Advanced Stats - Pitching: Thursday, June 15th
There’s a couple of things going on here today. Day games are not listed because they’ve already begun. There are also two pitchers listed for the Mets because when the data was compiled there was some confusion about who it would be and there was enough room to just go ahead and list both guys with the shorter slate. It will likely have been settled by the time you read this, so you can disregard the extra pitcher.
The good news tonight is Chris Sale. Yes. Use that guy. Pitching analysis complete?
As always, don’t forget to check lineups, umpire assignments, line movement, ownership projections and the weather forecast 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. All of these things are available right here on the site.
Starting Pitching Main Chart
| Pitcher | Team | Team Def | SIERA L2Yrs | IP/GS L2Yrs | GB% L2Yrs | Park Run | Hm/Rd xFIP | SIERA L14 | Opp | Opp Hm/Rd | Opp L/R wRC+ | Opp L7 wRC+ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Alex Cobb | TAM | 0.8 | 4.63 | 5.62 | 45.9% | 0.98 | 4.73 | 5.25 | DET | 120 | 99 | 102 |
| Chris Sale | BOS | 5.1 | 2.94 | 6.96 | 41.3% | 0.96 | 3.44 | 2.85 | PHI | 100 | 86 | 63 |
| Gio Gonzalez | WAS | -1.9 | 4.06 | 5.66 | 48.7% | 0.91 | 4.35 | 2.54 | NYM | 90 | 85 | 116 |
| Jeff Hoffman | COL | 0.7 | 4.12 | 5.3 | 42.0% | 1.39 | 4.52 | 2.42 | SFO | 79 | 78 | 97 |
| Jordan Montgomery | NYY | 1.3 | 4.27 | 5.74 | 39.3% | 0.93 | 4.82 | 3.83 | OAK | 115 | 87 | 107 |
| Justin Verlander | DET | 2.6 | 3.82 | 6.53 | 34.2% | 0.98 | 4.02 | 6.48 | TAM | 102 | 116 | 148 |
| Matt Moore | SFO | -0.2 | 4.58 | 5.79 | 38.1% | 1.39 | 5.18 | 6.78 | COL | 79 | 90 | 71 |
| Matt Strahm | KAN | 8 | 3.97 | 44.0% | 0.91 | 4.95 | 3.94 | ANA | 107 | 96 | 112 | |
| Michael Wacha | STL | -11.6 | 4.22 | 5.59 | 46.3% | 0.98 | 3.93 | 5.6 | MIL | 95 | 95 | 90 |
| Nick Pivetta | PHI | 4 | 5.01 | 4.85 | 37.1% | 0.96 | 3.07 | 6.34 | BOS | 101 | 98 | 130 |
| Ricky Nolasco | ANA | -5.6 | 4.36 | 5.94 | 42.1% | 0.91 | 4.4 | 3.49 | KAN | 85 | 83 | 126 |
| Robert Gsellman | NYM | 1.1 | 4.13 | 5.57 | 54.4% | 0.91 | 3.56 | 4.36 | WAS | 102 | 111 | 103 |
| Sonny Gray | OAK | -14.3 | 4.09 | 5.92 | 53.2% | 0.93 | 3.74 | 3.2 | NYY | 106 | 125 | 175 |
| Steven Matz | NYM | 1.1 | 3.62 | 6.03 | 49.2% | 0.91 | 3.43 | 5.97 | WAS | 102 | 102 | 103 |
| Zach Davies | MIL | -4 | 4.3 | 5.64 | 47.9% | 0.98 | 4.49 | 3.34 | STL | 98 | 96 | 111 |
Chris Sale has been the top pitcher on just about any slate he appears on, so there’s no question about it today. He hasn’t reached double digit strikeouts in four starts, but has at least six in every game this year and has gone fewer than seven innings only three times. What more can you say about a guy with a 30.5 K-BB%. Who’s he even facing? The Phillies? God help them.
