Advanced Stats - Pitching Charts: Tuesday, September 8th
I don’t remember it being this hard last September. Sure, teams were still expanding rosters, shutting guys down, and manipulating rotations, but you usually knew these things ahead of time. Now it seems to be chaos every day as to who’s pitching and for how long. I’m sure we all know about the Matt Harvey controversy from over the weekend and we’re already down two starters from the initial projected probables since todays prep started and I’m still not sure who’s pitching in Atlanta tonight. And we haven’t even gotten to the performances yet. It seemed like there were more negative point games for starting pitchers last week than there were the entire month prior. Oh well, at least Clayton Kershaw is pitching tonight. He costs how much on DraftKings???
Having just looked at the holiday schedule for Monday, there appears to be just four night games, so there will not be an article that day. Have a great holiday weekend and we’ll see you back here Tuesday.
Don’t forget to watch for lineups, umpire assignments, and Kevin’s weather report (and I’ll now add line movement) 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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | PHI | -3.9 | 3.94 | 5.91 | 1.22 | 1.01 | 3.64 | 3.64 | ATL | 79 | 86 | 67 | 19.8% | 7.3% | 18.9% | 11.7% | 11.1% |
| Adam Conley | FLA | 2.3 | 4.24 | 4.85 | 1.2 | 1.01 | 4.94 | 3.98 | MIL | 88 | 79 | 146 | 19.0% | 8.1% | 19.8% | 11.5% | 19.1% |
| Andrew Heaney | ANA | 2.1 | 4.12 | 5.78 | 1.05 | 0.91 | 4.19 | 4.25 | LOS | 101 | 113 | 120 | 19.2% | 6.9% | 22.4% | 10.5% | 8.8% |
| Carlos Carrasco | CLE | 0.4 | 2.73 | 6.38 | 1.76 | 1.08 | 2.81 | CHW | 84 | 92 | 104 | ||||||
| Carlos Rodon | CHW | -6.3 | 4.16 | 5.61 | 1.72 | 1.08 | 4.11 | 4.62 | CLE | 88 | 98 | 80 | 19.9% | 10.3% | 22.2% | 12.7% | 11.3% |
| Chase Anderson | ARI | 2.4 | 4.07 | 5.63 | 1.23 | 1.09 | 3.73 | 3.64 | SFO | 100 | 107 | 94 | 18.4% | 5.6% | 22.7% | 9.9% | 13.6% |
| Clayton Kershaw | LOS | 1.4 | 2.16 | 7.23 | 1.81 | 0.91 | 2.39 | 1.03 | ANA | 102 | 86 | 109 | 27.8% | 6.1% | 20.3% | 9.6% | 9.9% |
| Cole Hamels | TEX | 4.5 | 3.32 | 6.7 | 1.53 | 0.85 | 3.36 | 2.8 | SEA | 103 | 101 | 147 | 24.0% | 8.2% | 21.3% | 9.2% | 9.6% |
| Colin Rea | SDG | -7.4 | 3.79 | 4.84 | 2 | 0.84 | 3.19 | 3.9 | COL | 79 | 95 | 117 | 21.2% | 6.4% | 25.9% | 12.6% | 5.7% |
| Edinson Volquez | KAN | 8.9 | 4.22 | 6.06 | 1.51 | 1.04 | 4.35 | 4.26 | MIN | 78 | 88 | 90 | 20.7% | 7.9% | 22.6% | 9.4% | 8.0% |
| Erasmo Ramirez | TAM | 7.1 | 4.32 | 5.1 | 1.23 | 1.05 | 4.27 | 4.41 | DET | 108 | 101 | 93 | 18.1% | 7.1% | 19.1% | 11.5% | 9.4% |
| Francisco Liriano | PIT | -1.1 | 3.56 | 5.86 | 1.93 | 1.02 | 3.31 | 5.59 | CIN | 98 | 97 | 100 | 21.2% | 10.4% | 20.8% | 11.9% | 7.7% |
| Henry Owens | BOS | -1.6 | 4.47 | 5.03 | 0.55 | 1.07 | 4 | 5.72 | TOR | 104 | 128 | 118 | 20.3% | 9.9% | 18.7% | 15.7% | 9.8% |
| Jason Hammel | CHC | 4.6 | 3.46 | 5.79 | 0.98 | 0.98 | 3.4 | 4.13 | STL | 99 | 99 | 82 | 21.4% | 7.3% | 22.8% | 9.0% | 5.8% |
| Jonathan Gray | COL | -3.4 | 4.27 | 4.35 | 1.52 | 0.84 | 4 | 4.37 | SDG | 97 | 92 | 109 | 20.8% | 7.6% | 22.8% | 8.7% | 8.3% |
| Jordan Zimmermann | WAS | -4.4 | 3.49 | 6.25 | 1.14 | 1.03 | 3.57 | 3.9 | NYM | 94 | 96 | 164 | 19.6% | 7.2% | 23.3% | 12.5% | 15.1% |
| Kevin Gausman | BAL | 5.5 | 3.84 | 5.73 | 1.15 | 1.02 | 4.08 | 4.97 | NYY | 108 | 104 | 120 | 18.7% | 8.0% | 19.0% | 17.5% | 9.6% |
| Kyle Gibson | MIN | 2.3 | 4.21 | 5.92 | 2.01 | 1.04 | 4.23 | 4.29 | KAN | 109 | 103 | 134 | 15.2% | 6.8% | 18.5% | 8.9% | 9.6% |
| Masahiro Tanaka | NYY | -5.5 | 3.04 | 6.6 | 1.48 | 1.02 | 3.1 | 3.43 | BAL | 87 | 101 | 111 | 23.3% | 5.9% | 19.6% | 15.3% | 8.8% |
| Matt Boyd | DET | 2.8 | 4.94 | 4.63 | 0.67 | 1.05 | 5.2 | 6.27 | TAM | 98 | 115 | 137 | 16.7% | 8.0% | 20.7% | 17.9% | 9.5% |
| Matt Harvey | NYM | 1.1 | 3.35 | 6.64 | 1.22 | 1.03 | 3.79 | 2.2 | WAS | 104 | 97 | 147 | 24.0% | 7.3% | 19.9% | 12.8% | 7.0% |
| Matthew Wisler | ATL | -0.8 | 5.14 | 5.15 | 0.83 | 1.01 | 5.07 | 6.42 | PHI | 89 | 85 | 84 | 17.9% | 8.7% | 25.7% | 9.6% | 8.6% |
| Michael Wacha | STL | 0.8 | 3.74 | 6.03 | 1.27 | 0.98 | 3.64 | 4.07 | CHC | 93 | 97 | 137 | 22.9% | 8.2% | 18.8% | 11.7% | 10.1% |
| R.A. Dickey | TOR | -2 | 4.33 | 6.45 | 1.11 | 1.07 | 4.71 | 3.17 | BOS | 114 | 98 | 143 | 17.4% | 6.5% | 20.9% | 11.1% | 10.3% |
| Raisel Iglesias | CIN | 1.8 | 3.2 | 6.01 | 1.43 | 1.02 | 3.55 | 2.39 | PIT | 92 | 99 | 105 | 25.6% | 7.4% | 22.9% | 17.9% | 6.8% |
| Scott Kazmir | HOU | -0.3 | 3.55 | 5.97 | 1.2 | 0.93 | 3.78 | 3.72 | OAK | 100 | 96 | 117 | 19.7% | 7.3% | 20.7% | 9.1% | 6.9% |
| Sonny Gray | OAK | -6.7 | 3.57 | 6.66 | 2 | 0.93 | 3.68 | 4.02 | HOU | 92 | 100 | 126 | 20.6% | 7.3% | 19.8% | 12.4% | 7.5% |
| Taijuan Walker | SEA | -3.5 | 3.7 | 5.85 | 1.09 | 0.85 | 3.54 | 4.46 | TEX | 88 | 96 | 74 | 21.3% | 8.2% | 21.3% | 8.2% | 8.9% |
| Taylor Jungmann | MIL | -4.9 | 3.94 | 6.01 | 1.4 | 1.01 | 4.27 | 5.06 | FLA | 81 | 80 | 97 | 18.8% | 7.4% | 19.3% | 6.1% | 7.2% |
| Tim Hudson | SFO | 3.5 | 3.86 | 6.05 | 2.17 | 1.09 | 4.1 | 2.27 | ARI | 97 | 96 | 118 | 18.3% | 6.0% | 20.6% | 10.9% | 6.6% |
Aaron Nola had his worst start, or at least the shortest of his major league career, last time out, allowing two HRs and six runs against the Mets in just four innings. His 13.6 K-BB% and underlying numbers are ok, but the important thing here is that he’s facing the Braves. They may not strike out much (17.7% vs RHP), but are one of the worst offenses in baseball in any situation and especially vs RHP (7.6 HR/FB) on the road. They have a 5.3 Hard-Soft% on the season and 2.7 Hard-Soft% over the last week.
