Advanced Stats - Pitching: Wednesday, April 5th
Mid-week into the open of the season, you’d expect to see a decline in pitching talent, but that doesn’t really happen here. Part of the reason is that some teams have still only played one game and can call guys like Sale and DeGrom. One team even decided to throw Martin Perez before Cole Hamels. I’m also seeing a few names that might be interesting this year.
It’s been an exciting start to the season with pitchers hitting bombs and everyone throwing harder…but are they really throwing harder. Yesterday, we learned that MLB is now measuring velocity entirely with Statcast, which measures from a different point post-release than PitchF/x, the formerly employed tool and what we see in pages of Fangraphs. What’s this mean? It’s going to be a bit more difficult for us to compare velocity readings to past years until we find out exactly what’s going on. The early take though is that guys who have dropped (hi Zack Greinke) might be in more trouble than it seems.
Check out yesterday’s article for an explanation on some newly included stats this year, including DRA and some Statcast stuff. Remember that FanDuel has changed their pitcher pricing to de-emphasize the Win in favor of the Quality Start. A welcome, if not overdue change.
As always, 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. And all of which are now available right here on the site.
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 three year park factors. Home team is in bold. Team Def = UZR/150. L2Yrs is a rolling calendar. Hm/Rd xFIP is since the start of the 2016 season. Opp team offensive stats are wRC+.
| 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 | -1.4 | 4.5 | 4.4 | 52.5% | 0.97 | 2.57 | 5.37 | NYY | 84 | 93 | 107 |
| Bartolo Colon | ATL | -0.9 | 4.19 | 5.98 | 42.7% | 0.87 | 4.77 | 3.68 | NYM | 102 | 96 | 115 |
| Brandon Finnegan | CIN | 0.4 | 4.69 | 5.51 | 41.5% | 1.02 | 4.47 | 3.59 | PHI | 87 | 78 | 75 |
| Charlie Morton | HOU | 4.2 | 3.84 | 5.41 | 57.8% | 1.01 | 2.91 | SEA | 101 | 107 | 124 | |
| Chris Sale | BOS | 4.1 | 2.98 | 6.91 | 41.8% | 1.07 | 3.31 | 3.17 | PIT | 90 | 108 | 77 |
| Cole Hamels | TEX | 1.9 | 3.71 | 6.45 | 48.6% | 1.07 | 4.09 | 3.38 | CLE | 85 | 100 | 94 |
| Dan Straily | FLA | 2.8 | 4.66 | 5.83 | 32.9% | 1.02 | 4.82 | 4.11 | WAS | 96 | 95 | 91 |
| Danny Salazar | CLE | 5.4 | 3.59 | 5.86 | 45.5% | 1.07 | 3.83 | TEX | 106 | 98 | 85 | |
| Dylan Bundy | BAL | -3.2 | 4.23 | 5.09 | 35.9% | 1.04 | 4.42 | 4.47 | TOR | 97 | 103 | 80 |
| Garrett Richards | ANA | 6.5 | 3.99 | 6.37 | 53.6% | 0.95 | 3.9 | OAK | 83 | 91 | 84 | |
| J.A. Happ | TOR | 2.2 | 4.06 | 5.81 | 42.0% | 1.04 | 4.62 | 5.18 | BAL | 104 | 83 | 95 |
| Jacob deGrom | NYM | 1.3 | 3.29 | 6.28 | 44.9% | 0.87 | 3.31 | ATL | 86 | 89 | 105 | |
| James Paxton | SEA | -4.3 | 3.85 | 5.7 | 48.2% | 1.01 | 3.26 | 2.05 | HOU | 97 | 98 | 85 |
| Jameson Taillon | PIT | -2.8 | 3.61 | 5.78 | 52.4% | 1.07 | 3.46 | 3.71 | BOS | 121 | 113 | 58 |
| Jerad Eickhoff | PHI | 1.9 | 3.95 | 6.05 | 40.1% | 1.02 | 4.26 | 2.66 | CIN | 93 | 91 | 111 |
| Jharel Cotton | OAK | -8.3 | 4.02 | 5.82 | 37.6% | 0.95 | 4.42 | 2.89 | ANA | 98 | 99 | 104 |
| Matt Moore | SFO | 4.8 | 4.46 | 5.8 | 38.5% | 1.07 | 4.89 | 3.46 | ARI | 99 | 111 | 106 |
| Michael Pineda | NYY | 0.8 | 3.25 | 5.7 | 47.0% | 0.97 | 3.19 | 3.15 | TAM | 96 | 98 | 73 |
| Rich Hill | LOS | 2.3 | 3.09 | 5.8 | 45.9% | 0.9 | 3.81 | 3.33 | SDG | 78 | 98 | 97 |
| Taijuan Walker | ARI | -6.1 | 3.89 | 5.63 | 41.1% | 1.07 | 4.26 | 5.05 | SFO | 83 | 100 | 155 |
| Tanner Roark | WAS | 1.1 | 4.26 | 6.07 | 48.4% | 1.02 | 4.19 | 4.64 | FLA | 96 | 91 | 88 |
| Trevor Cahill | SDG | -5.9 | 3.71 | 4.28 | 59.3% | 0.9 | 3.68 | 4.37 | LOS | 107 | 109 | 65 |
| Tyler Chatwood | COL | -3.1 | 4.62 | 5.85 | 57.2% | 1.05 | 4.4 | 3.76 | MIL | 92 | 87 | 103 |
| Wily Peralta | MIL | -7.2 | 4.62 | 5.49 | 50.8% | 1.05 | 4.21 | 3.96 | COL | 84 | 96 | 73 |
One important note here is that with the season just under way, we’re still using some 2016 stats to start the season this week (even if it says 2017). Stats for the last seven, 14 or 30 days are also from the end of last season and should probably be largely ignored. They’re essentially filling in blank spaces right now. Also, we’re still using last year’s park factors as I’ve yet to find an updated site with multi-year factors. Feel free to leave a message if you know of one.
Charlie Morton threw only 17.1 innings for the Phillies last year, but with increased velocity and striking out 26.8% of the batters he faced. This spring, he looked to have maintained that velocity and possibly even increased it. He looked to be working up in the zone more often in the one start I saw, which may decrease his normally elite GB%, but also allow him to maintain a higher strikeout rate, which is great for DFS players.