Gio Gonzalez struck out a season high nine batters in his last start, three-hitting Texas through six innings. His sub-three ERA is a fluke as is his elevated strikeout rate over the last month, but the good news is that he hasn’t allowed a HR in four starts after 10 over his first nine starts. That’s significant because he hit a career high with 19 HRs allowed last year. Interestingly his hard hit rate has been up a bit (34.5%) over these four starts. His 11.3 BB% is his highest in seven years. Now that we’ve covered every reason not to roster him, let’s consider why you might. The Mets have faced a flurry of LHP recently and Cespedes got the night off last night, but should be back tonight. That should improve a poor offense against LHP somewhat, but they’re also down both middle infielders, switch hitters who have been competent against LHP since last season. The Mets don’t strike out a lot, but have been below average vs LHP. It should be a very good spot for him.
Jeff Hoffman has struck out 34 of 102 batters with a 13.0 SwStr%. He’s walked just three. How has he allowed barrels on 9.4% of BBEs with just 29.7% of them above a 95 mph EV? A 50.8% fly ball rate will do that and that’s absolutely dangerous in Coors Field. Now, he’s only started one game at home and allowed a HR as well as another one in 1.1 innings of relief. His three road starts were Phillies, Padres, and Cubs. That’s okay because nobody expects him to keep this up. However, he returns home to face another of the worst offenses in baseball. This is still not a favorable matchup, but it’s kind of like facing a good offense (110 wRC+ range?) on neutral ground. They don’t strike out a lot, but have very little power with just a 10.0 HR/FB even on the road this year.
Jordan Montgomery has been a quality arm for the Yankees and has been pitching very well as of late. He’s not a hard thrower, but still gets strikeouts, which is why the broadcasters love him. He’s also limited hard contact to 25%, which helps explain a 7.8 HR/FB that still may be unsustainable. However, he transitions to a very pitcher friendly park tonight. The A’s do have some power (17.3 HR/FB at home), but have struggled against LHP (25.3 K%).
Sonny Gray has hit double digit strikeouts in two of his last four starts (Marlins and Rays), though he hasn’t exactly been preventing runs. While his SwStr rate has been above 15% in three of his last five starts, it’s been below 8% in each of his other two. In those two double digit strikeout efforts, he threw his slider 30% of the time, while only half or less that mark in each of the other three, which leaves one outing unexplained. His slider usage in his first three starts was below 6%, so either way he’s throwing it more. His slider usage hasn’t seemed to affect his 56.7 GB% much. Is he going to throw 30% sliders against a predominantly RH Yankee lineup? Perhaps he should. It’s probably the worst spot on the slate. The Yankees have an 18.3 HR/FB vs RHP and a 4.0 K-BB% with a 22.5 HR/FB over the last week.
NOT AS GOOD AS THEY LOOK (OR THE FADE LIST)
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 (.293 BABIP – 72.9 LOB% – 14.1 HR/FB)
No qualifiers today.
NO THANK YOU (In order from least to most offensive)
Michael Wacha has not exceeded five strikeouts since missing a start a month ago. He does have a 54.3 GB% with just a 7.0 Hard-Soft%, so perhaps he’s run a bit unlucky with a .348 BABIP and 62.5 LOB% over that span, but he also has just a 6.5 K-BB%. His 27.7% EV above 95 mph is best on tonight’s board and Milwaukee will strike out (24.4% vs RHP), but they will take walks and do some damage too (18.0 HR/FB vs RHP).
Robert Gsellman gsets the start today over Matz. Although still not as good as last season, he has been pitching better recently with a SwStr exceeding 9% in each of his last three starts and has retained a 54.5% ground ball rate all season. His 4.7% Barrels/BBE is lowest on the board despite allowing contact at about league average authority (32.2 Hard%). The uptick in swings and misses is what almost interests us again, but he’s facing a Washington lineup that’s pretty good against RHP.
Justin Verlander has not been very good. His walk rate has doubled while he’s striking out batters at just a league average rate and much lower over the last month and also allowing a lot of hard contact in the air. I can’t fathom why DRA likes him so much. The Rays do strike out a lot (25.7% vs RHP), but also do damage (18.5 HR/FB on the road, 18.9 HR/FB vs RHP, 23.4 HR/FB last seven days). This might be the equivalent of the two Coors matchups tonight if we’re looking for a comparison.