Adam Conley has an ERA just touching five through six starts and some bullpen work. His 10.6 K-BB% is a touch below average, but he’s excelled at generating weak contact (5.3 Hard-Soft%) so far. None of that is all that special, but he faces one of the worst offenses vs LHP. They’ve been hot, but not necessarily hitting the ball hard over the last week (5.7 Hard-Soft%).
Chase Anderson has been a below average (10.3 K-BB%, 13.6 Hard-Soft%) pitcher, but not a terrible one and has been slightly better in recent starts (11.7 K-BB%, 7.4 Hard-Soft% over the last month), including his last in Colorado. He faces one of the better road offenses and 2nd best vs RHP, but that’s really not saying much and they haven’t hit all that well in great hitters parks (Coors and Chase) over the last week (6.2 HR/FB), but do represent a difficult park adjusted matchup.
Clayton Kershaw has a 29.1 K-BB% and has gone at least eight innings in eight of his last 10 starts. This may be how you run a pitcher into the ground come playoff time, but you have to get there first and DFS players can reap the benefits of his usage now. He’s struck out 29 of his last 60 batters. The Angels aren’t very good vs LHP (though with just a 10.2 K-BB%), but have hit the ball hard over the last week (20.4 Hard-Soft%). They represent a favorable park adjusted matchup in a favorable park with a similar run environment to Dodger Stadium.
Cole Hamels has been inconsistent in control and command since the trade, but has struck out at least eight in three of his last four starts without allowing a HR (after five in his first two starts). He has a strong 17.7 K-BB% on the season and has handled contact well (4.3 Hard-Soft%). Also, pitching his home games in a power friendly park for his entire career, he has just a 6.5 HR/FB on the road since last season and gets a huge environmental upgrade tonight. Seattle is actually an above average offense with a 14.4 HR/FB vs LHP, but strike out a lot (23.0 K% at home, 22.3 K% vs LHP). They have been hot, but have just a 4.8 Hard-Soft% over the last week and are a slightly favorable matchup in a very negative run environment.
Colin Rea has consistently allowed hard contact (33.8 Hard-Soft%) and has a terrible defense behind him, which has led to a 28.9 LD% and it’s difficult to buy in league average K% based on his SwStr%. After that ringing endorsement, I will note that he only serves up fly balls 23.7% of the time and has a great matchup (on of the best after park adjustment today) against a very poor road offense in a great park. The Rockies are one of the worst road offenses in baseball (18.1 K-BB%).
Jason Hammel has allowed at least three ERs in five or fewer innings in three of his last four starts, but aside from a HR issue since the All-Star break (nine of his 20 HRs allowed came in his last eight starts), his xFIP and SIERA have remained the same. All but two of those starts came at home and the two road starts came in Milwaukee and at Dodger Stadium, so this will be his first start in a power suppressing environment in a while. His 25.2 K% over the last month doesn’t even do his 14.3 SwStr% justice and his 19.2 K-BB% for the season is, by far, a career high. The Cardinals are an average offense in an average run environment, but with below average power and have been poor over the last week (22.4 K%, 6.0 HR/FB), making them a slightly favorable matchup here.
Jonathan Gray is a work in progress, but has great stuff and has struck out 11 of 43 batters faced on the road. That’s an incredibly small sample size, but suggests that he can be effective away from Coors Field with ERA estimators well below his ERA overall. He has a great park adjusted matchup tonight against an offense with a 15.7 K-BB% at home and 15.0 K-BB% vs RHP with a 23.4 K% over the last week.
Jordan Zimmermann has seen his K% rise since the All-Star break, to the point where he nearly has a league average rate for the season, though his 14.5 K-BB% still pales in comparison to last season with a similar contact authority rate (10.1 Hard-Soft%). He faces a red hot offense though, that’s nearly average on the road after being one of the worst road offenses for much of the season. The Mets have a 24.3 Hard-Soft% over the last week with just a 16.5 K% and 19.7 HR/FB, representing a difficult park adjusted matchup.
Masahiro Tanaka hasn’t been much better than average from a run prevention measure……or a bat missing measure (over the last month)……or contact authority (11.4 Hard-Soft%), but HEY, he has a 17.6 K-BB% for the season and that’s well above average, right? HRs are going to be a problem, especially at home and he has an 18.6 HR/FB to go along with a 19.9 K-BB% at Yankee Stadium in his major league career and the team he faces tonight is likely to accentuate both of those statistics. They hit a lot of HRs (15.2 HR/FB vs RHP), but strike out a lot (23.8% on the road, 22.2 vs RHP). They are a poor road team and represent a rather neutral park adjusted matchup here, all things considered.
Matt Harvey is pitching in an incredibly important game for his team tonight and for all of the ruckus made about his limitations, I haven’t been able to find anything that exists beyond the normal today in such a key game for the Mets, so as far as that goes, I’d expect him to at his norm (around 100 pitches) with limitations kicking in going forward. With that said, he has merely good instead of great on the road (15.9 K-BB%) and has benefited a bit from BABIP and strand rate, but the stuff has been a bit better over the last month (26.5 K%), though a slight drop in velocity was noticed in his last start, which may have started all of this madness. It was not significant though, 95 mph on average is still good enough in most parts of the world.
Michael Wacha skipped his last start due to those evil innings limits, but the good news is that there seems to be nothing more sinister going on and he’s gone at least six innings in each of his last seven starts, so there doesn’t seem to be an in game limitation going on. His 14.5 K-BB% is a slight improvement over last season and quite similar to his 14.4 K-BB% at home since last season, but like most Cardinal pitchers, he’s kept the ball in his home yard (6.7 HR/FB since 2014) with an improvement in contact quality overall (6.2 Hard-Soft%). He gets a hot Chicago offense (22.6 HR/FB over the last week) that represents a neutral park adjusted matchup, but strikes out a lot (24.8 K% on the road, 24.0 K% vs RHP, 26.0 K% over the last week).
Raisel Iglesias has pitched seven innings with double digit strikeouts in each of his last three starts and has a higher K% than the likes of Bumgarner, Arrieta, and deGrom for the season. A 14.3 HR/FB and a home park that enhances power have held him back slightly, but he’s been a DFS All-Star over the last month to anybody paying attention. He has a perfectly neutral park adjusted matchup against a Pittsburgh team that strikes out a bit more than average (22% on the road).
