Some Preseason Thoughts: American League

An in-depth look at the favorites to win each division and each wildcard.

So here we are, in the midst of opening week. I’m going to outline the favorites for this season, based on who was truly good last year and who made the best win-now moves this past offseason.

AL East

Favorite: Boston Red Sox

Mookie Betts accumulated 7.8 WAR and Xander Bogaerts had a career-best walk rate and ISO in their age-23 seasons. Andrew Benintendi is healthy and geared up for his first full season in the majors. Dustin Pedroia and Hanley Ramirez enjoyed bounce-back campaigns, the former garnering 5.2 WAR and playing 160 games, the latter with a 127 wRC+. Jackie Bradley Jr. proved his 2015 success was no fluke. The acquisition of Chris Sale offsets the injuries to David Price and Drew Pomeranz. They have plenty of rotation depth: Rick Porcello is a solid presence (although, some regression is to be expected) and both Eduardo Rodriquez and Steven Wright offer some sneaky upside.

Furthermore, it’s worth noting that last year, although they won 93 games, Baseball Prospectus said that they should have won 103 games (more than anyone else in the AL) based on runs scored and runs allowed, amongst other underlying statistics, and adjusted for strength of schedule. FanGraphs projects them to tie with the Astros for most wins in 2017.

AL Central

Favorite: Cleveland Indians

Carrying over from last year is a solid young core of Francisco Lindor, Tyler Naquin, and Jose Ramirez, backed by consistent veterans Carlos Santana and Jason Kipnis. The signing of Edwin Encarnacion and the return Michael Brantley further boosts this offense. As for the pitching, the big three of Carlos Carrasco, Corey Kluber, and Danny Salazar are returning, fully healthy. They are backed by a couple of solid arms in Trevor Bauer (whose excellent stuff still offers upside in his age-26 season) and Josh Tomlin. Furthermore, there are two solid prospects with major league experience: Mike Clevinger struck out more than a batter per inning in Triple-A last year, and Ryan Merritt was a postseason hero. Not to mention, a very strong bullpen composed of Andrew Miller, Cody Allen, Bryan Shaw, and the newly signed Boone Logan.

Andrew Miller’s ranks amongst the 133 qualified relievers last year:

1st 2nd 1st 2nd 3rd 1st
WAR O-Swing% Z-Swing%
2nd 2nd 1st (Lowest)

AL West

Favorite: Houston Astros

Despite a disappointing season last year, the Astros have an improving young core. Carlos Correa just put up 4.9 WAR in his first full season, which he seemed to be playing injured throughout. And he’s only 22! They’re getting a full season of Alex Bregman, who put up a 112 wRC+ in his first big league action. Jose Altuve, still only 26, had a career year, posting bests in walk rate, ISO, WAR, wRC+, OBP, Slugging, and more. George Springer, still only 27, played a full season for the first time, putting up a 124 wRC+ for the third straight season and garnering 4.5 WAR. The Astros don’t only have youngsters, though; they also improved their catching with the acquisition of veteran Brian McCann, and now have a respectable tandem of McCann and Evan Gattis. They’re set for their first full season of Yulieski Gurriel, the 32-year-old Cuban. They also signed three more solid veterans this offseason: Nori Aoki (career .353 OBP), Carlos Beltran (124 wRC+ last year), and Josh Reddick (career wRC+ of  105 and positive defensive marks).

On the pitching side of things, after struggling with shoulder issues for the last couple of years, Lance McCullers (30.1% K-rate last year) is healthy to begin the year. While Dallas Keuchel disappointed last year, his underlying metrics (3.87 FIP, 3.53 xFIP, 3.77 SIERA) suggest that he suffered from some bad luck. Joe Musgrove provided 62 solid innings in his MLB debut last year, and still has room to grow at age 24. Charlie Morton, the oft-injured veteran, showed much improved velocity last year in a small-sample and topped out at 97 this spring (he sat 91-92 in previous years) with his sinker, so he offers some sneaky upside. Collin McHugh is starting the season on the DL, but he has garnered at least 3 WAR in each of the last three seasons. The ‘Stros have some depth beyond those five: Mike Fiers can be an innings eater with the potential to showcase the swing-and-miss stuff that he showed before last year, Brad Peacock struck out a batter per inning in 117 Triple-A innings last year, and Chris Devenski, bullpen ace, started five games last year, putting up a 2.16 ERA in 108.1 innings (mostly in relief).