Ricky Nolasco has nice peripherals and a great run prevention matchup, but allows way too much hard contact. I’m more optimistic about the K% drop over the last month because he’s held his 10.7 SwStr%. The Royals have a 21.3 HR/FB over the last week.
Matt Strahm has not started a game since AA last season. Last time out, in San Diego, he threw a season high 49 pitches in two innings. The bullpen could see action some time around the fourth inning.
Matt Moore
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% |
|---|---|---|---|---|---|---|---|---|---|---|
| Alex Cobb | Rays | L2 Years | 16.4% | 6.8% | Road | 14.4% | 7.2% | L14 Days | 15.7% | 5.9% |
| Chris Sale | Red Sox | L2 Years | 29.6% | 4.8% | Road | 27.3% | 5.4% | L14 Days | 29.1% | 1.8% |
| Gio Gonzalez | Nationals | L2 Years | 22.4% | 8.9% | Road | 19.2% | 8.4% | L14 Days | 31.1% | 6.7% |
| Jeff Hoffman | Rockies | L2 Years | 22.5% | 8.0% | Home | 21.1% | 8.9% | L14 Days | 34.7% | 2.0% |
| Jordan Montgomery | Yankees | L2 Years | 23.0% | 8.7% | Road | 18.2% | 10.7% | L14 Days | 25.5% | 7.8% |
| Justin Verlander | Tigers | L2 Years | 24.8% | 7.1% | Home | 28.0% | 6.5% | L14 Days | 15.4% | 18.0% |
| Matt Moore | Giants | L2 Years | 19.4% | 8.6% | Road | 18.4% | 10.5% | L14 Days | 8.7% | 10.9% |
| Matt Strahm | Royals | L2 Years | 30.8% | 15.9% | Road | 27.1% | 19.6% | L14 Days | 28.6% | 14.3% |
| Michael Wacha | Cardinals | L2 Years | 20.4% | 8.3% | Home | 20.0% | 7.9% | L14 Days | 14.9% | 12.8% |
| Nick Pivetta | Phillies | L2 Years | 20.2% | 11.9% | Home | 24.0% | 0.0% | L14 Days | 13.6% | 15.9% |
| Ricky Nolasco | Angels | L2 Years | 18.5% | 5.7% | Home | 18.0% | 5.1% | L14 Days | 17.7% | 0.0% |
| Robert Gsellman | Mets | L2 Years | 19.0% | 7.6% | Home | 20.3% | 6.6% | L14 Days | 19.2% | 7.7% |
| Sonny Gray | Athletics | L2 Years | 19.2% | 7.7% | Home | 20.4% | 7.2% | L14 Days | 29.6% | 7.4% |
| Steven Matz | Mets | L2 Years | 22.8% | 5.8% | Home | 23.8% | 7.1% | L14 Days | 7.4% | 3.7% |
| Zach Davies | Brewers | L2 Years | 18.6% | 7.0% | Road | 16.6% | 7.5% | L14 Days | 21.7% | 6.5% |
K/BB Chart – Opponent
| Opponent | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Tigers | Home | 19.8% | 9.6% | RH | 23.3% | 9.8% | L7Days | 22.6% | 4.7% |
| Phillies | Home | 20.3% | 8.7% | LH | 19.6% | 7.9% | L7Days | 23.8% | 6.9% |
| Mets | Home | 19.6% | 9.3% | LH | 21.7% | 7.9% | L7Days | 21.4% | 9.2% |