Chris Sale is minus Don Cooper this year and his 25.7 K% last year was his first time below 30% since 2013, but had a 24.6 K-BB% over his last 12 starts. Without any information to the contrary, we’d expect him to be the same guy again this year. Boston can be touch on LHPs as were the Pirates last season, but that was more due to a 10.8 BB% than anything else. They struck out 23.1% of the time vs southpaws.
Cole Hamels sported a career high 9.1 BB%, but sustained an ERA below three and a half due to a 79.1 LOB%. He did keep the ball on the ground more often than in the past with a favorable 88 mph aEV with a 23.6 K% in line with his career rate. DRA liked him as much as his ERA for some unknown reason even if his other estimators were not as enthusiastic. Cleveland was just an average offense against LHP last year and Texas is on run friendly environment that usually doesn’t have to concern itself with difficult early season weather conditions.
Jacob deGrom ended his season with nerve surgery, but really didn’t seem the same for most of the season with a drop in velocity and his strikeout rate, which were masked with a low ERA until his last few starts when the injury took hold. All looks good this spring though, as he welcomed back “(classname)95-97 mph(title tooltip)”: http://www.amazinavenue.com/2017/3/29/14984054/mets-jacob-degrom-2017-new-york heaters. A completely healthy deGrom is potentially a Cy Young contender.
James Paxton had a partial breakout last year. He was the league’s second hardest thrower behind Syndergaard and saw a nice increase to his strikeout rate, including 29.2% over his last five starts. Curiously, he appeared to struggle with hard contact issues (19.0 Hard-Soft%, 91 mph aEV), but was only barreled up on 3.8% of BBEs and 2.5% of PAs, each second lowest on the slate. Though he had little platoon split last year (and even has a reverse one for his career), he did allow eight of nine HRs to RHBs and that is the predominant side for a powerful Houston order.
Jerad Eickhoff was a perfectly average pitcher in nearly every respect last year and if that’s what he is, the Phillies should be very happy. He did have a bit of a fly ball slant in a small park, which led to 30 HRs and there’s similar concern in Cincinnati, but it’s an otherwise favorable spot overall.
Jharel Cotton is a pitcher I’m excited to watch this year. His changeup has devastating potential and he rode that to a 29.5 K% in AAA last season before debuting with a 20.5 K% in 29.1 major league innings. There is some concern about finding a third workable pitch, but he did throw a slider and cutter last year as well. The Angels were DFS buzz kills last season, rarely striking out they’ve added a few swings and misses in the latter part of the order this year.
Michael Pineda was a polarizing pitcher last year, but is one of those guys who may be better in DFS than real life. He struggles with contact occasionally with his defense and home park doing him no favors, but the swing and miss stuff is elite. Few people even acknowledge that his ERA was below four over the last four months of the season (22 starts), never allowing more than five runs over that span. Five runs is obviously not good, but it might not torpedo your lineup with his strikeout potential. The good news is that he’s pitching in the most pitcher friendly park in the division tonight and the Rays had a 16.8 K-BB% vs RHP last year.
Rich Hill was dominant in the few games he actually pitched for the Dodgers last season with a 26.6 K-BB%. He tops today’s board with an 87.7 mph aEV, 2.6% Barrels/BBE and 1.4% Barrels/PA. The one issue is that the Dodgers held him to a fairly low pitch count, likely due to injury issues. Perhaps that changes this year. He’s certainly in a great spot against an offense that struck out 25.3% of the time vs LHP last year.
Tyler Chatwood leads today’s pitchers (min. 150 IP) with a 57.2 GB% and even chipped in a 17.2 IFFB% with an 87.9 mph aEV, 4.4% Barrels/BBE and 2.7% Barrels/PA last season, proving to be an exceptional contact manager. The hope today is that Milwaukee’s 25.8 K% vs RHP last year can push his low strikeout rate into the useful zone.
Wily Peralta has always thrown hard without the results to match. He did tick up a bit more after missing July leading to some interesting numbers underneath the hood, including an 11.0 SwStr% over his last 10 starts, which led to a league average strikeout rate (20.3%) and a 2.92 ERA (but estimators a bit higher – 81.7 LOB%). That guy might be interesting, though he pitches in a difficult environment.
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 (.298 BABIP – 72.3 LOB% – 13.3 HR/FB)
Dylan Bundy (.299 – 79.7% – 13.3) is someone we may potentially have something interesting things to say about because despite his disastrous spring results, there may be reason for some optimism, but an opening assignment against the Jays may not be the time to do that.
J.A. Happ (.268 – 79.7% – 11.1) is one of two qualified starters on today’s slate with three estimators at least a run worse than his ERA. His cost was often propped up by a high Win total, but $7K on DraftKings does seem more reasonable against a Baltimore team who struggled against LHP last year, but should probably be better going forward.
Tanner Roark (.269 – 79.5% – 9.4) is the only qualified pitcher on the board separated by at least 0.96 runs from all four estimators last season. He lived off incredibly weak contact in the first half (-4.5 Hard-Soft%), but wasn’t really exceptional in the second half (8.4 Hard-Soft%). Remove a 15 strikeout performance in his fourth start of the season last year and his 20.1 K% drops to 18.9% in all other starts.
Brandon Finnegan (.256 – 77% – 14.9) may have looked like to have close the season strong with a 1.93 ERA over his last seven starts, but with an 82.5% strand rate and 7.9 HR/FB. RHBs particularly mashed him last year with a .334 wOBA, 38.3 Hard% and 27 HRs. He has talent, but is going to need to show the ability to harness more of it.
Dan Straily (.239 – 81.2% – 12.0) should not expect to repeat the BABIP or LOB%.
Bartolo Colon (.291 – 76.5% – 11.5) had eight unearned runs last year (9.9% of his season total) or his ERA might have been a bit closer to his estimators. His 5.5 SwStr% was the lowest in the majors among qualified starters last season. Only one other pitcher was below 7%. He’s facing the team he used to pitch for tonight, which, considering the recent health of Mets pitchers and the relationship between these front offices the last couple of years, will probably be the team he’s pitching for again come late July. He’s the qualified pitcher furthest from his DRA today too.
