Advanced Stats - Pitching Charts: Saturday, April 16th
It’s the weekend. You don’t want to read a long winded intro on Saturday followed by several thousand words about pitchers and I don’t want to write it either. Let’s make us both happy and get to the action. We’re covering seven late games tonight. I’m still deciding whether to carry on showing 2015 season stats for the rest of April or convert entirely to 2016 stats on Monday. Any thoughts would be appreciated.
New season changes to the article were outlined on Opening Day, which you can find here so we won’t repeat those again. Park factors were supposed to be updated over the weekend, but Seamheads.com still seems to be behind, so we’ll give it a few more days before searching for another avenue.
Don’t forget to check lineups, umpire assignments, line movement, 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 stats 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 used here.
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 2015 season. Opp team offensive stats are wRC+.
| 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+ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | PHI | 3.42 | 6.08 | 1.4 | 1.01 | 2.99 | 2.09 | WAS | 109 | 88 | 111 | |
| Andrew Cashner | SDG | 3.95 | 6.04 | 1.5 | 0.84 | 3.02 | 3.71 | ARI | 82 | 86 | 63 | |
| Bud Norris | ATL | 3.99 | 5.67 | 1.17 | 1.01 | 4.7 | 4.7 | FLA | 106 | 97 | 103 | |
| Colby Lewis | TEX | 4.34 | 6.05 | 0.75 | 1.08 | 4.66 | 4.15 | BAL | 170 | 166 | 163 | |
| Collin McHugh | HOU | 3.63 | 6.19 | 1.27 | 1.01 | 3.83 | 5.49 | DET | 126 | 131 | 110 | |
| Johnny Cueto | SFO | 3.48 | 6.9 | 1.24 | 0.89 | 3.77 | 3.69 | LOS | 100 | 108 | 93 | |
| Jon Niese | PIT | 4.03 | 6.07 | 1.84 | 0.91 | 4.04 | 3.21 | MIL | 72 | 74 | 76 | |
| Justin Verlander | DET | 4.08 | 6.44 | 0.89 | 1.01 | 4.02 | 5.15 | HOU | 110 | 112 | 112 | |
| Max Scherzer | WAS | 2.84 | 6.8 | 0.83 | 1.01 | 2.63 | 3.76 | PHI | 53 | 75 | 62 | |
| Scott Kazmir | LOS | 3.88 | 5.87 | 1.16 | 0.89 | 4.01 | 3.3 | SFO | 95 | 86 | 94 | |
| Shelby Miller | ARI | 4.36 | 6.05 | 1.19 | 0.84 | 4.44 | 4.45 | SDG | -3 | 50 | 69 | |
| Taylor Jungmann | MIL | 4.19 | 5.48 | 1.42 | 0.91 | 4.49 | 5.39 | PIT | 105 | 112 | 105 | |
| Tom Koehler | FLA | 4.39 | 5.95 | 1.2 | 1.01 | 4.2 | 4.49 | ATL | 45 | 68 | 57 | |
| Yovani Gallardo | BAL | 4.24 | 5.75 | 1.67 | 1.08 | 4.1 | 5.1 | TEX | 55 | 77 | 93 |
Aaron Nola has struck out 17 of his first 52 batters, though he’s faced two poor offenses (SD, CIN) and his SwStr% suggests something much more average. He tops out in the low 90s, but already has strong secondary stuff, including a curveball he throws about a quarter of the time, which gets more than 20% whiffs. He’s had a bit of a HR issues, allowing one in each start and carrying a 15.1 HR/FB through 91.2 career innings. Washington has slightly under-achieved against RHP because they carry only two regulars (Murphy & Harper) who have been above average hitters against them. All of their RH batters have struggled and Dusty Baker continues to force “(player-popup)Michael Taylor”:/players/michael-taylor-11510’s .275 career OBP to the top of the lineup.
Andrew Cashner has started 2016 roughly after a disappointing 2015 season. The underlying numbers through two starts tell a bit of a different story. He’s carrying a .429 BABIP with a 34.5 LD%, though just a 24.1 Hard% and has struck out nearly a quarter of the batters he’s faced, allowing one HR. At home since last season he’s again struck out a quarter of batters faced with a standard 10.3 HR/FB. The hard contact one third on a third of his batted balls has been a bit much though. Arizona is a tough offense at home, but much more pedestrian on the road, as there are only a couple of batters that need to be treaded through carefully in the middle of the order.