| Giants | Road | 19.7% | 8.5% | RH | 19.2% | 7.6% | L7Days | 16.9% | 7.2% |
| Athletics | Home | 23.7% | 8.4% | LH | 25.3% | 7.2% | L7Days | 23.3% | 7.3% |
| Rays | Road | 27.3% | 9.4% | RH | 25.7% | 9.0% | L7Days | 23.3% | 6.4% |
| Rockies | Home | 21.0% | 7.7% | LH | 23.8% | 6.6% | L7Days | 23.4% | 7.9% |
| Angels | Home | 18.0% | 8.2% | LH | 18.7% | 10.0% | L7Days | 20.1% | 9.2% |
| Brewers | Road | 23.3% | 8.8% | RH | 24.4% | 9.0% | L7Days | 22.4% | 10.1% |
| Red Sox | Road | 18.7% | 8.9% | RH | 18.2% | 9.2% | L7Days | 17.6% | 10.8% |
| Royals | Road | 21.1% | 6.4% | RH | 21.3% | 6.5% | L7Days | 20.4% | 6.4% |
| Nationals | Road | 20.1% | 8.8% | RH | 19.2% | 9.0% | L7Days | 19.7% | 5.6% |
| Yankees | Road | 21.5% | 8.9% | RH | 21.7% | 9.7% | L7Days | 16.1% | 12.1% |
| Nationals | Road | 20.1% | 8.8% | LH | 22.0% | 7.7% | L7Days | 19.7% | 5.6% |
| Cardinals | Home | 21.1% | 9.5% | RH | 20.8% | 8.6% | L7Days | 19.1% | 8.0% |
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% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Alex Cobb | Rays | L2 Years | 36.2% | 14.2% | 22.2% | 2017 | 38.3% | 12.0% | 25.4% | Road | 32.9% | 13.6% | 19.5% | L14 Days | 46.2% | 11.1% | 38.5% |
| Chris Sale | Red Sox | L2 Years | 29.7% | 11.7% | 12.0% | 2017 | 29.7% | 7.3% | 15.1% | Road | 30.0% | 4.9% | 13.0% | L14 Days | 23.7% | 0.0% | 13.2% |
| Gio Gonzalez | Nationals | L2 Years | 32.4% | 10.7% | 12.8% | 2017 | 31.5% | 13.9% | 9.9% | Road | 32.0% | 12.5% | 11.6% | L14 Days | 25.0% | 0.0% | -7.1% |
| Jeff Hoffman | Rockies | L2 Years | 33.7% | 16.1% | 14.5% | 2017 | 32.8% | 9.4% | 15.6% | Home | 36.5% | 16.0% | 20.6% | L14 Days | 26.7% | 7.1% | 10.0% |
| Jordan Montgomery | Yankees | L2 Years | 25.0% | 7.8% | 11.1% | 2017 | 25.0% | 7.8% | 11.1% | Road | 19.8% | 3.3% | 9.3% | L14 Days | 26.5% | 7.7% | 8.8% |
| Justin Verlander | Tigers | L2 Years | 28.6% | 9.6% | 9.9% | 2017 | 38.2% | 9.8% | 23.1% | Home | 32.4% | 10.4% | 13.0% | L14 Days | 69.2% | 12.5% | 57.7% |
| Matt Moore | Giants | L2 Years | 32.9% | 10.8% | 16.1% | 2017 | 39.0% | 11.4% | 22.7% | Road | 33.1% | 12.0% | 19.0% | L14 Days | 32.4% | 5.9% | 13.5% |
| Matt Strahm | Royals | L2 Years | 28.4% | 12.5% | 6.3% | 2017 | 26.5% | 21.1% | 4.0% | Road | 34.6% | 16.7% | 16.4% | L14 Days | 27.3% | 33.3% | 0.0% |