NO THANK YOU (In order from least to most offensive)
Taijuan Walker was inconsistent last season and perhaps even disappointing for stretches last year, but it’s certainly plausible that bone spurs in his foot (removed this off-season) played a part in his ability to push off. He utilized a new slider to rack up the Ks this spring. There is some optimism for him this year, but facing a low strikeout offense in a dangerous environment persuades me to take a wait and see approach. He’s a difficult cutoff point today on whom I’ve been wavering quite a bit and really wouldn’t mind some GPP exposure just in case at $7.5K on either site.
Danny Salazar is a difficult exclusion, but simply carries too much risk here. As little as we like to pay attention to pre-season stats, he has a rough spring and did end the season with some arm issues and pitches in a difficult environment in Texas tonight. While his $8.1K cost on DraftKings is intriguing for a guy who can have an elite strikeout rate, he also had the highest aEV on the slate last year, by nearly a full mph (91.9).
Garrett Richards has health concerns after electing not to have TJ surgery after just 34 innings last season. He did hit 99 mph in a mid-March start, but quickly fell off to a still very respectable 96.
Matt Moore struggled with command and control last year and starts this season in a near hitter’s paradise against an offense that torched LHP last year (20.1 HR/FB, 35.3 Hard%) despite a 23.3 K%. He allowed 20 HRs with a 42.8 FB% to RHBs last year.
Jameson Taillon has some merit, which may be better spoken of when he’s not facing the Red Sox in Boston.
Alex Cobb struggled and was hit hard (as the Statcast data shows) in his brief return from TJ surgery late last season. We’d like to see a return to form or something close to it.
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 | 15.4% | 6.7% | Home | 26.5% | 5.9% | L14 Days | 12.1% | 9.1% |
| Bartolo Colon | Braves | L2 Years | 16.4% | 3.5% | Road | 11.5% | 3.9% | L14 Days | 20.0% | 0.0% |
| Brandon Finnegan | Reds | L2 Years | 20.4% | 11.3% | Home | 19.5% | 7.9% | L14 Days | 23.5% | 0.0% |
| Charlie Morton | Astros | L2 Years | 18.1% | 7.7% | Home | 27.7% | 12.8% | L14 Days | ||
| Chris Sale | Red Sox | L2 Years | 28.8% | 4.9% | Home | 27.8% | 4.3% | L14 Days | 24.7% | 1.4% |
| Cole Hamels | Rangers | L2 Years | 24.0% | 8.0% | Home | 23.3% | 9.2% | L14 Days | 24.1% | 3.7% |
| Dan Straily | Marlins | L2 Years | 20.3% | 9.3% | Road | 20.8% | 8.2% | L14 Days | 22.6% | 7.6% |
| Danny Salazar | Indians | L2 Years | 26.6% | 8.7% | Road | 28.0% | 12.5% | L14 Days | ||
| Dylan Bundy | Orioles | L2 Years | 21.9% | 8.9% | Home | 21.6% | 7.0% | L14 Days | 18.6% | 7.0% |
| Garrett Richards | Angels | L2 Years | 20.7% | 9.0% | Road | 22.9% | 8.6% | L14 Days | ||
| J.A. Happ | Blue Jays | L2 Years | 20.8% | 6.9% | Road | 18.1% | 8.1% | L14 Days | 13.9% | 8.9% |
| Jacob deGrom | Mets | L2 Years | 25.7% | 5.5% | Home | 29.1% | 7.5% | L14 Days | ||
| James Paxton | Mariners | L2 Years | 21.4% | 6.6% | Road | 22.7% | 5.1% | L14 Days | 36.2% | 2.1% |
| Jameson Taillon | Pirates | L2 Years | 20.3% | 4.1% | Road | 20.0% | 3.8% | L14 Days | 25.0% | 6.8% |
| Jerad Eickhoff | Phillies | L2 Years | 21.3% | 5.4% | Road | 18.8% | 5.2% | L14 Days | 30.7% | 3.2% |
| Jharel Cotton | Athletics | L2 Years | 20.5% | 3.6% | Home | 21.5% | 3.1% | L14 Days | 28.1% | 1.6% |
| Matt Moore | Giants | L2 Years | 20.1% | 8.5% | Road | 19.8% | 10.6% | L14 Days | 25.0% | 4.4% |
| Michael Pineda | Yankees | L2 Years | 25.5% | 5.2% | Road | 27.1% | 7.0% | L14 Days | 34.9% | 10.6% |