Johnny Cueto lasted nearly four times through the Dodgers batting order in his last start, which is very rare in this day and age, though it only cost him 104 pitches. He struck out eight of 34 batters and just three of 21 batters hit balls classified as hard, but LA ended up with 10 hits and six runs. The underlying numbers are pretty close to what they normally are, though since leaving Cincinnati, he’s been underperforming against them instead of beating them. Early velocity is down about a mile per hour, but it’s not a concern yet and hasn’t affected his SwStr%. The Dodgers have already seen a lot of him in his last start and are a tough offense at home against RHP.
Max Scherzer against the Phillies is about as easy as today gets from an analysis standpoint. The results haven’t exactly been there after two starts against Atlanta, but his velocity and SwStr% are both in line with his career rates and he has a -18.2 Hard-Soft%. His BABIP is .226, but he’s only stranded 71.4% of his runners? I’m confident we’ll see the expected version of him sooner rather than later.
Tom Koehler walks too many batters, generally allows too much hard contact (17.4 Hard-Soft%), and misses bats at a below league average rate. He’s a back end of the rotation starter if that. Why are we talking about him then? He’s facing the Braves, they have been terrible, and many of the other pitchers on the board might make you sick (as you’ll read below).
NO THANK YOU (In order from least to most offensive)
Collin McHugh followed up a serious stinker with seven shutout innings against the Royals, but neither was entirely what they seemed. A matchup against a tough Detroit lineup makes me hesitant to pay a higher than average price for him.
Jon Niese has struck out 12 of 47 batters on an 8.2 SwStr% and is not projected to do as much going forward. He’s allowed three HRs and evenly split fly balls and grounders, though he’s been nearly a two to one ground baller through most of his career. The Brewers strike out a lot, but have a lot of RH power. Pittsburgh normally crushes RH power, but it’s not impossible and I’m not buying into the early upside in his strikeout rate yet.
Justin Verlander is now down to 92.6 mph on average through two starts in which he’s allowed 40% hard contact. The good news is his SwStr% is on par with last season, though that only projects slightly better than league average. The Astros may help him generate a few more strikeouts than he has been, but these are pretty marginal offenses that have hit him hard so far and the Astros are a little scary here in their home park for one of the higher prices on the board.
Scott Kazmir has not started strong for once and his velocity is down a mile per hour to the point where he usually finishes years, not starts them. Again, this is not really a point of severe concern after two starts, but it’s not really a reason for enthusiasm either. He easily dispatched the Padres in his first start, but that’s something we could probably trust a high school pitcher to do at this point. These Giants are a good offense and they blasted him for three HRs at home last time out. His SwStr% is slightly below average, but that K% is up so far. That’s not really a big deal either yet and I see him as more likely than not to be ok, noting that his peripherals suggested he was merely ok last year too and not the All Star his 3.10 ERA projected. I struggle to justify paying over $8K for just ok against one of the better offenses in baseball though.
Shelby Miller has been a disaster through two starts in Arizona. The matchup gets easier for him tonight (about as easy as it gets), but, like several of tonight’s pitchers, it’s another arm that is difficult to justify paying for considering a two mph drop in velocity and a mere 5.4 SwStr% (though it was 9.6% in his second start). Again, it’s probably not right to be overly concerned about anything you see over just two starts, but he really projects as a middle or the rotation pitcher and was over-priced to being with. We all knew the Diamondbacks overpaid when looking at the underlying metrics from last season. It’s a shame you can’t confidently take advantage of a matchup with the Padres because they’re about as easy as it gets so far.
Taylor Jungmann has induced four swinging strikes in 140 pitches thrown this season and his velocity has also cratered two mph to just below 90 mph on average. Are we sensing a theme on today’s pitchers yet? Although over half his contact has been kept on the ground so far, nearly half of his contact (44.4%) has been hit hard and he’s walked as many has he’s struck out (three) through two starts.
Yovani Gallardo has not hit 90 mph on a single one of his 185 pitches yet and is also down 2 mph on average. His K-BB% was in single digits last season, but at least he was generating ground balls. What the hell happened to this guy? He used to be good.