Scott Kazmir returns to Oakland and after a small blip through a couple of starts not long after the trade, has been able to avoid the 2nd half swoon that did him in last season. His ERA is a bit higher over the last month and the HRs have increased, which was expected with the downgrade in park effects, but the xFIP and SIERA are the same as they’ve been all season. The favorable environment in Oakland just made him look better than he was for most the season. Luckily, he gets to revisit that environment tonight to take on a low strikeout, low power team that seems to be a slightly favorable matchup after adjustment.
Sonny Gray is a pitcher whom I feel has traditionally been over-valued in a daily fantasy setting due to a lot of his success being owed to his circumstances (great BABIP suppressing park) and while I still feel the same, there might be some extenuating circumstances today that leave him better positioned to potentially turn a profit for you. Firstly, he’s allowed 13 runs (not all earned) with just 11 strikeouts over his last three starts, but his SwStr% has remained intact. Secondly, he faces a powerful offense (14.5 HR/FB vs RHP), but one that strikes out a lot (24.2% vs RHP) in a good environment, neutralizing the overall matchup.
Tim Hudson has pitched just 2.1 relief innings since July 26th and is sporting an ugly 6.6 K-BB%. This is the end. He’s allowing harder contact and more HRs, but his SwStr% is right at his career rate as is his 2.43 GB/FB, so there may be a slow dying spark remaining, though not enough to start the fire again. He faces an average offense made to look much better by the generous park in which they will play tonight.
Taijuan Walker is not someone you can confidently project in any given performance and has not exceeded four strikeouts in three of his last four starts, but does have a 16.2 K-BB% and ERA estimators that suggest something at least slightly better than the season he has experienced. He has a 19.7 K-BB% at home since last season, but the real allure here is a cold offense (3.4 HR/FB and Hard-Soft% over the last week) traveling to Safeco tonight. They are also a poor road offense and potentially tonight’s top park adjusted matchup.
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
Andrew Heaney (.281 BABIP – 78.4 LOB% – 7.1 HR/FB) – His HR rate might be close to acceptable in a good park, but he’s had an ERA closer to his estimators over the last month and probably ends up seeing his LOB% drop a bit too as it’s close to the extreme end for a pitcher who doesn’t generate a lot of strikeouts.
Taylor Jungmann (.281 BABIP – 77.3 LOB% – 3.4 HR/FB) – He may have a great matchup tonight, but seems a bit over-priced for a guy who’s success depends on an unsustainable HR rate.
Carlos Rodon (Last 30 days – .220 BABIP – 88.8 LOB% – 17.4 HR/FB) – Overall, he has a great K%, but has walked at least three in each of his last four starts and faces a very patient team, which may preclude him from going deep enough to actually achieve the full benefit of his bat missing prowess. In addition, his SwStr% has been below average in four of his last seven starts.
NO THANK YOU (In order from least to most offensive)
Carlos Carrasco – This has nothing to do with talent or matchup, but this is a guy coming off more than a two week layoff due to a shoulder issue. You have to not only consider health and a potential level of rust, but if he’s going to be limited as well.
Edinson Volquez has allowed at least five ERs in three of his last five starts and while you might see ERA estimators that are much lower over the last month in the ERA chart below, you also want to notice that his K% has risen over the last month while his SwStr% has dropped significantly, somewhat negating much of the improvement to his estimators. That said, he’s backed by the best defense in baseball, facing the worst road offense, so he’s really close to borderline in terms of getting the full write up tonight and I guess he just almost did.
Kevin Gausman – While still maintaining the talent has been better than the results (14.3 K-BB%, 2.3 Hard-Soft%), this just may not be the spot for an incredibly frustrating pitcher.
Erasmo Ramirez – Although he’s still exhibiting a SwStr% that deserves better, it’s dropped significantly, along with his K% over the last month and he’s been hit hard (41.2 Hard%) over his last three starts. It doesn’t get any easier on the road tonight.
Francisco Liriano hasn’t struck out more than five in any of his last seven starts and although he’s still generating an elite SwStr%, he’s just walking so many batters that he can’t get to three strikes before four balls too often. He has a 4.6 K-BB% over his last five starts in which his GB% is way down (46.1% vs 51.8% for the season).
Ryan Weber seems to be someone making his debut today instead of Matthew Wisler, but since this is news that I’m just now receiving and it probably doesn’t make much of a difference, I’ve left Wisler’s stats in today so you can get some idea of what the new pitcher faces. While he has a great matchup, he seems to be nothing more than organizational depth with little upside.