| Rich Hill | Dodgers | L2 Years | 30.3% | 7.0% | Home | 26.0% | 8.5% | L14 Days | 26.2% | 4.8% |
| Taijuan Walker | Diamondbacks | L2 Years | 21.6% | 6.0% | Home | 21.3% | 7.1% | L14 Days | 21.3% | 14.7% |
| Tanner Roark | Nationals | L2 Years | 18.3% | 7.5% | Home | 21.8% | 9.1% | L14 Days | 22.1% | 11.8% |
| Trevor Cahill | Padres | L2 Years | 21.7% | 10.8% | Road | 22.6% | 10.3% | L14 Days | 14.3% | 14.3% |
| Tyler Chatwood | Rockies | L2 Years | 17.5% | 10.5% | Road | 19.1% | 11.3% | L14 Days | 27.5% | 11.8% |
| Wily Peralta | Brewers | L2 Years | 14.8% | 7.8% | Home | 18.5% | 8.1% | L14 Days | 18.2% | 6.8% |
K/BB Chart – Opponent
| Opponent | Split | K% | BB% | Split | K% | BB% | Split | K% | BB% |
|---|---|---|---|---|---|---|---|---|---|
| Yankees | Road | 19.8% | 7.0% | RH | 20.0% | 7.8% | L7Days | 17.4% | 10.4% |
| Mets | Home | 21.0% | 9.2% | RH | 21.0% | 8.4% | L7Days | 16.4% | 9.4% |
| Phillies | Road | 21.8% | 7.0% | LH | 22.7% | 6.9% | L7Days | 23.4% | 5.9% |
| Mariners | Road | 20.2% | 7.4% | RH | 20.2% | 8.2% | L7Days | 23.6% | 8.0% |
| Pirates | Road | 22.5% | 8.8% | LH | 23.1% | 10.8% | L7Days | 26.8% | 8.1% |
| Indians | Road | 21.7% | 7.4% | LH | 20.5% | 8.0% | L7Days | 20.7% | 12.0% |
| Nationals | Home | 19.6% | 9.0% | RH | 20.0% | 8.6% | L7Days | 22.5% | 11.3% |
| Rangers | Home | 19.2% | 8.0% | RH | 20.0% | 7.2% | L7Days | 23.3% | 8.1% |
| Blue Jays | Road | 22.8% | 9.9% | RH | 22.4% | 10.1% | L7Days | 20.2% | 13.3% |
| Athletics | Home | 18.4% | 6.9% | RH | 19.0% | 7.6% | L7Days | 21.3% | 7.1% |
| Orioles | Home | 20.4% | 8.1% | LH | 22.5% | 8.4% | L7Days | 23.9% | 8.3% |
| Braves | Road | 20.5% | 8.0% | RH | 19.7% | 8.5% | L7Days | 23.1% | 8.8% |
| Astros | Home | 24.5% | 9.0% | LH | 23.4% | 8.7% | L7Days | 21.5% | 5.3% |
| Red Sox | Home | 16.6% | 8.8% | RH | 18.0% | 8.6% | L7Days | 17.1% | 11.1% |
| Reds | Home | 21.8% | 8.3% | RH | 20.6% | 7.3% | L7Days | 20.4% | 5.4% |
| Angels | Road | 16.6% | 7.7% | RH | 16.4% | 7.7% | L7Days | 14.4% | 8.8% |
| Diamondbacks | Home | 23.5% | 7.3% | LH | 23.3% | 8.8% | L7Days | 22.2% | 7.4% |
| Rays | Home | 25.9% | 7.7% | RH | 24.2% | 7.4% | L7Days | 20.8% | 5.3% |
| Padres | Road | 25.9% | 6.7% | LH | 25.3% | 8.1% | L7Days | 25.5% | 5.0% |
| Giants | Road | 18.5% | 8.5% | RH | 17.3% | 9.5% | L7Days | 16.9% | 9.7% |
| Marlins | Road | 20.0% | 7.2% | RH | 19.0% | 7.3% | L7Days | 20.3% | 7.4% |
| Dodgers | Home | 21.5% | 8.5% | RH | 21.1% | 8.4% | L7Days | 20.5% | 6.0% |
| Brewers | Home | 26.1% | 10.1% | RH | 25.8% | 9.4% | L7Days | 23.7% | 8.5% |
| Rockies | Road | 24.1% | 6.9% | RH | 20.7% | 7.7% | L7Days | 28.1% | 3.5% |
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 | 29.6% | 21.7% | 12.3% | 2017 | 29.6% | 21.7% | 12.3% | Home | 43.5% | 20.0% | 26.1% | L14 Days | 38.5% | 37.5% | 23.1% |
| Bartolo Colon | Braves | L2 Years | 32.1% | 11.1% | 15.3% | 2017 | 35.4% | 11.5% | 19.2% | Road | 36.7% | 11.0% | 23.6% | L14 Days | 43.8% | 15.8% | 35.5% |
| Brandon Finnegan | Reds | L2 Years | 34.9% | 16.0% | 17.6% | 2017 | 35.9% | 14.9% | 19.5% | Home | 36.3% | 17.7% | 20.7% | L14 Days | 30.8% | 0.0% | 15.4% |
| Charlie Morton | Astros | L2 Years | 30.1% | 14.9% | 9.1% | 2017 | 20.5% | 14.3% | 4.6% | Home | 17.9% | 0.0% | -3.5% | L14 Days | |||
| Chris Sale | Red Sox | L2 Years | 28.7% | 12.2% | 9.9% | 2017 | 31.7% | 11.9% | 14.7% | Home | 33.8% | 20.8% | 17.1% | L14 Days | 34.0% | 22.2% | 18.0% |
| Cole Hamels | Rangers | L2 Years | 29.4% | 13.0% | 8.4% | 2017 | 32.0% | 14.0% | 11.6% | Home | 33.1% | 16.3% | 13.2% | L14 Days | 38.5% | 7.7% | 25.7% |