The bullpen is loaded. Luke Gregerson led the MLB in swinging strike rate last year, Ken Giles has a career 34% K-rate and an only 8.2% walk-rate, Will Harris and Tony Sipp are two lefties who have struck out more than a batter per inning in their careers, James Hoyt had a 2.96 SIERA last year and Michael Feliz had a 2.45. Not to mention, Chris Devenski.

Beyond the obvious depth on the MLB team, the Astros have a solid farm system. They have 9 top-100 prospects, according to KATOH, the stat-based prospect ranking system on FanGraphs. Among them are familiar names such as outfielder Kyle Tucker (119 wRC+ in A-ball last year, 188 in 69 PAs in High-A), David Paulino (1.83 ERA in 64 Double-A innings last year), Francis Martes (3.33 ERA, 2.73 FIP in 125.1 Double-A innings last year), and A.J. Reed (142 wRC+ in 296 Triple-A PAs last year).


Favorite: Toronto Blue Jays

While they lost Edwin Encarnacion, much firepower remains. Josh Donaldson is still Josh Donaldson. Kevin Pillar is one of the best defenders in baseball, accumulating the most defensive runs saved above average out of every outfielder the last two years. I’m expecting a bounce-back from Jose Bautista, who played through injury last season. Devon Travis, who has 4.8 WAR in only 163 career games, is fully healthy to start the season. Russell Martin provides a steady presence behind the plate. Even though his offense has declined over the last two years, Troy Tulowitzki still provides upside at shortstop and defends well. The signings of Steve Pearce (136 wRC+ last year) and Kendrys Morales (whose homerun power should play up  at Rogers Centre) should help offset the loss of Encarnacion.

Their stellar rotation from last year remains intact. Although J.A. Happ, Marco Estrada, and Aaron Sanchez are due for some regression, Marcus Stroman was unlucky last year (his ERA-FIP was the 10th highest amongst qualified pitchers last season). It’s also worth noting that Estrada, with a superb rising fastball, is known to defy his peripherals by inducing popups at a high rate. Sanchez is still young (24), so he can improve his skills before regression catches him. Either way, he led the AL in ERA in his second year in the majors and features an excellent sinker. Francisco Liriano provides some sneaky strikeout upside at the back-end of the rotation.

The bullpen is solid too, headed by Roberto Osuna, Joe Biagini (who I profiled last year), and Jason Grilli (who rebounded nicely last year).

Second Wildcard

Favorite: Seattle Mariners

 The Mariners have some upside (Mike Zunino, Mitch Haniger, and Dan Vogelbach are all former top prospects still under 27 years old), but their aging stars (Nelson Cruz is 36, Hisashi Iwakuma is 35, and Robinson Cano is 34) will have to remain effective in order for them to catch the Blue Jays. The ineffectiveness of Felix Hernandez and the injury to Drew Smyly mean the M’s will have to lean heavily on the injury-prone but high-upside James Paxton for innings.


Favorite: Houston Astros

With unmatched depth and a stat-savvy UPenn and Northwestern educated GM in Jeff Lunhow, I pick the ‘Stros over the Red Sox (whose depth is rapidly disappearing under old-school president of baseball operations Dave Dumbrowski) and the defending pennant winners (Carlos Carrasco and Danny Salazar are too injury-prone for my liking, and their depth pales in comparison to the Astros).

About those Yankees:

The young trio of Greg Bird, Gary Sanchez, and Aaron Judge will have to really wow in order to make them a contender :(.

Data from Baseball Prospectus and FanGraphs. Picture from

Thanks for reading!


Starlin has Really not Been Sterling

A common misconception amongst casual baseball fans is that Starlin Castro is a solid player. I’m here to debunk that myth.

Twenty-one homers, a career-high by seven. A .270 batting average. Only 118 strikeouts in 610 PAs. So, Starlin Castro is back on the map, right?