Henry Owens – It started promisingly and he has some talent, but has lasted a total of 6.2 innings, allowing nine runs with six walks and eight strikeouts over 36 batters in his last two starts. He’s only exceeded five innings in two of his six starts. Oh, and a lefty against the Toronto Blue Jays.
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 | 19.9% | 6.3% | Home | 21.5% | 7.5% | L14 Days | 21.7% | 4.4% |
| Adam Conley | Marlins | 19.1% | 8.6% | Home | 15.7% | 9.6% | L14 Days | 22.7% | 9.1% |
| Andrew Heaney | Angels | 16.9% | 4.7% | Home | 16.9% | 4.4% | L14 Days | 17.0% | 1.9% |
| Carlos Carrasco | Indians | 27.0% | 5.3% | Road | 27.3% | 5.4% | L14 Days | ||
| Carlos Rodon | White Sox | 23.6% | 12.3% | Home | 23.6% | 13.6% | L14 Days | 18.8% | 12.5% |
| Chase Anderson | Diamondbacks | 18.6% | 6.9% | Home | 19.6% | 6.5% | L14 Days | 17.0% | 2.1% |
| Clayton Kershaw | Dodgers | 32.6% | 4.4% | Road | 30.1% | 5.2% | L14 Days | 48.3% | 3.3% |
| Cole Hamels | Rangers | 24.5% | 7.2% | Road | 24.6% | 7.4% | L14 Days | 31.0% | 8.6% |
| Colin Rea | Padres | 20.4% | 7.4% | Home | 21.2% | 7.1% | L14 Days | 22.7% | 9.1% |
| Edinson Volquez | Royals | 17.9% | 8.6% | Home | 16.8% | 9.3% | L14 Days | 17.8% | 6.7% |
| Erasmo Ramirez | Rays | 17.7% | 8.3% | Road | 17.2% | 7.6% | L14 Days | 18.4% | 7.9% |
| Francisco Liriano | Pirates | 25.4% | 10.6% | Road | 26.9% | 11.5% | L14 Days | 18.0% | 16.0% |
| Henry Owens | Red Sox | 21.5% | 9.6% | Home | 23.2% | 5.8% | L14 Days | 22.2% | 16.7% |
| Jason Hammel | Cubs | 22.9% | 5.6% | Road | 24.6% | 6.3% | L14 Days | 20.5% | 6.8% |
| Jonathan Gray | Rockies | 17.4% | 7.4% | Road | 25.6% | 9.3% | L14 Days | 14.9% | 8.5% |
| Jordan Zimmermann | Nationals | 21.0% | 4.1% | Home | 19.7% | 4.4% | L14 Days | 18.8% | 10.4% |
| Kevin Gausman | Orioles | 20.1% | 6.9% | Road | 19.8% | 7.7% | L14 Days | 9.1% | 6.8% |
| Kyle Gibson | Twins | 15.3% | 7.7% | Road | 14.9% | 8.6% | L14 Days | 17.0% | 6.4% |
| Masahiro Tanaka | Yankees | 24.3% | 4.4% | Home | 24.7% | 4.8% | L14 Days | 22.6% | 3.8% |
| Matt Boyd | Tigers | 14.9% | 6.9% | Home | 13.6% | 3.4% | L14 Days | 10.8% | 13.5% |
| Matt Harvey | Mets | 24.0% | 5.2% | Road | 23.2% | 7.3% | L14 Days | 34.0% | 4.0% |
| Matthew Wisler | Braves | 14.2% | 9.1% | Road | 14.8% | 9.1% | L14 Days | 14.6% | 16.7% |
| Michael Wacha | Cardinals | 21.1% | 6.8% | Home | 20.5% | 6.1% | L14 Days | 20.7% | 6.9% |
| R.A. Dickey | Blue Jays | 17.3% | 7.6% | Road | 14.7% | 7.6% | L14 Days | 21.4% | 1.8% |
| Raisel Iglesias | Reds | 27.1% | 7.3% | Home | 25.1% | 7.9% | L14 Days | 37.7% | 9.4% |
| Scott Kazmir | Astros | 22.7% | 6.8% | Road | 21.4% | 7.2% | L14 Days | 22.9% | 6.3% |
| Sonny Gray | Athletics | 20.8% | 7.6% | Home | 19.5% | 7.2% | L14 Days | 13.7% | 5.9% |
| Taijuan Walker | Mariners | 22.4% | 7.0% | Home | 26.0% | 6.3% | L14 Days | 18.0% | 8.0% |
| Taylor Jungmann | Brewers | 21.9% | 8.7% | Road | 19.6% | 9.1% | L14 Days | 17.0% | 10.6% |
| Tim Hudson | Giants | 14.2% | 4.9% | Road | 12.3% | 5.7% | L14 Days | 25.0% | 0.0% |
Combo K/BB Charts – Opponent
| Opponent | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Braves | Road | 18.7% | 6.9% | RH | 17.7% | 7.7% | L7Days | 19.2% | 10.9% |
| Brewers | Road | 20.4% | 5.8% | LH | 20.9% | 7.0% | L7Days | 15.1% | 8.2% |
| Dodgers | Road | 21.0% | 10.0% | LH | 21.0% | 9.4% | L7Days | 22.4% | 11.0% |
| White Sox | Home | 20.9% | 7.0% | RH | 20.1% | 6.4% | L7Days | 18.0% | 7.7% |
| Indians | Road | 18.7% | 8.4% | LH | 18.9% | 8.7% | L7Days | 15.7% | 6.0% |
| Giants | Road | 18.8% | 6.9% | RH | 18.4% | 7.3% | L7Days | 17.7% | 3.9% |
| Angels | Home | 20.0% | 7.5% | LH | 18.5% | 8.3% | L7Days | 17.4% | 7.6% |
| Mariners | Home | 23.0% | 7.9% | LH | 22.3% | 6.2% | L7Days | 18.3% | 11.7% |
| Rockies | Road | 24.0% | 5.9% | RH | 20.2% | 5.9% | L7Days | 18.7% | 2.7% |
| Twins | Road | 23.4% | 6.8% | RH | 21.6% | 6.9% | L7Days | 26.8% | 8.8% |
| Tigers | Home | 18.1% | 7.5% | RH | 19.8% | 6.6% | L7Days | 17.2% | 4.8% |
| Reds | Home | 18.9% | 8.9% | LH | 19.7% | 8.9% | L7Days | 18.1% | 6.6% |
| Blue Jays | Road | 20.0% | 8.3% | LH | 17.1% | 10.2% | L7Days | 17.9% | 8.5% |
| Cardinals | Home | 18.9% | 8.5% | RH | 19.3% | 7.7% | L7Days | 22.4% | 8.8% |
| Padres | Home | 22.2% | 6.5% | RH | 21.5% | 6.5% | L7Days | 23.4% | 7.3% |
| Mets | Road | 21.4% | 7.1% | RH | 20.0% | 7.7% | L7Days | 16.5% | 9.3% |
| Yankees | Home | 20.1% | 8.8% | RH | 19.6% | 8.5% | L7Days | 23.5% | 9.0% |
| Royals | Home | 14.1% | 6.6% | RH | 15.4% | 6.3% | L7Days | 14.7% | 5.3% |
| Orioles | Road | 23.8% | 6.4% | RH | 22.2% | 7.0% | L7Days | 21.9% | 8.8% |
| Rays | Road | 20.5% | 7.4% | LH | 21.7% | 7.6% | L7Days | 18.7% | 9.1% |
| Nationals | Home | 20.7% | 9.1% | RH | 21.5% | 8.7% | L7Days | 20.8% | 9.7% |
| Phillies | Home | 19.9% | 6.6% | RH | 20.3% | 5.9% | L7Days | 23.7% | 4.9% |
| Cubs | Road | 24.8% | 8.6% | RH | 24.0% | 9.1% | L7Days | 26.0% | 11.9% |
| Red Sox | Home | 16.9% | 7.5% | RH | 17.2% | 7.4% | L7Days | 16.7% | 6.8% |