| Dan Straily | Marlins | L2 Years | 31.9% | 11.9% | 16.7% | 2017 | 32.2% | 12.0% | 17.4% | Road | 31.1% | 14.9% | 14.4% | L14 Days | 25.0% | 17.6% | 13.9% |
| Danny Salazar | Indians | L2 Years | 30.9% | 12.5% | 14.6% | 2017 | 33.8% | 12.8% | 18.7% | Road | 31.8% | 11.9% | 13.4% | L14 Days | |||
| Dylan Bundy | Orioles | L2 Years | 28.0% | 13.3% | 4.4% | 2017 | 28.0% | 13.3% | 4.4% | Home | 27.2% | 12.2% | 1.6% | L14 Days | 32.3% | 18.2% | 6.5% |
| Garrett Richards | Angels | L2 Years | 25.6% | 11.3% | 3.8% | 2017 | 35.7% | 7.1% | 20.4% | Road | 29.8% | 7.1% | 19.2% | L14 Days | |||
| J.A. Happ | Blue Jays | L2 Years | 31.4% | 10.2% | 13.4% | 2017 | 31.6% | 11.1% | 13.8% | Road | 30.8% | 11.7% | 12.7% | L14 Days | 25.0% | 0.0% | 3.3% |
| Jacob deGrom | Mets | L2 Years | 28.6% | 10.4% | 9.3% | 2017 | 31.3% | 11.5% | 12.3% | Home | 28.0% | 11.3% | 6.5% | L14 Days | |||
| James Paxton | Mariners | L2 Years | 31.8% | 9.3% | 16.1% | 2017 | 33.1% | 8.2% | 19.0% | Road | 33.2% | 9.4% | 18.1% | L14 Days | 48.3% | 11.1% | 31.1% |
| Jameson Taillon | Pirates | L2 Years | 33.2% | 15.5% | 15.9% | 2017 | 33.2% | 15.5% | 15.9% | Road | 30.6% | 21.2% | 12.4% | L14 Days | 30.0% | 15.4% | 3.3% |
| Jerad Eickhoff | Phillies | L2 Years | 31.8% | 12.3% | 11.7% | 2017 | 30.8% | 13.1% | 10.8% | Road | 33.1% | 11.1% | 15.3% | L14 Days | 29.3% | 26.7% | 0.0% |
| Jharel Cotton | Athletics | L2 Years | 28.2% | 9.8% | 5.8% | 2017 | 28.2% | 9.8% | 5.8% | Home | 30.6% | 10.7% | 4.1% | L14 Days | 35.6% | 14.3% | 17.8% |
| Matt Moore | Giants | L2 Years | 31.0% | 10.6% | 14.0% | 2017 | 30.8% | 10.4% | 15.5% | Road | 30.4% | 11.3% | 16.3% | L14 Days | 34.0% | 5.6% | 25.5% |
| Michael Pineda | Yankees | L2 Years | 31.4% | 15.9% | 13.9% | 2017 | 32.7% | 17.0% | 15.5% | Road | 30.4% | 9.6% | 11.6% | L14 Days | 25.0% | 17.6% | 11.1% |
| Rich Hill | Dodgers | L2 Years | 27.1% | 5.1% | 3.6% | 2017 | 28.3% | 4.2% | 6.0% | Home | 31.0% | 4.8% | 10.4% | L14 Days | 27.6% | 14.3% | 6.9% |
| Taijuan Walker | Diamondbacks | L2 Years | 29.5% | 15.1% | 10.9% | 2017 | 28.6% | 17.6% | 7.8% | Home | 27.7% | 16.1% | 6.4% | L14 Days | 27.1% | 21.4% | 2.1% |
| Tanner Roark | Nationals | L2 Years | 25.1% | 11.7% | 2.4% | 2017 | 24.3% | 9.4% | 1.2% | Home | 25.4% | 7.1% | 3.5% | L14 Days | 20.0% | 17.6% | 4.4% |
| Trevor Cahill | Padres | L2 Years | 30.9% | 18.0% | 9.7% | 2017 | 29.8% | 18.4% | 9.6% | Road | 39.6% | 21.1% | 19.8% | L14 Days | 30.0% | 0.0% | 30.0% |
| Tyler Chatwood | Rockies | L2 Years | 29.5% | 12.4% | 10.5% | 2017 | 29.5% | 12.4% | 10.5% | Road | 24.8% | 6.2% | 0.9% | L14 Days | 25.8% | 11.1% | 3.2% |
| Wily Peralta | Brewers | L2 Years | 32.9% | 15.3% | 15.3% | 2017 | 33.1% | 17.1% | 16.4% | Home | 37.6% | 19.1% | 21.7% | L14 Days | 21.2% | 0.0% | 6.0% |
Batted Ball Charts – Opponent
| Opponent | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% | Split | Hard% | HR/FB% | Hd-St% |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Yankees | Road | 29.6% | 10.1% | 13.0% | RH | 29.5% | 13.4% | 12.9% | L7Days | 35.1% | 14.8% | 16.2% |
| Mets | Home | 34.3% | 13.6% | 13.3% | RH | 33.7% | 13.3% | 15.2% | L7Days | 31.5% | 9.8% | 8.8% |
| Phillies | Road | 31.5% | 12.2% | 11.2% | LH | 27.1% | 9.6% | 7.0% | L7Days | 31.6% | 6.3% | 10.9% |
| Mariners | Road | 31.1% | 14.9% | 12.0% | RH | 31.4% | 14.9% | 13.2% | L7Days | 30.3% | 17.7% | 4.7% |
| Pirates | Road | 31.0% | 11.9% | 11.3% | LH | 33.0% | 13.0% | 14.6% | L7Days | 27.2% | 15.2% | 10.1% |
| Indians | Road | 30.7% | 10.8% | 11.4% | LH | 29.2% | 10.0% | 11.3% | L7Days | 33.8% | 6.3% | 14.1% |
| Nationals | Home | 32.0% | 12.9% | 13.8% | RH | 32.8% | 12.1% | 14.9% | L7Days | 35.1% | 12.1% | 16.6% |