| Michael Wacha | Cardinals | L2 Years | 29.7% | 12.5% | 9.5% | 2017 | 26.0% | 12.5% | 5.8% | Home | 29.9% | 10.3% | 9.8% | L14 Days | 32.4% | 18.2% | 0.0% |
| Nick Pivetta | Phillies | L2 Years | 35.6% | 15.6% | 23.4% | 2017 | 35.6% | 15.6% | 23.4% | Home | 50.0% | 60.0% | 44.4% | L14 Days | 25.8% | 0.0% | 9.7% |
| Ricky Nolasco | Angels | L2 Years | 35.0% | 14.2% | 20.9% | 2017 | 38.2% | 20.2% | 24.2% | Home | 31.0% | 11.8% | 15.0% | L14 Days | 40.0% | 27.3% | 30.0% |
| Robert Gsellman | Mets | L2 Years | 30.8% | 9.9% | 10.9% | 2017 | 32.2% | 13.2% | 11.2% | Home | 29.3% | 11.4% | 7.8% | L14 Days | 39.5% | 9.1% | 21.1% |
| Sonny Gray | Athletics | L2 Years | 31.3% | 14.9% | 15.1% | 2017 | 32.1% | 16.1% | 18.2% | Home | 31.0% | 13.7% | 13.7% | L14 Days | 32.4% | 0.0% | 20.6% |
| Steven Matz | Mets | L2 Years | 28.0% | 12.2% | 7.6% | 2017 | 20.8% | 0.0% | 8.3% | Home | 33.7% | 17.5% | 7.5% | L14 Days | 20.8% | 0.0% | 8.3% |
| Zach Davies | Brewers | L2 Years | 32.8% | 13.1% | 12.5% | 2017 | 30.8% | 15.9% | 9.4% | Road | 29.6% | 12.8% | 6.0% | L14 Days | 25.0% | 14.3% | 9.4% |
Batted Ball Charts – Opponent
| Opponent | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Tigers | Home | 49.7% | 14.0% | 37.1% | RH | 42.6% | 12.5% | 28.0% | L7Days | 38.8% | 10.3% | 25.9% |
| Phillies | Home | 30.5% | 14.5% | 10.5% | LH | 29.3% | 15.8% | 9.2% | L7Days | 30.4% | 5.4% | 11.5% |
| Mets | Home | 34.7% | 10.0% | 16.1% | LH | 35.6% | 9.9% | 14.6% | L7Days | 40.5% | 15.8% | 22.7% |
| Giants | Road | 30.1% | 10.0% | 9.6% | RH | 27.8% | 9.0% | 6.2% | L7Days | 23.7% | 5.3% | 1.1% |
| Athletics | Home | 32.9% | 17.3% | 18.1% | LH | 32.8% | 10.2% | 15.4% | L7Days | 35.3% | 6.6% | 17.9% |
| Rays | Road | 34.5% | 18.5% | 15.4% | RH | 36.4% | 18.9% | 19.2% | L7Days | 36.6% | 23.4% | 21.5% |
| Rockies | Home | 30.2% | 15.9% | 10.3% | LH | 30.8% | 16.9% | 10.9% | L7Days | 25.0% | 11.5% | 8.3% |
| Angels | Home | 28.6% | 14.5% | 9.7% | LH | 30.8% | 10.8% | 14.0% | L7Days | 34.0% | 11.5% | 15.7% |
| Brewers | Road | 30.0% | 16.9% | 10.6% | RH | 33.6% | 18.0% | 14.3% | L7Days | 29.0% | 17.3% | 7.0% |
| Red Sox | Road | 33.1% | 12.7% | 12.8% | RH | 36.0% | 10.0% | 18.6% | L7Days | 42.1% | 8.5% | 25.8% |
| Royals | Road | 31.7% | 15.7% | 12.1% | RH | 32.4% | 12.8% | 13.2% | L7Days | 34.1% | 21.3% | 14.7% |
| Nationals | Road | 29.8% | 14.1% | 10.8% | RH | 31.1% | 14.6% | 13.7% | L7Days | 30.5% | 14.9% | 15.5% |