K/BB Chart
Pitcher and Opponent K% & BB% for titled splits, similar to the Main Chart.
| Pitcher | Team | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | Phillies | L2 Years | 23.0% | 5.1% | Home | 25.7% | 5.3% | L14 Days | 32.7% | 0.0% |
| Andrew Cashner | Padres | L2 Years | 19.3% | 7.2% | Home | 25.3% | 6.3% | L14 Days | 23.8% | 7.1% |
| Bud Norris | Braves | L2 Years | 19.9% | 7.9% | Road | 17.8% | 9.8% | L14 Days | 14.8% | 7.4% |
| Colby Lewis | Rangers | L2 Years | 17.1% | 5.7% | Home | 16.5% | 5.6% | L14 Days | 21.7% | 8.7% |
| Collin McHugh | Astros | L2 Years | 21.9% | 6.4% | Home | 20.4% | 5.6% | L14 Days | 10.8% | 8.1% |
| Johnny Cueto | Giants | L2 Years | 22.6% | 5.8% | Road | 18.4% | 4.7% | L14 Days | 20.0% | 3.3% |
| Jon Niese | Pirates | L2 Years | 16.4% | 6.4% | Home | 15.1% | 6.2% | L14 Days | 25.5% | 4.3% |
| Justin Verlander | Tigers | L2 Years | 19.2% | 6.9% | Road | 21.0% | 4.5% | L14 Days | 15.2% | 8.7% |
| Max Scherzer | Nationals | L2 Years | 29.1% | 5.5% | Road | 32.6% | 3.7% | L14 Days | 25.5% | 9.8% |
| Scott Kazmir | Dodgers | L2 Years | 20.5% | 7.0% | Home | 21.9% | 8.8% | L14 Days | 22.5% | 2.5% |
| Shelby Miller | Diamondbacks | L2 Years | 18.2% | 8.7% | Road | 16.9% | 8.6% | L14 Days | 16.0% | 6.0% |
| Taylor Jungmann | Brewers | L2 Years | 20.6% | 9.4% | Road | 19.5% | 10.4% | L14 Days | 9.1% | 9.1% |
| Tom Koehler | Marlins | L2 Years | 18.4% | 9.3% | Home | 19.0% | 9.7% | L14 Days | 20.7% | 13.8% |
| Yovani Gallardo | Orioles | L2 Years | 16.5% | 7.8% | Road | 15.9% | 7.2% | L14 Days | 16.3% | 9.3% |
K/BB Chart – Opponent
| Opponent | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Nationals | Road | 21.6% | 8.0% | RH | 21.1% | 9.2% | L7Days | 20.8% | 7.9% |
| Diamondbacks | Road | 19.7% | 8.5% | RH | 21.3% | 6.2% | L7Days | 21.1% | 6.2% |
| Marlins | Home | 15.5% | 9.3% | RH | 20.4% | 9.5% | L7Days | 22.2% | 10.1% |
| Orioles | Road | 23.6% | 10.1% | RH | 21.8% | 9.2% | L7Days | 22.1% | 8.7% |
| Tigers | Road | 20.9% | 8.0% | RH | 26.8% | 7.9% | L7Days | 19.5% | 10.2% |
| Dodgers | Home | 20.3% | 6.3% | RH | 20.4% | 5.4% | L7Days | 21.3% | 6.5% |
| Brewers | Road | 27.2% | 11.3% | LH | 29.5% | 17.8% | L7Days | 27.7% | 12.1% |
| Astros | Home | 27.0% | 12.4% | RH | 27.3% | 9.8% | L7Days | 26.6% | 12.5% |
| Phillies | Home | 23.3% | 10.4% | RH | 21.5% | 6.7% | L7Days | 23.5% | 9.0% |
| Giants | Road | 13.6% | 6.4% | LH | 19.4% | 4.2% | L7Days | 17.0% | 4.9% |
| Padres | Home | 26.7% | 3.8% | RH | 28.2% | 5.8% | L7Days | 26.8% | 7.4% |
| Pirates | Home | 17.8% | 11.0% | RH | 17.1% | 10.9% | L7Days | 16.2% | 10.3% |
| Braves | Road | 22.2% | 7.4% | RH | 23.2% | 11.6% | L7Days | 22.9% | 9.7% |
| Rangers | Home | 27.0% | 9.6% | RH | 22.8% | 8.4% | L7Days | 23.5% | 4.2% |
Batted Ball Chart
Pitcher and Opponent Batted Ball stats.