| Rangers | Home | 31.5% | 13.7% | 12.2% | RH | 31.1% | 14.1% | 12.0% | L7Days | 34.9% | 10.4% | 15.2% |
| Blue Jays | Road | 33.1% | 14.6% | 12.8% | RH | 33.3% | 15.0% | 14.6% | L7Days | 26.3% | 6.7% | 3.5% |
| Athletics | Home | 27.4% | 8.6% | 9.5% | RH | 29.4% | 10.0% | 10.4% | L7Days | 35.9% | 8.9% | 22.1% |
| Orioles | Home | 33.1% | 16.6% | 12.0% | LH | 31.7% | 12.1% | 11.1% | L7Days | 38.5% | 14.3% | 16.7% |
| Braves | Road | 28.0% | 10.5% | 7.9% | RH | 29.4% | 9.7% | 11.0% | L7Days | 29.2% | 15.7% | 7.7% |
| Astros | Home | 32.9% | 14.5% | 15.2% | LH | 34.3% | 14.4% | 17.4% | L7Days | 27.4% | 4.7% | 8.5% |
| Red Sox | Home | 33.5% | 12.9% | 14.3% | RH | 34.2% | 13.2% | 15.2% | L7Days | 25.8% | 7.5% | 6.4% |
| Reds | Home | 30.7% | 12.7% | 13.8% | RH | 30.0% | 11.5% | 12.1% | L7Days | 24.1% | 13.1% | 3.9% |
| Angels | Road | 30.9% | 9.4% | 11.8% | RH | 30.5% | 9.9% | 11.8% | L7Days | 25.3% | 8.5% | 5.5% |
| Diamondbacks | Home | 35.2% | 17.7% | 20.1% | LH | 35.3% | 20.1% | 19.3% | L7Days | 35.5% | 21.1% | 18.9% |
| Rays | Home | 33.4% | 13.4% | 14.4% | RH | 32.5% | 14.2% | 12.9% | L7Days | 30.9% | 4.7% | 8.9% |
| Padres | Road | 30.4% | 13.8% | 11.1% | LH | 32.5% | 14.9% | 14.4% | L7Days | 22.7% | 8.3% | 6.0% |
| Giants | Road | 31.5% | 10.1% | 11.8% | RH | 29.5% | 8.4% | 9.7% | L7Days | 27.7% | 9.6% | 10.6% |
| Marlins | Road | 29.4% | 10.4% | 9.3% | RH | 29.4% | 9.8% | 8.9% | L7Days | 29.9% | 10.0% | 11.9% |
| Dodgers | Home | 33.0% | 15.7% | 15.7% | RH | 34.6% | 15.6% | 18.0% | L7Days | 28.5% | 6.7% | 8.9% |
| Brewers | Home | 34.3% | 16.3% | 16.7% | RH | 32.2% | 15.5% | 13.0% | L7Days | 26.4% | 20.0% | 5.0% |
| Rockies | Road | 30.5% | 12.3% | 10.6% | RH | 32.9% | 14.6% | 15.4% | L7Days | 33.1% | 4.8% | 15.6% |
K/SwStr Chart (2016 LG AVG – 20.2 K% – 9.5 SwStr% – 2.13 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 | 15.4% | 7.5% | 2.05 | 10.7% | 7.6% | 1.41 |
| Bartolo Colon | ATL | 16.2% | 5.5% | 2.95 | 16.8% | 5.5% | 3.05 |
| Brandon Finnegan | CIN | 19.8% | 9.6% | 2.06 | 22.2% | 9.2% | 2.41 |
| Charlie Morton | HOU | 26.8% | 12.3% | 2.18 | |||
| Chris Sale | BOS | 25.7% | 11.3% | 2.27 | 27.9% | 13.1% | 2.13 |
| Cole Hamels | TEX | 23.6% | 12.2% | 1.93 | 23.8% | 12.0% | 1.98 |
| Dan Straily | FLA | 20.5% | 10.2% | 2.01 | 22.6% | 11.7% | 1.93 |
| Danny Salazar | CLE | 27.6% | 11.1% | 2.49 | 34.9% | 13.4% | 2.60 |
| Dylan Bundy | BAL | 21.9% | 10.5% | 2.09 | 21.4% | 10.1% | 2.12 |
| Garrett Richards | ANA | 23.0% | 11.2% | 2.05 | |||
| J.A. Happ | TOR | 20.5% | 9.6% | 2.14 | 14.6% | 7.7% | 1.90 |
| Jacob deGrom | NYM | 23.7% | 10.7% | 2.21 | |||
| James Paxton | SEA | 22.9% | 11.7% | 1.96 | 29.2% | 12.0% | 2.43 |
| Jameson Taillon | PIT | 20.3% | 8.3% | 2.45 | 20.2% | 8.6% | 2.35 |
| Jerad Eickhoff | PHI | 20.6% | 9.4% | 2.19 | 24.3% | 9.6% | 2.53 |
| Jharel Cotton | OAK | 20.5% | 12.5% | 1.64 | 20.5% | 12.5% | 1.64 |
| Matt Moore | SFO | 21.2% | 10.4% | 2.04 | 23.9% | 12.3% | 1.94 |
| Michael Pineda | NYY | 27.4% | 14.1% | 1.94 | 31.7% | 14.5% | 2.19 |
| Rich Hill | LOS | 29.4% | 10.6% | 2.77 | 34.3% | 10.9% | 3.15 |
| Taijuan Walker | ARI | 20.8% | 10.0% | 2.08 | 22.3% | 11.0% | 2.03 |
| Tanner Roark | WAS | 20.1% | 8.9% | 2.26 | 23.2% | 10.0% | 2.32 |
| Trevor Cahill | SDG | 23.2% | 11.0% | 2.11 | 18.0% | 7.5% | 2.40 |
| Tyler Chatwood | COL | 17.5% | 7.8% | 2.24 | 23.2% | 10.7% | 2.17 |
| Wily Peralta | MIL | 16.8% | 8.5% | 1.98 | 18.9% | 11.1% | 1.70 |
Bartolo Colon has lived in this area for the last several years, though this strikeout rate makes him virtually unusable.