| Yankees | Road | 32.2% | 13.3% | 14.6% | RH | 32.9% | 18.3% | 14.0% | L7Days | 38.4% | 22.5% | 20.8% |
| Nationals | Road | 29.8% | 14.1% | 10.8% | LH | 30.4% | 15.7% | 10.3% | L7Days | 30.5% | 14.9% | 15.5% |
| Cardinals | Home | 29.6% | 10.4% | 9.2% | RH | 30.3% | 12.2% | 11.0% | L7Days | 27.1% | 14.0% | 7.9% |
K/SwStr Chart (2017 LG AVG – 20.4 K% – 9.7 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% |
|---|---|---|---|---|---|---|---|
| Alex Cobb | TAM | 16.8% | 7.4% | 2.27 | 19.6% | 8.0% | 2.45 |
| Chris Sale | BOS | 35.3% | 16.0% | 2.21 | 29.7% | 15.9% | 1.87 |
| Gio Gonzalez | WAS | 22.1% | 9.1% | 2.43 | 26.6% | 9.4% | 2.83 |
| Jeff Hoffman | COL | 33.3% | 13.0% | 2.56 | 32.9% | 11.4% | 2.89 |
| Jordan Montgomery | NYY | 23.0% | 12.7% | 1.81 | 23.7% | 11.9% | 1.99 |
| Justin Verlander | DET | 20.7% | 8.9% | 2.33 | 16.5% | 8.8% | 1.88 |
| Matt Moore | SFO | 17.3% | 8.2% | 2.11 | 14.4% | 8.0% | 1.80 |
| Matt Strahm | KAN | 27.7% | 10.4% | 2.66 | 25.6% | 11.3% | 2.27 |
| Michael Wacha | STL | 21.8% | 9.7% | 2.25 | 19.6% | 9.4% | 2.09 |
| Nick Pivetta | PHI | 20.2% | 7.0% | 2.89 | 17.2% | 4.5% | 3.82 |
| Ricky Nolasco | ANA | 19.9% | 10.7% | 1.86 | 17.5% | 10.7% | 1.64 |
| Robert Gsellman | NYM | 16.7% | 7.7% | 2.17 | 18.4% | 9.2% | 2.00 |
| Sonny Gray | OAK | 23.7% | 11.2% | 2.12 | 29.9% | 13.2% | 2.27 |
| Steven Matz | NYM | 7.4% | 6.1% | 1.21 | 7.4% | 6.1% | 1.21 |
| Zach Davies | MIL | 16.5% | 7.4% | 2.23 | 13.9% | 8.1% | 1.72 |
The most important thing to probably note tonight is Gio Gonzalez and Jeff Hoffman can’t exactly support their K% over the last month, though the latter still projects well.
ERA Estimators Chart (2017 LG AVG – 4.35 ERA – 4.32 SIERA – 4.26 xFIP – 4.37 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 | Season DRA | DIFF | ERA L30 | SIERA L30 | DIFF | xFIP L30 | DIFF | FIP L30 | DIFF |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Alex Cobb | TAM | 4.29 | 4.66 | 0.37 | 4.53 | 0.24 | 4.33 | 0.04 | 5.14 | 0.85 | 5.34 | 4.54 | -0.8 | 4.67 | -0.67 | 4.3 | -1.04 |
| Chris Sale | BOS | 2.97 | 2.54 | -0.43 | 2.56 | -0.41 | 1.83 | -1.14 | 1.62 | -1.35 | 4.45 | 2.89 | -1.56 | 2.74 | -1.71 | 1.75 | -2.7 |
| Gio Gonzalez | WAS | 2.91 | 4.61 | 1.7 | 4.3 | 1.39 | 4.35 | 1.44 | 3.79 | 0.88 | 3.68 | 3.91 | 0.23 | 3.27 | -0.41 | 3.08 | -0.6 |