| Pitcher | Team | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Aaron Nola | Phillies | L2 Years | 28.0% | 15.1% | 10.2% | 2016 | 28.8% | 15.1% | 9.6% | Home | 25.4% | 21.6% | 8.4% | L14 Days | 22.9% | 15.4% | 14.3% |
| Andrew Cashner | Padres | L2 Years | 30.2% | 9.6% | 12.6% | 2016 | 30.2% | 11.5% | 12.6% | Home | 33.9% | 10.3% | 17.2% | L14 Days | 24.1% | 10.0% | 3.4% |
| Bud Norris | Braves | L2 Years | 33.4% | 12.9% | 18.3% | 2016 | 36.9% | 16.7% | 22.1% | Road | 35.6% | 14.8% | 19.3% | L14 Days | 33.3% | 6.7% | 23.8% |
| Colby Lewis | Rangers | L2 Years | 34.9% | 9.5% | 21.0% | 2016 | 33.3% | 8.9% | 19.7% | Home | 32.2% | 9.5% | 21.4% | L14 Days | 37.5% | 13.3% | 18.7% |
| Collin McHugh | Astros | L2 Years | 25.7% | 8.8% | 3.7% | 2016 | 25.1% | 8.9% | 3.4% | Home | 22.5% | 6.8% | -0.9% | L14 Days | 17.2% | 0.0% | 0.0% |
| Johnny Cueto | Giants | L2 Years | 24.8% | 9.2% | 2.5% | 2016 | 28.7% | 9.5% | 8.7% | Road | 30.1% | 10.1% | 10.2% | L14 Days | 17.8% | 0.0% | -4.4% |
| Jon Niese | Pirates | L2 Years | 30.0% | 12.0% | 13.0% | 2016 | 29.7% | 14.3% | 10.5% | Home | 34.5% | 17.1% | 15.1% | L14 Days | 28.1% | 21.4% | 6.2% |
| Justin Verlander | Tigers | L2 Years | 26.6% | 7.6% | 7.2% | 2016 | 23.0% | 7.5% | 4.1% | Road | 17.7% | 7.8% | -5.5% | L14 Days | 40.0% | 6.3% | 11.4% |
| Max Scherzer | Nationals | L2 Years | 28.9% | 9.2% | 10.0% | 2016 | 28.1% | 10.5% | 7.2% | Road | 27.7% | 10.8% | 3.3% | L14 Days | 21.2% | 16.7% | -18.2% |
| Scott Kazmir | Dodgers | L2 Years | 24.9% | 9.9% | 7.7% | 2016 | 25.7% | 10.2% | 6.8% | Home | 23.5% | 4.1% | 3.6% | L14 Days | 13.8% | 25.0% | -3.4% |
| Shelby Miller | Diamondbacks | L2 Years | 30.9% | 8.3% | 11.9% | 2016 | 26.7% | 6.4% | 5.4% | Road | 27.2% | 7.8% | 3.4% | L14 Days | 43.6% | 31.3% | 28.2% |
| Taylor Jungmann | Brewers | L2 Years | 29.5% | 10.0% | 10.4% | 2016 | 28.3% | 9.9% | 8.8% | Road | 33.8% | 13.2% | 17.6% | L14 Days | 44.4% | 11.1% | 29.6% |
| Tom Koehler | Marlins | L2 Years | 33.5% | 9.2% | 17.2% | 2016 | 34.5% | 10.9% | 18.5% | Home | 35.5% | 8.1% | 19.6% | L14 Days | 21.1% | 0.0% | -5.2% |
| Yovani Gallardo | Orioles | L2 Years | 26.7% | 10.4% | 10.1% | 2016 | 25.5% | 8.8% | 10.1% | Road | 21.6% | 8.7% | 6.9% | L14 Days | 9.4% | 0.0% | -6.2% |
Batted Ball Charts – Opponent
| Opponent | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Nationals | Road | 33.0% | 13.3% | 17.1% | RH | 30.8% | 11.5% | 13.6% | L7Days | 30.5% | 12.3% | 11.7% |
| Diamondbacks | Road | 31.0% | 13.8% | 12.0% | RH | 31.6% | 14.3% | 13.4% | L7Days | 28.7% | 15.4% | 9.4% |