| Pirates | Road | 22.0% | 6.9% | RH | 20.6% | 7.1% | L7Days | 21.1% | 6.0% |
| Athletics | Home | 16.4% | 7.5% | LH | 16.7% | 8.4% | L7Days | 18.0% | 7.5% |
| Astros | Road | 22.7% | 7.6% | RH | 24.2% | 7.4% | L7Days | 22.7% | 7.9% |
| Rangers | Road | 21.6% | 7.3% | RH | 19.1% | 8.0% | L7Days | 20.5% | 12.8% |
| Marlins | Home | 19.1% | 6.5% | RH | 19.0% | 6.2% | L7Days | 15.9% | 3.4% |
| Diamondbacks | Home | 21.1% | 8.1% | RH | 20.6% | 7.6% | L7Days | 16.8% | 9.5% |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | Phillies | 17.1% | 13.6% | 8.5% | Home | 16.9% | 19.0% | 9.5% | L14 Days | 11.8% | 18.8% | 12.5% |
| Adam Conley | Marlins | 22.8% | 12.5% | 22.5% | Home | 18.3% | 8.3% | 20.8% | L14 Days | 20.7% | 18.2% | 36.4% |
| Andrew Heaney | Angels | 21.4% | 9.9% | 7.6% | Home | 17.5% | 10.6% | 7.6% | L14 Days | 25.6% | 5.0% | 10.0% |
| Carlos Carrasco | Indians | 19.2% | 9.3% | 5.8% | Road | 18.9% | 6.3% | 7.2% | L14 Days | |||
| Carlos Rodon | White Sox | 25.1% | 12.5% | 9.1% | Home | 28.2% | 12.5% | 7.5% | L14 Days | 18.2% | 22.2% | 22.2% |
| Chase Anderson | Diamondbacks | 24.3% | 11.8% | 10.3% | Home | 22.8% | 11.0% | 9.6% | L14 Days | 23.7% | 9.1% | 45.5% |
| Clayton Kershaw | Dodgers | 20.4% | 8.7% | 12.0% | Road | 20.1% | 7.7% | 13.8% | L14 Days | 22.2% | 8.3% | 8.3% |
| Cole Hamels | Rangers | 21.5% | 10.1% | 9.8% | Road | 19.6% | 6.5% | 7.0% | L14 Days | 22.9% | 0.0% | 12.5% |
| Colin Rea | Padres | 28.9% | 11.1% | 0.0% | Home | 30.0% | 7.7% | 0.0% | L14 Days | 31.0% | 12.5% | 0.0% |
| Edinson Volquez | Royals | 18.9% | 9.0% | 6.5% | Home | 17.9% | 4.9% | 4.9% | L14 Days | 41.2% | 11.1% | 0.0% |
| Erasmo Ramirez | Rays | 20.0% | 11.3% | 10.9% | Road | 20.1% | 12.5% | 8.3% | L14 Days | 10.7% | 15.4% | 7.7% |
| Francisco Liriano | Pirates | 20.3% | 11.9% | 8.2% | Road | 19.7% | 7.5% | 9.4% | L14 Days | 15.2% | 13.3% | 6.7% |
| Henry Owens | Red Sox | 17.4% | 12.2% | 12.2% | Home | 18.4% | 26.1% | 4.3% | L14 Days | 13.6% | 13.3% | 0.0% |
| Jason Hammel | Cubs | 22.7% | 12.0% | 5.9% | Road | 23.0% | 11.2% | 5.6% | L14 Days | 25.0% | 7.1% | 0.0% |
| Jonathan Gray | Rockies | 21.8% | 7.4% | 11.1% | Road | 21.4% | 7.7% | 15.4% | L14 Days | 30.3% | 0.0% | 0.0% |
| Jordan Zimmermann | Nationals | 22.7% | 7.5% | 12.9% | Home | 22.7% | 5.9% | 11.4% | L14 Days | 26.5% | 20.0% | 40.0% |
| Kevin Gausman | Orioles | 20.9% | 9.7% | 11.9% | Road | 20.0% | 9.9% | 9.9% | L14 Days | 16.2% | 36.4% | 0.0% |
| Kyle Gibson | Twins | 19.8% | 9.7% | 11.1% | Road | 17.7% | 10.1% | 13.2% | L14 Days | 13.9% | 0.0% | 14.3% |
| Masahiro Tanaka | Yankees | 22.2% | 15.6% | 9.1% | Home | 21.1% | 18.6% | 8.5% | L14 Days | 17.9% | 12.5% | 6.3% |
| Matt Boyd | Tigers | 17.9% | 18.2% | 9.1% | Home | 18.6% | 16.7% | 5.6% | L14 Days | 25.0% | 33.3% | 16.7% |
| Matt Harvey | Mets | 18.1% | 10.9% | 10.3% | Road | 14.0% | 10.0% | 8.6% | L14 Days | 22.6% | 10.0% | 0.0% |
| Matthew Wisler | Braves | 26.2% | 12.0% | 12.0% | Road | 30.3% | 18.2% | 12.7% | L14 Days | 26.7% | 0.0% | 6.3% |
| Michael Wacha | Cardinals | 21.6% | 6.7% | 9.8% | Home | 20.9% | 6.7% | 9.2% | L14 Days | 10.0% | 10.0% | 20.0% |
| R.A. Dickey | Blue Jays | 20.3% | 10.8% | 12.8% | Road | 20.2% | 8.3% | 14.9% | L14 Days | 18.6% | 14.3% | 7.1% |
| Raisel Iglesias | Reds | 23.1% | 14.3% | 8.6% | Home | 20.5% | 9.5% | 9.5% | L14 Days | 25.9% | 50.0% | 0.0% |
| Scott Kazmir | Astros | 20.4% | 7.6% | 7.1% | Road | 22.0% | 12.0% | 5.4% | L14 Days | 25.8% | 7.7% | 0.0% |
| Sonny Gray | Athletics | 17.0% | 9.3% | 7.8% | Home | 18.3% | 11.4% | 6.5% | L14 Days | 23.1% | 12.5% | 0.0% |
| Taijuan Walker | Mariners | 23.7% | 11.4% | 10.9% | Home | 21.1% | 13.6% | 7.4% | L14 Days | 28.6% | 0.0% | 0.0% |
| Taylor Jungmann | Brewers | 20.5% | 3.4% | 6.9% | Road | 19.1% | 6.5% | 0.0% | L14 Days | 12.1% | 0.0% | 11.8% |
| Tim Hudson | Giants | 21.2% | 11.6% | 7.1% | Road | 21.8% | 12.5% | 9.2% | L14 Days | 16.7% | 0.0% | 0.0% |
Combo Batted Ball Charts – Opponent
| Opponent | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% | Split | LD% | HR/FB% | IFFB% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Braves | Road | 22.3% | 7.8% | 8.8% | RH | 22.0% | 7.6% | 9.6% | L7Days | 23.2% | 3.5% | 17.5% |
| Brewers | Road | 19.4% | 10.0% | 9.0% | LH | 18.6% | 10.9% | 7.5% | L7Days | 19.0% | 9.1% | 18.2% |
| Dodgers | Road | 21.5% | 12.9% | 10.1% | LH | 22.4% | 11.9% | 8.4% | L7Days | 26.0% | 12.5% | 8.9% |
| White Sox | Home | 21.3% | 10.9% | 9.5% | RH | 21.1% | 11.0% | 9.8% | L7Days | 18.8% | 9.7% | 6.9% |
| Indians | Road | 20.4% | 10.1% | 10.6% | LH | 23.2% | 8.5% | 6.4% | L7Days | 17.9% | 10.3% | 11.8% |
| Giants | Road | 22.2% | 11.4% | 6.0% | RH | 21.3% | 10.1% | 6.8% | L7Days | 21.8% | 6.2% | 3.1% |
| Angels | Home | 20.6% | 11.9% | 10.2% | LH | 18.1% | 9.6% | 10.4% | L7Days | 20.6% | 11.4% | 4.5% |
| Mariners | Home | 21.7% | 12.3% | 8.8% | LH | 21.6% | 14.4% | 10.6% | L7Days | 20.6% | 12.1% | 9.1% |
| Rockies | Road | 20.3% | 12.4% | 9.8% | RH | 21.4% | 14.3% | 9.4% | L7Days | 23.9% | 17.7% | 15.2% |
