauer – I don’t think I have enough confidence in him at a mid-range or higher price.
Tsuyoshi Wada – This could be a nice sneaky spot if only I believed more in his K rate. It’s just so far off that I’m not sure how much value is left, even at a very affordable price against a below average offense vs LHP.
You can find me on twitter @FreelanceBBall for any questions, comments, or insults.
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