| Marlins | Home | 22.9% | 4.8% | -5.2% | RH | 23.1% | 3.6% | -5.0% | L7Days | 22.4% | 9.1% | -6.7% |
| Orioles | Road | 37.7% | 22.2% | 18.5% | RH | 36.9% | 20.6% | 15.7% | L7Days | 36.1% | 21.3% | 17.7% |
| Tigers | Road | 33.8% | 14.0% | 19.0% | RH | 30.1% | 15.6% | 17.1% | L7Days | 33.5% | 11.7% | 17.0% |
| Dodgers | Home | 24.8% | 10.3% | 3.0% | RH | 29.4% | 5.9% | 9.8% | L7Days | 25.2% | 5.8% | 4.4% |
| Brewers | Road | 34.1% | 20.0% | 17.6% | LH | 35.8% | 18.8% | 14.9% | L7Days | 37.6% | 23.1% | 21.8% |
| Astros | Home | 31.5% | 7.7% | 16.7% | RH | 33.3% | 17.5% | 15.3% | L7Days | 31.8% | 14.8% | 16.6% |
| Phillies | Home | 14.0% | 7.9% | -5.6% | RH | 23.9% | 11.4% | 3.5% | L7Days | 18.5% | 9.4% | -3.8% |
| Giants | Road | 32.2% | 17.2% | 10.9% | LH | 20.8% | 14.0% | -8.0% | L7Days | 24.7% | 17.9% | 2.3% |
| Padres | Home | 15.4% | 0.0% | -6.6% | RH | 24.4% | 7.7% | 4.7% | L7Days | 24.9% | 11.4% | 6.6% |
| Pirates | Home | 26.5% | 2.4% | 7.2% | RH | 26.7% | 4.9% | 6.5% | L7Days | 26.6% | 5.0% | 6.5% |
| Braves | Road | 23.1% | 0.0% | 3.3% | RH | 20.5% | 5.6% | -1.9% | L7Days | 25.2% | 1.7% | 6.5% |
| Rangers | Home | 20.2% | 5.0% | -8.2% | RH | 24.3% | 5.8% | -0.9% | L7Days | 27.6% | 7.4% | 4.4% |
K/SwStr Chart (2015 LG AVG – 19.5 K% – 9.3 SwStr% – 2.1 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 | 21.4% | 8.6% | 2.49 | 32.7% | 9.0% | 3.63 |
| Andrew Cashner | SDG | 20.5% | 8.2% | 2.50 | 23.8% | 8.6% | 2.77 |
| Bud Norris | ATL | 18.8% | 9.6% | 1.96 | 14.8% | 6.7% | 2.21 |
| Colby Lewis | TEX | 16.5% | 8.2% | 2.01 | 21.7% | 8.6% | 2.52 |
| Collin McHugh | HOU | 19.9% | 10.3% | 1.93 | 10.8% | 7.6% | 1.42 |
| Johnny Cueto | SFO | 20.3% | 9.9% | 2.05 | 20.0% | 11.5% | 1.74 |
| Jon Niese | PIT | 14.7% | 5.8% | 2.53 | 25.5% | 8.2% | 3.11 |
| Justin Verlander | DET | 21.1% | 10.0% | 2.11 | 15.2% | 10.1% | 1.50 |
| Max Scherzer | WAS | 30.7% | 15.3% | 2.01 | 25.5% | 12.3% | 2.07 |
| Scott Kazmir | LOS | 20.3% | 10.3% | 1.97 | 22.5% | 8.3% | 2.71 |
| Shelby Miller | ARI | 19.9% | 9.2% | 2.16 | 16.0% | 5.4% | 2.96 |
| Taylor Jungmann | MIL | 21.4% | 8.4% | 2.55 | 9.1% | 2.9% | 3.14 |
| Tom Koehler | FLA | 17.1% | 7.3% | 2.34 | 20.7% | 9.9% | 2.09 |
| Yovani Gallardo | BAL | 15.3% | 6.5% | 2.35 | 16.3% | 6.5% | 2.51 |
We’re still using 2015 numbers a bit long until just about every pitcher has made a couple of starts, but also using this year’s stats in the “L30 Days” column. As mentioned, we’re showing just starting pitcher league averages in the header information now, which drops K% and SwStr% just slightly from the overall average that includes relievers.