Not so fast. Castro did not just experience a sweet power-surge, as some may think. He greatly benefitted from an inflated HR/FB rate. Last year, his 15% rate was way higher than his previous career high (10.1%). Some may dismiss this stat and say that the move to Yankee Stadium helped him out, but in fact, the park factors on FanGraphs list Wrigley (106) as an easier venue for righties to hit homers than Yankee Stadium (105). As was often discussed amongst the Sabermetric community, last year the number of homers skyrocketed all around the MLB (possibly due to the balls being “juiced”), so take that with Castro’s inflated HR/FB rate and the most PAs he saw in a year since 2013, and we have a career-high in homers, even though Castro posted a fly ball rate lower than his career average and a popup rate higher than his career average. All of these homers helped lead to a career-high ISO, at .163. Because I don’t think the home run increase is sustainable, I don’t think the ISO increase is, either. He only hit 29 doubles, tying him for 51st out of the 88 players with at least 600 PAs last year. He also only hit one triple. Further undermining his ISO explosion, the league average ISO also ran up to its highest in ten years, fifth highest all-time, at .162. This was only the second time in Castro’s career that he had bested the league average ISO in a season (and he barely did so in 2016).


Accompanying this power surge was an erosion of plate discipline. Castro posted the second-worst walk rate of his career, at 3.9%. This was the third-lowest walk rate amongst the 88 hitters with at least 600 PAs last year. To make matters worse, his strikeout rate (19.3%) was the worst of his career. His swinging strike rate ballooned to 11.3%, way higher than his previous career-high (9%), and firmly below average. His chase rate was its worst since 2012, ranking 11th highest in the group of 88. If there is one good thing here, he also swung at pitches in the zone at the highest rate in his career. However, this could just be a function of Castro seeing a career-high number of strikes and him choosing to have a more aggressive approach (career-high overall swing rate as well, ranking 12th in the group of 88). Yet, he still made contact on pitches in the zone at the lowest rate in his career. Either way, Castro’s .300 OBP last year undermined his improvements in the power department, and he ended up with a below-average 94 wRC+. That OBP was the seventh-lowest amongst the 88 hitters with at least 600 PAs.

Noted for his speed as a prospect, Castro never actually posted a positive BsR (base-running runs above average) value in a season. His base stealing days appear to be over, as he only attempted to steal four times last year. Although he wasn’t caught once, he still posted a -1.6 BsR.

Did he at least hit the ball hard? Well, his Hard% was the second highest of his career, but it was still just below league average. His Soft% was a couple percentage points below league average, at least. His line drive rate was the second highest of his career (right around league average). But did his exit velocity improve? Of the 61 hitters with at least 400 batted ball events last year, Castro had the 43rd highest average exit velocity, at 89 MPH. The prior year, he ranked 44/55 amongst the hitters with at least 400 batted ball events, with an 86.5 average exit velocity. While Castro experienced quite a jump there, the average of the first group was 89.9 and the average of the second group was 88.9 MPH, so the entire league experienced a jump, and Castro ended up below average both years.

Starlin Castro is definitely a below average hitter. There are certainly some good things about him, but when he has a down year on defense, like last season, his offense isn’t enough to bank on–he only accumulated 1.1 fWAR in 151 games. This was the 11th worst amongst the 88 hitters with at least 600 PAs, and the worst amongst the second basemen in that group. Despite an uptick in homers, I don’t see enough of a skills improvement for Castro to maintain a 20-per season pace. I would expect something more along the lines of 15-per season, with his increased aggressiveness giving him more shots to lift the ball out of the park. This aggressiveness, however, can be his downfall: he doesn’t walk often and he doesn’t hit the ball hard, so some bad luck on balls in play could lead to a horrific OBP.

Data from FanGraphs and Baseball Savant. Graph made courtesy of Picture: USA TODAY NETWORK/USA TODAY NETWORK/SIPA USA–via

Thanks for reading!

Caught on Cotton

A few weeks ago, I wrote about a potential impact rookie hitter for 2017, Dan Vogelbach. Today I’ll evaluate a potential impact rookie pitcher, Jharel Cotton.

Just before the trade deadline this past summer, the Dodgers and Athletics struck a blockbuster deal that sent ace Rich Hill and capable right fielder Josh Reddick to the Dodgers and pitching prospects Grant Holmes, Frankie Montas, and Jharel Cotton to the A’s. The oft-overlooked Cotton was largely considered the third-best prospect the A’s received; after all, how good could a pitcher who put up a 4.90 ERA in 97.1 frames of Triple-A ball be?