| Twins | Road | 19.4% | 9.1% | 10.8% | RH | 20.8% | 10.0% | 11.7% | L7Days | 17.1% | 12.3% | 14.0% |
| Tigers | Home | 21.9% | 9.7% | 9.5% | RH | 21.7% | 10.2% | 8.7% | L7Days | 20.1% | 9.6% | 11.0% |
| Reds | Home | 23.2% | 11.9% | 9.0% | LH | 22.6% | 14.3% | 7.7% | L7Days | 23.8% | 12.5% | 5.4% |
| Blue Jays | Road | 19.2% | 13.5% | 13.8% | LH | 20.3% | 13.9% | 17.5% | L7Days | 23.5% | 15.2% | 10.9% |
| Cardinals | Home | 21.8% | 8.1% | 8.4% | RH | 22.2% | 9.4% | 9.1% | L7Days | 22.3% | 6.0% | 6.0% |
| Padres | Home | 20.8% | 11.5% | 7.3% | RH | 19.6% | 10.5% | 8.3% | L7Days | 23.0% | 14.8% | 7.4% |
| Mets | Road | 22.9% | 10.8% | 10.0% | RH | 22.4% | 10.9% | 11.6% | L7Days | 22.3% | 19.7% | 4.5% |
| Yankees | Home | 19.3% | 14.3% | 12.0% | RH | 20.9% | 13.8% | 8.9% | L7Days | 16.9% | 20.9% | 14.9% |
| Royals | Home | 20.8% | 8.5% | 8.0% | RH | 21.0% | 9.1% | 9.5% | L7Days | 17.7% | 16.1% | 1.6% |
| Orioles | Road | 20.6% | 12.6% | 10.8% | RH | 20.4% | 15.2% | 9.1% | L7Days | 15.1% | 17.4% | 8.7% |
| Rays | Road | 21.0% | 10.7% | 9.8% | LH | 20.8% | 12.7% | 10.8% | L7Days | 20.7% | 15.5% | 5.2% |
| Nationals | Home | 19.6% | 13.7% | 8.5% | RH | 21.0% | 13.2% | 8.5% | L7Days | 24.1% | 18.8% | 6.3% |
| Phillies | Home | 22.1% | 10.6% | 8.4% | RH | 22.4% | 9.3% | 8.3% | L7Days | 26.3% | 7.7% | 3.8% |
| Cubs | Road | 20.7% | 11.2% | 7.4% | RH | 20.1% | 13.1% | 9.4% | L7Days | 19.4% | 22.6% | 4.8% |
| Red Sox | Home | 21.2% | 11.5% | 9.0% | RH | 20.5% | 10.2% | 10.2% | L7Days | 24.6% | 11.5% | 7.7% |
| Pirates | Road | 21.5% | 9.4% | 7.9% | RH | 21.4% | 10.1% | 6.7% | L7Days | 24.9% | 14.0% | 8.0% |
| Athletics | Home | 19.5% | 7.2% | 11.0% | LH | 19.1% | 7.5% | 11.6% | L7Days | 17.1% | 12.3% | 6.2% |
| Astros | Road | 21.7% | 11.4% | 10.9% | RH | 19.9% | 14.5% | 11.3% | L7Days | 18.8% | 15.3% | 8.5% |
| Rangers | Road | 18.5% | 10.4% | 10.1% | RH | 19.0% | 10.3% | 9.4% | L7Days | 16.8% | 3.4% | 15.5% |
| Marlins | Home | 19.2% | 8.9% | 8.9% | RH | 20.1% | 9.5% | 8.9% | L7Days | 24.6% | 8.5% | 6.4% |
| Diamondbacks | Home | 21.9% | 10.1% | 7.9% | RH | 21.7% | 10.9% | 8.8% | L7Days | 20.3% | 20.0% | 6.7% |
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 | 19.9% | 8.3% | 2.40 | 19.0% | 7.0% | 2.71 |
| Adam Conley | FLA | 19.1% | 8.3% | 2.30 | 23.2% | 9.2% | 2.52 |
| Andrew Heaney | ANA | 17.3% | 9.0% | 1.92 | 16.4% | 8.1% | 2.02 |
| Carlos Carrasco | CLE | 27.7% | 13.0% | 2.13 | 31.3% | 10.9% | 2.87 |
| Carlos Rodon | CHW | 23.6% | 10.5% | 2.25 | 24.8% | 10.6% | 2.34 |
| Chase Anderson | ARI | 16.1% | 7.5% | 2.15 | 16.7% | 8.9% | 1.88 |
| Clayton Kershaw | LOS | 33.7% | 15.9% | 2.12 | 37.2% | 17.8% | 2.09 |
| Cole Hamels | TEX | 25.2% | 13.6% | 1.85 | 24.4% | 14.9% | 1.64 |
| Colin Rea | SDG | 20.4% | 6.1% | 3.34 | 20.4% | 6.1% | 3.34 |
| Edinson Volquez | KAN | 17.9% | 9.5% | 1.88 | 19.7% | 7.7% | 2.56 |
| Erasmo Ramirez | TAM | 18.1% | 11.4% | 1.59 | 14.3% | 8.3% | 1.72 |
| Francisco Liriano | PIT | 25.7% | 13.9% | 1.85 | 18.5% | 12.6% | 1.47 |
| Henry Owens | BOS | 21.5% | 10.9% | 1.97 | 21.1% | 11.6% | 1.82 |
| Jason Hammel | CHC | 24.5% | 11.2% | 2.19 | 25.2% | 14.3% | 1.76 |
| Jonathan Gray | COL | 17.4% | 9.7% | 1.79 | 16.7% | 9.0% | 1.86 |
| Jordan Zimmermann | WAS | 19.2% | 8.1% | 2.37 | 24.6% | 10.0% | 2.46 |
| Kevin Gausman | BAL | 20.1% | 10.3% | 1.95 | 21.0% | 10.3% | 2.04 |
| Kyle Gibson | MIN | 16.6% | 9.5% | 1.75 | 15.6% | 9.8% | 1.59 |
| Masahiro Tanaka | NYY | 22.5% | 11.4% | 1.97 | 20.7% | 9.8% | 2.11 |
| Matt Boyd | DET | 14.9% | 9.1% | 1.64 | 15.2% | 9.2% | 1.65 |
| Matt Harvey | NYM | 24.0% | 11.2% | 2.14 | 26.5% | 11.9% | 2.23 |
| Matthew Wisler | ATL | 14.2% | 7.7% | 1.84 | 14.4% | 8.5% | 1.69 |
| Michael Wacha | STL | 20.6% | 10.0% | 2.06 | 20.0% | 8.6% | 2.33 |
| R.A. Dickey | TOR | 14.7% | 9.2% | 1.60 | 14.8% | 9.0% | 1.64 |
| Raisel Iglesias | CIN | 27.1% | 12.1% | 2.24 | 34.9% | 14.4% | 2.42 |
| Scott Kazmir | HOU | 22.0% | 10.7% | 2.06 | 22.4% | 10.8% | 2.07 |
| Sonny Gray | OAK | 20.7% | 9.8% | 2.11 | 14.8% | 10.3% | 1.44 |
| Taijuan Walker | SEA | 22.2% | 9.9% | 2.24 | 17.6% | 7.4% | 2.38 |
| Taylor Jungmann | MIL | 21.9% | 8.9% | 2.46 | 23.2% | 10.7% | 2.17 |
| Tim Hudson | SFO | 12.5% | 8.7% | 1.44 | 25.0% | 17.9% | 1.40 |
Clayton Kershaw – His SwStr% over the last month is nearly a league average K%. More than one of every six pitches he’s thrown has been swung on and missed.
Cole Hamels has seen a nice spike in his SwStr% over the last month and has had at least a 15.2 SwStr% in four of his last five starts with the lone exception of striking out just two of 28 Tigers with an 8.3 SwStr% three starts back.
Colin Rea saw his SwStr exceed 6.6% for the first time in his last start (9.2%). He’ll need many more like that to maintain his current league average K%.
Sonny Gray – I’m not too worried about the big dip in strikeouts as his SwStr% has actually risen slightly. He’s had a double digit rate in three of his last four starts.
Tim Hudson has a SwStr% that nearly matches his career rate. At this point, I don’t expect a major boost to his K%, but it’s there.