Though there are some discrepancies in early returns this season, we can’t really confidently say anything after just a couple of starts and everyone was within range last year.
ERA Estimators Chart (2015 LG AVG – 4.10 ERA – 4.07 SIERA – 4.00 xFIP – 4.03 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 | 3.59 | 3.66 | 0.07 | 3.58 | -0.01 | 4.04 | 0.45 | 3.21 | 2.09 | -1.12 | 2.14 | -1.07 | 2.58 | -0.63 |
| Andrew Cashner | SDG | 4.34 | 4 | -0.34 | 3.84 | -0.5 | 3.85 | -0.49 | 8 | 3.71 | -4.29 | 3.63 | -4.37 | 3.38 | -4.62 |
| Bud Norris | ATL | 6.72 | 4.17 | -2.55 | 4.29 | -2.43 | 5.04 | -1.68 | 6 | 4.7 | -1.3 | 4.73 | -1.27 | 3.91 | -2.09 |
| Colby Lewis | TEX | 4.66 | 4.43 | -0.23 | 4.62 | -0.04 | 4.17 | -0.49 | 3 | 4.15 | 1.15 | 4.39 | 1.39 | 4.66 | 1.66 |
| Collin McHugh | HOU | 3.89 | 3.91 | 0.02 | 3.91 | 0.02 | 3.58 | -0.31 | 6.14 | 5.49 | -0.65 | 5.78 | -0.36 | 3.29 | -2.85 |
| Johnny Cueto | SFO | 3.44 | 3.81 | 0.37 | 3.78 | 0.34 | 3.53 | 0.09 | 4.5 | 3.69 | -0.81 | 3.72 | -0.78 | 2.08 | -2.42 |
| Jon Niese | PIT | 4.13 | 4.27 | 0.14 | 4.11 | -0.02 | 4.41 | 0.28 | 5.73 | 3.21 | -2.52 | 3.73 | -2 | 5.34 | -0.39 |
| Justin Verlander | DET | 3.37 | 3.95 | 0.58 | 4.15 | 0.78 | 3.49 | 0.12 | 8.71 | 5.15 | -3.56 | 5.32 | -3.39 | 4.22 | -4.49 |
| Max Scherzer | WAS | 2.79 | 2.63 | -0.16 | 2.88 | 0.09 | 2.77 | -0.02 | 4.15 | 3.76 | -0.39 | 3.71 | -0.44 | 4.31 | 0.16 |
| Scott Kazmir | LOS | 3.1 | 4.1 | 1 | 4.14 | 1.04 | 3.98 | 0.88 | 5.4 | 3.3 | -2.1 | 3.78 | -1.62 | 5.86 | 0.46 |
| Shelby Miller | ARI | 3.02 | 4.16 | 1.14 | 4.07 | 1.05 | 3.45 | 0.43 | 8.18 | 4.45 | -3.73 | 4.73 | -3.45 | 8.43 | 0.25 |
| Taylor Jungmann | MIL | 3.77 | 4.11 | 0.34 | 4.1 | 0.33 | 3.92 | 0.15 | 11.57 | 5.39 | -6.18 | 5.54 | -6.03 | 5.44 | -6.13 |
| Tom Koehler | FLA | 4.08 | 4.67 | 0.59 | 4.58 | 0.5 | 4.53 | 0.45 | 2.84 | 4.49 | 1.65 | 4.12 | 1.28 | 3.16 | 0.32 |
| Yovani Gallardo | BAL | 3.42 | 4.59 | 1.17 | 4.31 | 0.89 | 4 | 0.58 | 5.4 | 5.1 | -0.3 | 5.54 | 0.14 | 2.96 | -2.44 |
Anything that needs to be said about the pitchers with larger gaps was either already said above, most of whom don’t court much interest today.