Rich Hill is probably in line for something closer to 25% over a higher workload.
ERA Estimators Chart (2016 LG AVG – 4.34 ERA – 4.30 SIERA – 4.24 xFIP – 4.30 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 | 8.59 | 4.5 | -4.09 | 4.39 | -4.2 | 5.6 | -2.99 | 5.04 | -3.55 | 10.06 | 5.18 | -4.88 | 5.11 | -4.95 | 6.97 | -3.09 |
| Bartolo Colon | ATL | 3.43 | 4.37 | 0.94 | 4.17 | 0.74 | 3.99 | 0.56 | 4.96 | 1.53 | 3.82 | 4.32 | 0.5 | 4.39 | 0.57 | 4.24 | 0.42 |
| Brandon Finnegan | CIN | 3.98 | 4.92 | 0.94 | 4.87 | 0.89 | 5.19 | 1.21 | 4.84 | 0.86 | 2.08 | 5.22 | 3.14 | 5.45 | 3.37 | 4.65 | 2.57 |
| Charlie Morton | HOU | 4.15 | 3.56 | -0.59 | 3.01 | -1.14 | 3.09 | -1.06 | 3.06 | -1.09 | |||||||
| Chris Sale | BOS | 3.34 | 3.43 | 0.09 | 3.58 | 0.24 | 3.46 | 0.12 | 3.00 | -0.34 | 4.39 | 2.82 | -1.57 | 3.13 | -1.26 | 4 | -0.39 |
| Cole Hamels | TEX | 3.32 | 3.99 | 0.67 | 3.85 | 0.53 | 3.98 | 0.66 | 3.48 | 0.16 | 5.86 | 4.09 | -1.77 | 3.86 | -2 | 4.7 | -1.16 |
| Dan Straily | FLA | 3.76 | 4.67 | 0.91 | 5.02 | 1.26 | 4.88 | 1.12 | 4.59 | 0.83 | 3.13 | 4.86 | 1.73 | 5.56 | 2.43 | 5.5 | 2.37 |
| Danny Salazar | CLE | 3.87 | 3.86 | -0.01 | 3.74 | -0.13 | 3.74 | -0.13 | 3.53 | -0.34 | 3.72 | 2.7 | -1.02 | 2.32 | -1.4 | 3.97 | 0.25 |
| Dylan Bundy | BAL | 4.02 | 4.23 | 0.21 | 4.61 | 0.59 | 4.7 | 0.68 | 4.07 | 0.05 | 6.63 | 4.54 | -2.09 | 4.57 | -2.06 | 6.15 | -0.48 |
| Garrett Richards | ANA | 2.34 | 4.22 | 1.88 | 3.91 | 1.57 | 3.32 | 0.98 | 3.07 | 0.73 | |||||||
| J.A. Happ | TOR | 3.18 | 4.28 | 1.1 | 4.18 | 1 | 3.96 | 0.78 | 4.26 | 1.08 | 2.97 | 5.18 | 2.21 | 5.14 | 2.17 | 4.02 | 1.05 |
| Jacob deGrom | NYM | 3.04 | 3.66 | 0.62 | 3.47 | 0.43 | 3.32 | 0.28 | 3.86 | 0.82 | |||||||
| James Paxton | SEA | 3.79 | 3.54 | -0.25 | 3.35 | -0.44 | 2.8 | -0.99 | 3.51 | -0.28 | 3.68 | 2.82 | -0.86 | 2.65 | -1.03 | 2.06 | -1.62 |
| Jameson Taillon | PIT | 3.38 | 3.61 | 0.23 | 3.43 | 0.05 | 3.71 | 0.33 | 3.67 | 0.29 | 3.86 | 4.04 | 0.18 | 4.11 | 0.25 | 4.15 | 0.29 |
| Jerad Eickhoff | PHI | 3.65 | 4.05 | 0.4 | 4.15 | 0.5 | 4.19 | 0.54 | 3.90 | 0.25 | 2.52 | 3.42 | 0.9 | 3.63 | 1.11 | 4.63 | 2.11 |
| Jharel Cotton | OAK | 2.15 | 4.02 | 1.87 | 4.32 | 2.17 | 3.76 | 1.61 | 4.21 | 2.06 | 2.15 | 4.02 | 1.87 | 4.32 | 2.17 | 3.76 | 1.61 |
| Matt Moore | SFO | 4.08 | 4.39 | 0.31 | 4.56 | 0.48 | 4.17 | 0.09 | 4.98 | 0.90 | 5.17 | 3.97 | -1.2 | 3.94 | -1.23 | 3.43 | -1.74 |
| Michael Pineda | NYY | 4.82 | 3.4 | -1.42 | 3.3 | -1.52 | 3.8 | -1.02 | 3.49 | -1.33 | 3.21 | 3.43 | 0.22 | 3.29 | 0.08 | 4.18 | 0.97 |
| Rich Hill | LOS | 2.12 | 3.29 | 1.17 | 3.36 | 1.24 | 2.39 | 0.27 | 3.08 | 0.96 | 2.22 | 2.59 | 0.37 | 2.6 | 0.38 | 2.05 | -0.17 |
| Taijuan Walker | ARI | 4.22 | 4.13 | -0.09 | 4.28 | 0.06 | 4.99 | 0.77 | 4.13 | -0.09 | 4.31 | 4.11 | -0.2 | 4.15 | -0.16 | 5.51 | 1.2 |
| Tanner Roark | WAS | 2.83 | 4.32 | 1.49 | 4.17 | 1.34 | 3.79 | 0.96 | 3.88 | 1.05 | 2.6 | 4.59 | 1.99 | 4.28 | 1.68 | 4.01 | 1.41 |
| Trevor Cahill | SDG | 2.74 | 3.93 | 1.19 | 3.93 | 1.19 | 4.35 | 1.61 | 3.77 | 1.03 | 2.53 | 4.16 | 1.63 | 3.71 | 1.18 | 5.68 | 3.15 |
| Tyler Chatwood | COL | 3.87 | 4.62 | 0.75 | 4.37 | 0.5 | 4.32 | 0.45 | 4.29 | 0.42 | 4.4 | 3.91 | -0.49 | 3.87 | -0.53 | 4.74 | 0.34 |
| Wily Peralta | MIL | 4.86 | 4.51 | -0.35 | 4.22 | -0.64 | 4.71 | -0.15 | 4.60 | -0.26 | 2.84 | 3.88 | 1.04 | 3.62 | 0.78 | 3.43 | 0.59 |
There’s an exorbitant number of outliers today, most of whom we’re uninterested in and many who had shortened seasons last year. Michael Pineda is really the only full workload one we’re interested in and his issues have been covered to death, not to mention they weren’t nearly so apparent from June on.