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 | 4.02 | 3.94 | -0.08 | 4 | -0.02 | 4.33 | 0.31 | 4.34 | 4.25 | -0.09 | 4.29 | -0.05 | 4.28 | -0.06 |
| Adam Conley | FLA | 5.02 | 4.24 | -0.78 | 4.32 | -0.7 | 4.5 | -0.52 | 5.55 | 3.85 | -1.7 | 3.76 | -1.79 | 4.05 | -1.5 |
| Andrew Heaney | ANA | 3.18 | 4.14 | 0.96 | 4.25 | 1.07 | 3.59 | 0.41 | 4.5 | 4.34 | -0.16 | 4.55 | 0.05 | 3.61 | -0.89 |
| Carlos Carrasco | CLE | 3.53 | 2.84 | -0.69 | 2.8 | -0.73 | 2.81 | -0.72 | 2.08 | 2.57 | 0.49 | 2.57 | 0.49 | 2.49 | 0.41 |
| Carlos Rodon | CHW | 4.1 | 4.16 | 0.06 | 3.89 | -0.21 | 4.02 | -0.08 | 1.85 | 3.73 | 1.88 | 3.42 | 1.57 | 3.96 | 2.11 |
| Chase Anderson | ARI | 4.26 | 4.31 | 0.05 | 4.18 | -0.08 | 4.07 | -0.19 | 4.94 | 4.21 | -0.73 | 3.93 | -1.01 | 3.76 | -1.18 |
| Clayton Kershaw | LOS | 2.18 | 2.19 | 0.01 | 2.06 | -0.12 | 2.03 | -0.15 | 0.9 | 1.79 | 0.89 | 1.72 | 0.82 | 1.07 | 0.17 |
| Cole Hamels | TEX | 3.7 | 3.4 | -0.3 | 3.31 | -0.39 | 3.39 | -0.31 | 2.89 | 3.74 | 0.85 | 3.36 | 0.47 | 2.32 | -0.57 |
| Colin Rea | SDG | 5.47 | 3.78 | -1.69 | 3.51 | -1.96 | 3.51 | -1.96 | 5.47 | 3.79 | -1.68 | 3.51 | -1.96 | 3.51 | -1.96 |
| Edinson Volquez | KAN | 3.53 | 4.36 | 0.83 | 4.26 | 0.73 | 3.75 | 0.22 | 5.52 | 3.88 | -1.64 | 3.75 | -1.77 | 3.24 | -2.28 |
| Erasmo Ramirez | TAM | 3.84 | 4.1 | 0.26 | 4.14 | 0.3 | 4.09 | 0.25 | 3.86 | 4.53 | 0.67 | 4.39 | 0.53 | 5 | 1.14 |
| Francisco Liriano | PIT | 3.4 | 3.5 | 0.1 | 3.29 | -0.11 | 3.32 | -0.08 | 5.29 | 4.96 | -0.33 | 4.8 | -0.49 | 4.56 | -0.73 |
| Henry Owens | BOS | 5.87 | 4.46 | -1.41 | 4.85 | -1.02 | 5.07 | -0.8 | 5.96 | 4.66 | -1.3 | 5 | -0.96 | 5.71 | -0.25 |
| Jason Hammel | CHC | 3.55 | 3.38 | -0.17 | 3.46 | -0.09 | 3.65 | 0.1 | 5.4 | 3.32 | -2.08 | 3.31 | -2.09 | 4.86 | -0.54 |
| Jonathan Gray | COL | 6.15 | 4.26 | -1.89 | 4.18 | -1.97 | 3.67 | -2.48 | 6.45 | 4.36 | -2.09 | 4.39 | -2.06 | 3.86 | -2.59 |
| Jordan Zimmermann | WAS | 3.38 | 3.87 | 0.49 | 3.84 | 0.46 | 3.6 | 0.22 | 3.13 | 3.26 | 0.13 | 3.33 | 0.2 | 4.59 | 1.46 |
| Kevin Gausman | BAL | 4.59 | 3.84 | -0.75 | 4.03 | -0.56 | 4.45 | -0.14 | 4.66 | 3.63 | -1.03 | 3.63 | -1.03 | 5.11 | 0.45 |
| Kyle Gibson | MIN | 3.84 | 4.24 | 0.4 | 4.05 | 0.21 | 4.12 | 0.28 | 4.13 | 4.76 | 0.63 | 4.61 | 0.48 | 3.99 | -0.14 |
| Masahiro Tanaka | NYY | 3.73 | 3.43 | -0.3 | 3.36 | -0.37 | 4.09 | 0.36 | 3.41 | 3.49 | 0.08 | 3.39 | -0.02 | 4.01 | 0.6 |
| Matt Boyd | DET | 8.36 | 4.93 | -3.43 | 5.35 | -3.01 | 6.94 | -1.42 | 8.63 | 5.19 | -3.44 | 5.65 | -2.98 | 7.02 | -1.61 |
| Matt Harvey | NYM | 2.6 | 3.35 | 0.75 | 3.37 | 0.77 | 3.33 | 0.73 | 1.71 | 2.67 | 0.96 | 2.48 | 0.77 | 2.42 | 0.71 |
| Matthew Wisler | ATL | 5.81 | 5.14 | -0.67 | 5.22 | -0.59 | 5.36 | -0.45 | 8.06 | 5.68 | -2.38 | 6.02 | -2.04 | 7.04 | -1.02 |
| Michael Wacha | STL | 2.69 | 3.79 | 1.1 | 3.69 | 1 | 3.27 | 0.58 | 1.44 | 4.12 | 2.68 | 4.21 | 2.77 | 3.5 | 2.06 |
| R.A. Dickey | TOR | 4.09 | 4.74 | 0.65 | 4.73 | 0.64 | 4.58 | 0.49 | 4.83 | 4.44 | -0.39 | 4.4 | -0.43 | 4.25 | -0.58 |
| Raisel Iglesias | CIN | 3.81 | 3.2 | -0.61 | 3.22 | -0.59 | 3.54 | -0.27 | 2.38 | 2.37 | -0.01 | 2.21 | -0.17 | 3.52 | 1.14 |
| Scott Kazmir | HOU | 2.5 | 3.86 | 1.36 | 3.8 | 1.3 | 3.37 | 0.87 | 4.45 | 3.77 | -0.68 | 3.82 | -0.63 | 4.16 | -0.29 |
| Sonny Gray | OAK | 2.36 | 3.61 | 1.25 | 3.55 | 1.19 | 3.28 | 0.92 | 4.32 | 3.91 | -0.41 | 3.87 | -0.45 | 5.3 | 0.98 |
| Taijuan Walker | SEA | 4.51 | 3.71 | -0.8 | 3.83 | -0.68 | 3.98 | -0.53 | 3.82 | 4.09 | 0.27 | 3.91 | 0.09 | 2.82 | -1 |
| Taylor Jungmann | MIL | 2.42 | 3.94 | 1.52 | 3.94 | 1.52 | 3.04 | 0.62 | 2.88 | 4.42 | 1.54 | 4.57 | 1.69 | 3.34 | 0.46 |
| Tim Hudson | SFO | 4.69 | 4.22 | -0.47 | 4.1 | -0.59 | 4.61 | -0.08 | 0 | 2.27 | 2.27 | 2.67 | 2.67 | 1.43 | 1.43 |
Adam Conley – We’ll look at his performance over the last month, in which he’s had five of his six starts for the year and a .391 BABIP along with a 13.6 HR/FB, but as was mentioned earlier, he generates a lot of weak contact. It’s been even weaker over the last month (2.8 Hard-Soft%) with a pretty standard batted ball distribution. This is all good news for his future, obviously.
Colin Rea – ERA estimators are a great tool when other information is limited, but in this case, I think we can throw a lot of it out the window. We’ve discussed both a possible error in his K% and an extremely high rate of hard contact allowed that might not allow his ERA to match up with his estimators without improvement in those areas. Numbers don’t automatically regress if a pitcher isn’t capable of frequently throwing pitchers that batters can’t hit hard.
Jason Hammel does have a 22.2 HR/FB over the last month and also a .343 BABIP predicated on a 30.3 Hard-Soft% and 32.0 LD%, but an elite SwStr% suggests this is more about location than fatigue (potentially similar to Scherzer) where some sort of mechanical adjustment may be necessary?
Jonathan Gray has a .375 BABIP that seems mostly a product of Coors Field thus far with a normal batted ball distribution and 6.6 Hard-Soft%. His ERA estimators aren’t great, but are much better than his actual ERA and I’ll guess they remain much better on the road going forward as well.
Matt Harvey has an 81.7 LOB% that is probably in line for some regression, but with a great Z-Contact% and well positioned defense, I can’t be so sure about his .261 BABIP. His 18.1 LD% is still well below average, but rose to 25% over the last month.