BABIP Chart (2015 LG AVG – .295 BABIP – 21.1 LD% – 9.5 IFFB% – 87.7 Z-Contact%)
A few years back, 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. A pitcher with a much lower BABIP than his team allows is a red flag absent further supporting evidence, while a pitcher with a much higher BABIP than his team allows may have something to offer in the future, especially with the right indicators.
| Pitcher | Team | Team BABIP | Pitcher BABIP | Diff | Pitcher LD% | Pitcher IFFB% | Pitcher Zcontact |
|---|---|---|---|---|---|---|---|
| Aaron Nola | PHI | 0.282 | 0.289 | 0.007 | 0.2 | 8.2% | 87.3% |
| Andrew Cashner | SDG | 0.298 | 0.330 | 0.032 | 0.227 | 9.1% | 89.5% |
| Bud Norris | ATL | 0.305 | 0.332 | 0.027 | 0.228 | 8.9% | 86.4% |
| Colby Lewis | TEX | 0.264 | 0.289 | 0.025 | 0.22 | 7.9% | 90.3% |
| Collin McHugh | HOU | 0.299 | 0.310 | 0.011 | 0.2 | 11.3% | 85.9% |
| Johnny Cueto | SFO | 0.347 | 0.281 | -0.066 | 0.22 | 12.2% | 86.7% |
| Jon Niese | PIT | 0.288 | 0.300 | 0.012 | 0.208 | 5.0% | 92.5% |
| Justin Verlander | DET | 0.317 | 0.267 | -0.05 | 0.199 | 13.8% | 84.5% |
| Max Scherzer | WAS | 0.256 | 0.268 | 0.012 | 0.188 | 12.9% | 78.9% |
| Scott Kazmir | LOS | 0.229 | 0.273 | 0.044 | 0.198 | 7.1% | 86.6% |
| Shelby Miller | ARI | 0.307 | 0.285 | -0.022 | 0.182 | 8.9% | 87.4% |
| Taylor Jungmann | MIL | 0.292 | 0.290 | -0.002 | 0.206 | 7.2% | 90.9% |
| Tom Koehler | FLA | 0.330 | 0.283 | -0.047 | 0.184 | 7.0% | 90.7% |
| Yovani Gallardo | BAL | 0.305 | 0.303 | -0.002 | 0.22 | 8.2% | 89.9% |
Don’t pay much attention to this year’s Team BABIP yet. The sample is way too small. Pitcher numbers are still from 2015.
There’s really not much here that was far out of line last year.
Pitcher Notes & Summary
Here we normally 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.
We’re still just talking a bit more about the pitchers you might be considering today in relation to their price tags in no particular order until we get a bit more information about 2016.
This was one of the ugliest, most frustrating pitching articles I’ve ever written, taking way longer than just 2.5K words normally would. There’s very little to be optimistic about and very difficult to wade through. Let’s finally finish it off with some last thoughts based on cost.
Aaron Nola might not be in as bad a spot as it looks if he can navigate around the two big LH bats in the Washington lineup. He’s likely not as good as he’s shown early (not yet anyway), especially in the strikeout department and seems accurately priced, but there’s some wiggle room for upside. He was the first pitcher I wrote up alphabetically today, but after wading through the rest of the sewage and coming back to him, he’s starting to look much better.
Andrew Cashner is about as average as you can get in both skillset and cost today. However, a decent matchup at home puts him in the usable category.
Johnny Cueto – I’m kind of not sure what to do here. He’s the 2nd costliest pitcher on the board and not in a great spot. I’ve always felt that his low BABIP and high strand rate would eventually come back to bite him and now that it has over most of a calendar year now, I can’t tell what he’s going to be going forward. Is he going to get some of that back? The K%, which had been higher, has dropped back to league average as well. Is he just an average pitcher now or something more? I may lean against paying up for him today as it seems a bit of a high risk, mediocre reward gamble.
Max Scherzer has had a few issues early, but who on this board hasn’t. He’s really expensive, but he’s facing the Phillies and you’d have to have more confidence in him than any other pitcher today. We may have to grade tonight on a curve and not expect any pitcher to really exceed their price tag by what we normally might. I can’t even find the guy likely to compete with him for the top score tonight though.
Tom Koehler is not good, but he’s facing the Braves at home and is inexpensive. It’s really difficult to pick out pitchers worth their price today.
You can find me on twitter @FreelanceBBall for any questions, comments, or insults.
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