BABIP & Statcast Chart (2016 LG AVG – .298 BABIP – 44.3 GB% – 20.9 LD% – 9.5 IFFB% – 87.2 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 | 0.297 | 0.355 | 0.058 | 52.5% | 0.188 | 8.7% | 88.1% | 90.5 | 9.70% | 6.70% | 72 |
| Bartolo Colon | ATL | 0.293 | 0.291 | -0.002 | 43.2% | 0.227 | 11.0% | 92.7% | 90.3 | 5.10% | 3.70% | 565 |
| Brandon Finnegan | CIN | 0.290 | 0.256 | -0.034 | 38.1% | 0.225 | 6.2% | 86.0% | 88.8 | 7.90% | 4.90% | 454 |
| Charlie Morton | HOU | 0.306 | 0.326 | 0.02 | 62.8% | 0.209 | 0.0% | 83.3% | 88.9 | 5.30% | 2.80% | 38 |
| Chris Sale | BOS | 0.293 | 0.279 | -0.014 | 41.2% | 0.21 | 9.3% | 83.2% | 89.2 | 5.70% | 3.40% | 542 |
| Cole Hamels | TEX | 0.292 | 0.299 | 0.007 | 49.6% | 0.195 | 4.1% | 85.1% | 88 | 6.60% | 4.00% | 519 |
| Dan Straily | FLA | 0.303 | 0.239 | -0.064 | 32.0% | 0.199 | 7.8% | 85.3% | 89.3 | 7.80% | 4.80% | 489 |
| Danny Salazar | CLE | 0.289 | 0.307 | 0.018 | 47.8% | 0.171 | 10.4% | 83.6% | 91.9 | 7.00% | 3.90% | 329 |
| Dylan Bundy | BAL | 0.299 | 0.299 | 0 | 35.9% | 0.219 | 19.3% | 84.2% | 88.5 | 6.40% | 3.60% | 266 |
| Garrett Richards | ANA | 0.301 | 0.302 | 0.001 | 45.8% | 0.25 | 7.1% | 85.9% | 89.7 | 5.70% | 3.40% | 87 |
| J.A. Happ | TOR | 0.282 | 0.268 | -0.014 | 42.5% | 0.22 | 9.6% | 85.0% | 90 | 7.20% | 4.60% | 511 |
| Jacob deGrom | NYM | 0.308 | 0.312 | 0.004 | 45.6% | 0.227 | 7.7% | 84.9% | 88.7 | 6.50% | 4.00% | 371 |
| James Paxton | SEA | 0.292 | 0.347 | 0.055 | 48.1% | 0.219 | 8.2% | 85.4% | 91 | 3.80% | 2.50% | 338 |
| Jameson Taillon | PIT | 0.306 | 0.287 | -0.019 | 52.4% | 0.202 | 9.5% | 92.2% | 89.4 | 4.70% | 2.90% | 256 |
| Jerad Eickhoff | PHI | 0.304 | 0.278 | -0.026 | 40.7% | 0.201 | 12.7% | 88.6% | 89.5 | 6.20% | 3.90% | 513 |
| Jharel Cotton | OAK | 0.299 | 0.198 | -0.101 | 37.6% | 0.141 | 24.4% | 85.5% | 88.9 | 5.20% | 3.60% | 77 |
| Matt Moore | SFO | 0.287 | 0.285 | -0.002 | 38.2% | 0.197 | 7.9% | 84.0% | 89.2 | 7.10% | 4.30% | 504 |
| Michael Pineda | NYY | 0.292 | 0.339 | 0.047 | 45.8% | 0.216 | 3.8% | 86.2% | 90.3 | 7.30% | 4.20% | 439 |
| Rich Hill | LOS | 0.288 | 0.275 | -0.013 | 45.3% | 0.189 | 12.6% | 78.7% | 87.7 | 2.60% | 1.40% | 228 |
| Taijuan Walker | ARI | 0.320 | 0.267 | -0.053 | 44.1% | 0.181 | 12.4% | 86.0% | 90 | 8.40% | 5.20% | 358 |
| Tanner Roark | WAS | 0.288 | 0.269 | -0.019 | 48.7% | 0.201 | 6.1% | 87.1% | 87.8 | 6.00% | 3.60% | 518 |
| Trevor Cahill | SDG | 0.296 | 0.246 | -0.05 | 56.6% | 0.217 | 2.6% | 84.4% | 89.4 | 5.70% | 2.80% | 140 |
| Tyler Chatwood | COL | 0.317 | 0.286 | -0.031 | 57.2% | 0.172 | 5.8% | 88.7% | 87.9 | 4.40% | 2.70% | 409 |
| Wily Peralta | MIL | 0.300 | 0.336 | 0.036 | 50.0% | 0.225 | 4.5% | 90.9% | 89.6 | 7.70% | 5.10% | 362 |
These numbers show why there’s reason for optimism on guys like Michael Pineda and James Paxton, while the opposite may be true for Dan Straily. Taijuan Walker is the most interesting one here, but there may be other reasons for optimism even if we expect a BABIP decline.
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
Jacob deGrom (1t) is threw much like he did in 2015 this spring. He’s one of the best RHPs in the league when healthy and has a nice matchup at home against the Braves tonight. He is tied for the second highest cost and I’ve been flip-flopping between tiers on him quite a bit, but expectations are high either way.
Value Tier Two
Michael Pineda (3) has elite upside, but frustrates owners by blowing up too often. That really didn’t happen as much after May last season though. He gets an environmental upgrade tonight against a team that swings and misses, costing not much more than $8K.
Chris Sale (1t) is the most expensive pitcher on the board and the only one who costs more than $10K on both sites (though he’s joined by two others on DraftKings). Expectations should be for something similar to last year with perhaps even a slight increase in strikeout rate.
Rich Hill (4) is tied with deGrom for the second highest price on the board. The concern, and really the only one, is that the Dodgers pull the plug early here, but he’s one of few pitchers who could make a $10K price tag work with an expectation of six innings or less, especially in this matchup. If you expect him to go deeper, he may be a top tier guy.
Value Tier Three
Charlie Morton is a speculative add at a low cost. With newfound velocity and potentially a new method of attack, he attempts to sustain massive gains in his strikeout rate before succumbing to injury after just four starts last year.
James Paxton carries some risk in what could be a difficult spot in Houston for a LHP, but also showed tremendous upside last season. Some smart baseball writers are fairly high on him this season and for a cost of $7.7K or less, he’s certainly worth at least considering, especially on two pitcher sites.
Jharel Cotton is priced a bit aggressively on DraftKings ($7.8K) where I’d likely drop him a tier, but costs less than $7K on FanDuel with above average strikeout upside, though that upside may be a bit less against the Angels.
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.
Cole Hamels is a flawed pitcher, but he still has upside and at around $9K on either site, it might be worth exploring. Just beware that he often blew up with at least four ERs in seven of 32 starts last year and exactly three six more times, striking out eight or more only eight times.
Jerad Eickhoff does have some HR concerns and is not extremely high upside, but at least than $8K is probably fine in your SP2 spot in Cincinnati.
Tyler Chatwood is a ground ball machine, who excelled at inducing bad contact last year. He doesn’t have much upside in his strikeout rate, which more often than not makes him unusable. The hope is that the Brewers give him some semblance of upside in that department today. He’s off the board for me on FanDuel ($7.6K), but may be fine in your SP2 spot for just $5.9K on DraftKings.
Wily Peralta from the last 11 starts last season might be an interesting speculation at a very low price early in the season. He was throwing harder and missing some bats after returning in August last year.
You can find me on twitter @FreelanceBBall for any questions, comments, or insults.
NOTE: Button for pitcher salary chart above opens in popup window