| Jeff Hoffman | COL | 2.33 | 2.68 | 0.35 | 3.12 | 0.79 | 2.48 | 0.15 | 2.13 | -0.20 | 1.33 | 2.58 | 1.25 | 2.95 | 1.62 | 1.69 | 0.36 |
| Jordan Montgomery | NYY | 3.55 | 4.27 | 0.72 | 4.46 | 0.91 | 3.56 | 0.01 | 3.50 | -0.05 | 2.79 | 3.93 | 1.14 | 3.89 | 1.1 | 3.36 | 0.57 |
| Justin Verlander | DET | 4.68 | 4.92 | 0.24 | 5.22 | 0.54 | 4.57 | -0.11 | 3.36 | -1.32 | 5.06 | 5.23 | 0.17 | 5.45 | 0.39 | 5.51 | 0.45 |
| Matt Moore | SFO | 5.28 | 5 | -0.28 | 5.27 | -0.01 | 4.89 | -0.39 | 7.97 | 2.69 | 4.66 | 5.53 | 0.87 | 5.74 | 1.08 | 4.8 | 0.14 |
| Matt Strahm | KAN | 4.5 | 4.88 | 0.38 | 4.86 | 0.36 | 5.7 | 1.2 | 4.27 | -0.23 | 1.86 | 4.9 | 3.04 | 4.8 | 2.94 | 4.87 | 3.01 |
| Michael Wacha | STL | 4.5 | 4.34 | -0.16 | 4.12 | -0.38 | 4 | -0.5 | 4.05 | -0.45 | 6.56 | 5.01 | -1.55 | 4.7 | -1.86 | 4.79 | -1.77 |
| Nick Pivetta | PHI | 5.52 | 5.01 | -0.51 | 4.93 | -0.59 | 5.23 | -0.29 | 7.42 | 1.90 | 4.91 | 6.18 | 1.27 | 5.54 | 0.63 | 3.86 | -1.05 |
| Ricky Nolasco | ANA | 4.81 | 4.3 | -0.51 | 4.5 | -0.31 | 5.62 | 0.81 | 6.68 | 1.87 | 5.6 | 4.47 | -1.13 | 4.56 | -1.04 | 5.42 | -0.18 |
| Robert Gsellman | NYM | 4.95 | 4.38 | -0.57 | 4.29 | -0.66 | 4.26 | -0.69 | 5.43 | 0.48 | 2.25 | 4.36 | 2.11 | 4.21 | 1.96 | 3.51 | 1.26 |
| Sonny Gray | OAK | 4.37 | 3.55 | -0.82 | 3.17 | -1.2 | 3.39 | -0.98 | 2.81 | -1.56 | 4.7 | 2.93 | -1.77 | 2.32 | -2.38 | 2.36 | -2.34 |
| Steven Matz | NYM | 1.29 | 5.97 | 4.68 | 5.73 | 4.44 | 2.97 | 1.68 | 6.80 | 5.51 | 1.29 | 5.97 | 4.68 | 5.73 | 4.44 | 2.97 | 1.68 |
| Zach Davies | MIL | 4.74 | 4.82 | 0.08 | 4.74 | 0 | 5.06 | 0.32 | 5.96 | 1.22 | 3.21 | 4.49 | 1.28 | 4.36 | 1.15 | 4.9 | 1.69 |
Gio Gonzalez has a career high 85% strand rate. His 10.8 K-BB% is his lowest mark since 2010.
Jeff Hoffman is posting a .230 BABIP with an 83.3 LOB% and 9.4 HR/FB. We’re still dealing with a small sample size and only one start at Coors with the rest of them against poor offenses, but it might at least be interesting with the BABIP and his extreme fly ball rate.
Jordan Montgomery his meeting his FIP, but flies below other estimators due to his 7.8 HR/FB. With a 14.3 K-BB%, I don’t see why they’re that high though. Estimators still seem to occasionally undervalue fly ball pitchers by normalizing HR rates. In a decent park like Oakland, I’d buy more into his ERA/FIP combination.
Sonny Gray has just a 58.5 LOB%. His issues seem to lie mostly in sequencing.