Michael Wacha – I’m not going to go nuts about 7.8 HR/FB or 78.0 LOB% with a league average K% in a great situation in St Louis, but can pick some bones with his 83.9 LOB% over the last month. Otherwise, I’m fine with respecting his FIP most of the time at home.
Scott Kazmir went from a park that suppresses BABIP due to all the foul ground on the field to a defense that shifts a ton, but it’s really two different ways of potentially sustaining a low, but reasonable BABIP. His FIP tells us the difference between a 7.1 HR/FB with Oakland and a 15.2 HR/FB over his last six starts, though he didn’t allow a HR in his first three Houston starts and has a 7.8 HR/FB with them through nine starts overall. The ability to continue suppressing HRs to at least some extent might mean the difference between essentially a league average pitcher or something slightly better.
Sonny Gray – While I’ll accept some degree of tomfoolery in that park and he does generate a 14.8 LD% with just a 4.9 Hard-Soft%, it all seems a little too low. He won’t be able to sustain a LD% that low going forward. Only Brett Anderson and Marco Estrada are below 17% with him and he’s been between 18-19% each of his first two seasons.
Taijuan Walker has a 68.2 LOB% and a 12.2 HR/FB, though he’s allowed just one over his last five starts.
BABIP Chart (2015 LG AVG – .295 BABIP – 9.4 IFFB% – 86.9 Z-Contact%)
Last year, 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 you have a pitcher with a much lower BABIP than his team’s allowed (red), then you look for some factors that may support it may be onto something (check batted ball profile too).
| Pitcher | Team | Team BABIP | Pitcher BABIP | Diff | Pitcher IFFB% | Pitcher Zcontact |
|---|---|---|---|---|---|---|
| Aaron Nola | PHI | 0.317 | 0.261 | -0.056 | 8.5% | 88.4% |
| Adam Conley | FLA | 0.293 | 0.318 | 0.025 | 22.5% | 86.1% |
| Andrew Heaney | ANA | 0.286 | 0.281 | -0.005 | 7.1% | 90.6% |
| Carlos Carrasco | CLE | 0.288 | 0.302 | 0.014 | 6.5% | 85.4% |
| Carlos Rodon | CHW | 0.313 | 0.324 | 0.011 | 9.1% | 85.9% |
| Chase Anderson | ARI | 0.296 | 0.306 | 0.01 | 11.1% | 88.9% |
| Clayton Kershaw | LOS | 0.298 | 0.287 | -0.011 | 10.8% | 78.2% |
| Cole Hamels | TEX | 0.295 | 0.302 | 0.007 | 13.3% | 84.2% |
| Colin Rea | SDG | 0.299 | 0.333 | 0.034 | 0.0% | 92.1% |
| Edinson Volquez | KAN | 0.285 | 0.287 | 0.002 | 5.4% | 86.9% |
| Erasmo Ramirez | TAM | 0.281 | 0.263 | -0.018 | 13.8% | 84.0% |
| Francisco Liriano | PIT | 0.301 | 0.284 | -0.017 | 9.7% | 83.6% |
| Henry Owens | BOS | 0.308 | 0.310 | 0.002 | 12.2% | 80.8% |
| Jason Hammel | CHC | 0.293 | 0.281 | -0.012 | 3.8% | 85.5% |
| Jonathan Gray | COL | 0.316 | 0.375 | 0.059 | 11.1% | 89.3% |
| Jordan Zimmermann | WAS | 0.307 | 0.306 | -0.001 | 12.2% | 89.8% |
| Kevin Gausman | BAL | 0.297 | 0.284 | -0.013 | 13.9% | 84.5% |
| Kyle Gibson | MIN | 0.301 | 0.285 | -0.016 | 8.1% | 89.5% |
| Masahiro Tanaka | NYY | 0.300 | 0.244 | -0.056 | 8.1% | 86.8% |
| Matt Boyd | DET | 0.302 | 0.363 | 0.061 | 9.1% | 83.1% |
| Matt Harvey | NYM | 0.285 | 0.261 | -0.024 | 10.3% | 83.3% |
| Matthew Wisler | ATL | 0.310 | 0.316 | 0.006 | 12.0% | 89.7% |
| Michael Wacha | STL | 0.296 | 0.272 | -0.024 | 11.8% | 84.8% |
| R.A. Dickey | TOR | 0.281 | 0.268 | -0.013 | 13.5% | 83.9% |
| Raisel Iglesias | CIN | 0.289 | 0.275 | -0.014 | 8.6% | 86.6% |
| Scott Kazmir | HOU | 0.281 | 0.266 | -0.015 | 5.2% | 86.0% |
| Sonny Gray | OAK | 0.286 | 0.243 | -0.043 | 8.8% | 88.0% |
| Taijuan Walker | SEA | 0.298 | 0.292 | -0.006 | 10.6% | 85.7% |
| Taylor Jungmann | MIL | 0.302 | 0.281 | -0.021 | 6.9% | 89.9% |
| Tim Hudson | SFO | 0.287 | 0.310 | 0.023 | 7.5% | 89.7% |
Aaron Nola has a BABIP more than 50 points below what his atrocious defense allows and with no real standout indicators either. Aside from the numbers in the chart above, he’s allowed about average contact authority, but with a 17.7 LD% that bodes well, but can’t be counted on as a true talent (LD rates experience a great amount of variance). Regression is likely, but he’s hoping a 13.6 HR/FB regresses in his favor as well or there will be problems without a strong ground ball rate.
Masahiro Tanaka – There’s really nothing in his profile to justify this low of a BABIP. He’s generating fewer ground balls this season, or actually the same amount with 4% of his line drives turning into fly balls this year, but with no increase in pop ups. A BABIP in line for regression is really saving his ERA from his HR rate at this point.
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.
It really falls apart quickly after the first few guys tonight.
Value Tier One
Clayton Kershaw (1) – This is the easy one. Good Lord, he’s broken the DraftKings pricing model today, but he might be the only easy one. While nothing is guaranteed, he’s about as close to a 25 point guarantee you can get.
Value Tier Two
Raisel Iglesias (3) – You look at the short track record and ERA and may scoff at the above average price tag, but it’s still very generous considering his elite K% in a neutral spot. I have him for the #2 projected K% behind Kershaw.
Value Tier Three
Cole Hamels (2) has been inconsistent since the trade, but is in a great position to generate strikeouts tonight in a great park at a high, but reasonable price.
Jason Hammel – The results and length haven’t been there, but the swing and miss in his game has been elite. HRs have been a major issue, but he pitches in a park that should be more forgiving than usual against a team without a lot of power.
Tim Hudson – There’s not much left in the tank and it’s a scary spot in Arizona for a guy that’s being hit harder, but he still has the same ground ball rate and SwStr% for the minimum cost. He has to be worth more than the minimum cost still, right?
Taijuan Walker – Recent strikeout rates are not encouraging, but the potential for the top park adjusted matchup at an average or below average price (FanDuel) is enticing.
Aaron Nola has been mediocre, but gets the Braves at a much more affordable price on FanDuel (and FantasyAces).
Masahiro Tanaka (4t) carries some risk in his HR rate against a powerful team vs RHP in a scary park, but should generate a few more strikeouts and shouldn’t allow many baserunners otherwise.
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.
Colin Rea – The pure numbers wanted to push him much higher, but I can’t buy into his ERA estimators considering his SwStr% and contact authority rates.
Matt Harvey (4t) – I don’t think a pitch limit will encumber him here, but I’m not 100% positive (if I were, he might be a bit higher). We may be paying the home price and getting the road performance, which is still really good.
Jonathan Gray has some potential in a great matchup on the road at a low price, even with a pitch limit.
You can find me on twitter @FreelanceBBall for any questions, comments, or insults.
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