BABIP & Statcast Chart (2017 LG AVG – .293 BABIP – 44.5 GB% – 20.3 LD% – 9.2 IFFB% – 86.6 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 | GB% | Pitcher LD% | Pitcher IFFB% | Pitcher Zcontact | Exit Velocity | Barrels BBE | Barrels PA | BBE |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Alex Cobb | TAM | 0.293 | 0.313 | 0.02 | 43.9% | 0.233 | 8.4% | 91.6% | 88.7 | 6.30% | 4.70% | 256 |
| Chris Sale | BOS | 0.316 | 0.311 | -0.005 | 39.0% | 0.219 | 9.8% | 75.4% | 87.1 | 6.10% | 3.60% | 212 |
| Gio Gonzalez | WAS | 0.298 | 0.274 | -0.024 | 46.5% | 0.2 | 9.7% | 86.2% | 86.2 | 6.30% | 4.20% | 222 |
| Jeff Hoffman | COL | 0.285 | 0.230 | -0.055 | 28.6% | 0.206 | 9.4% | 83.1% | 87.6 | 9.40% | 5.90% | 64 |
| Jordan Montgomery | NYY | 0.277 | 0.282 | 0.005 | 39.3% | 0.174 | 7.8% | 86.1% | 86.7 | 6.70% | 4.50% | 180 |
| Justin Verlander | DET | 0.311 | 0.298 | -0.013 | 33.3% | 0.213 | 8.8% | 86.0% | 89.1 | 8.90% | 6.00% | 225 |
| Matt Moore | SFO | 0.309 | 0.308 | -0.001 | 36.8% | 0.198 | 6.7% | 88.6% | 89.7 | 10.60% | 7.80% | 246 |
| Matt Strahm | KAN | 0.303 | 0.200 | -0.103 | 41.3% | 0.174 | 5.3% | 81.2% | 82.8 | 12.20% | 6.40% | 49 |
| Michael Wacha | STL | 0.292 | 0.319 | 0.027 | 46.4% | 0.202 | 3.6% | 84.1% | 84.6 | 6.90% | 4.80% | 173 |
| Nick Pivetta | PHI | 0.305 | 0.365 | 0.06 | 37.1% | 0.27 | 9.4% | 89.5% | 87.5 | 11.10% | 7.50% | 90 |
| Ricky Nolasco | ANA | 0.289 | 0.295 | 0.006 | 39.5% | 0.184 | 7.4% | 85.3% | 89.2 | 11.00% | 8.00% | 228 |
| Robert Gsellman | NYM | 0.319 | 0.314 | -0.005 | 54.5% | 0.201 | 11.3% | 87.5% | 85.9 | 4.70% | 3.50% | 214 |
| Sonny Gray | OAK | 0.292 | 0.311 | 0.019 | 56.7% | 0.201 | 3.2% | 88.1% | 87.3 | 5.10% | 3.50% | 137 |
| Steven Matz | NYM | 0.319 | 0.208 | -0.111 | 34.8% | 0.174 | 0.0% | 90.9% | ||||
| Zach Davies | MIL | 0.307 | 0.315 | 0.008 | 49.1% | 0.195 | 11.6% | 89.3% | 86.6 | 6.70% | 4.90% | 224 |
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 change depending on ever evolving situations throughout the day. This is the more opinionated part. If there are questions, it’ll help show you where my imaginary boundaries are drawn.
Value Tier One
Chris Sale (1) projects for one of the best performances we’ve seen this year in Philadelphia, not that these things always turn out the way we project him, but there’s really no reason other than ownership considerations that you can think of not to use him.
Value Tier Two
Nobody. Use Chris Sale.
Value Tier Three
Jeff Hoffman could get in trouble against any major league team with that fly ball rate at Coors. However, he’s facing one of the worst offenses in baseball at a low price and has shown strong upside so far. He can take a step back and still be worth the cost. No matchup at Coors should be considered good, but this might be the least bad it gets?
Jordan Montgomery is facing a team with some RH power in a park that’s supposed to be pitcher friendly, but has not suppressed HRs from the home team this year. They have struggled against LHP though.
Value Tier Four – These guys seem basically in line with their price tag. They are either barely usable 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.
Gio Gonzalez isn’t nearly as good as his ERA. He’s been stranding a lot of runners and walking too many batters. He’s probably adequately priced around $9K in a good matchup too. Standards are a little relaxed on this slate though.
Sonny Gray has a terrible matchup tonight, but has now become interesting in his willingness to double up on his slider usage occasionally. His high ground ball rate could otherwise help navigate this lineup. He could get destroyed, but now there might be more upside here than previously thought. One would think he’d do anything possible to avoid contact against this offense and the slider would seem the perfect weapon against all those loud RH bats.
You can find me on twitter @FreelanceBBall for any questions, comments, or insults.
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