Well, I’ll answer that question for you; pretty damn good. As I often write, ERA isn’t a tell-all statistic, and Cotton had some pretty good indicators that suggested he was more than just a run-of-the-mill pitcher in those 97.1 frames. Although the 1.57 homers per nine were troubling, it is encouraging that in years prior in the minors, he only allowed a rate higher than 1 homer per nine at one level. Also, that rate normalized after the trade; in 38.1 frames for the A’s Triple-A affiliate, he allowed 0.70 homers per nine, sporting a 2.82 ERA. In the majors, the rate wasn’t great, but it was still palatable at 1.23 homers per nine.

What I like most about Cotton, though, is his command and his swing-and-miss stuff. At every stop in the minors in which he threw at least 20 innings, he never walked more than 3.02 per nine. Even more exciting, in those 97.1 innings for the Dodgers Triple-A affiliate, he only allowed 2.96 walks per nine and struck out 11 per nine. That’s right. I said 11. So, he probably suffered from some bad luck there; his strand rate was just barely over 60% and his home run to fly-ball ratio was probably exorbitant. In his short stint in the majors, he only struck out 7.o6 per nine, but with only a 1.23 BB/9 rate and a 12.5% swinging strike rate, which would have been a top ten rate had he qualified.

How did he amass such a high swinging strike rate? Is it sustainable? Let’s take a look at his repertoire.

In order of usage, he throws a four-seamer (34%), a changeup (28.3%), a cutter/slider (16.4%), a two-seamer (13.5%), and a curve (7.8%). His four-seamer averages a solid 92.3, right around the average for a right-handed starter. What really makes this pitch special, though, is its rise. It would have ranked within the top 15, had he qualified. This helped Cotton to a crazy 24.4% popup rate, which was better than every single pitcher who threw 30 or more innings, except for Tyler Clippard. This would explain the miniscule BABIP that Cotton allowed (.198). While I don’t think that figure is sustainable, the rise on the fastball looks good for suppressing BABIP going forward. Let’s check the Baseball Prospectus PitchFX leaderboards for the fastball, too. Of the 228 starters who threw at least 100 four-seamers last year, Cotton’s ranked 113th in average velocity, 42nd in rise, and most impressive, second in terms of popups per balls in play.

Onto the changeup. This one’s a beauty.


A 40% O-Swing rate, and he only throws it in the zone 35.5% of the time! A 17.7% swinging strike rate. A 54.8% swing rate, almost as high as his fastball (55.7%). Also, it would have had top-15 drop, had he qualified. A 4.4 pVAL in only 125 pitches. If we look at the PitchFX leaderboards on Baseball Prospectus instead of FanGraphs, the prognosis is similarly positive: of the 153 starters who threw at least 100 changeups last year, Cotton’s had the 55th highest swing rate, the 48th best whiffs per swing, the 38th best drop, the 21st highest fouls per swing, and best of all, the second highest popups per balls in play rate.

The cutter/slider:

A high O-Swing rate (37.9%) and a low Z-Swing rate (62.8%) point to signs of success for this pitch and possible sustenance of its exorbitant swinging strike rate (22.2%). Here are the relevant stats from Baseball Prospectus as well: of the 89 starters who threw at least 50 cutters last year, Cotton’s had the 28th highest average velocity, the 27th highest swing rate, the third best whiffs per swing, the second best GB/FB ratio, and the best popup per balls in play ratio. Although the pitch also has the lowest fouls per swing rate in that group, the high whiff rate and excellent contact management negate any ill effects from that.

Cotton also throws a curve:

He only threw it 34 times in the majors last year, but it looks like it has good movement, and it generated a 17.7% swinging strike rate. It has above average drop and horizontal movement.

Lastly, Cotton throws a two-seamer, his most ineffective pitch, but it is good to know that he has another fastball he can turn to when he’s in need of a ground ball.

With a full starter’s repertoire, excellent contact quality management, and a robust swinging strike rate that has good foundations, look for Cotton to do big things this season in his first full year in the majors.

Data from FanGraphs and Baseball Prospectus. Video from Pitcherlist. Picture courtesy of USA Today Sports Images, via

Thanks for reading!




Dan the Man

A promising rookie took a big step forward last year.

2016 was an excellent year for rookies. We saw 20 homers in only 229 PAs from Gary Sanchez, 20 in only 330 PAs from Ryan Schimpf, and 27 in only 415 PAs from Trevor Story. Trea Turner managed 33 steals, 13 homers, and a .388 BABIP. Tyler Naquin ran a .411 BABIP.   Not to mention, Corey Seager racked up 7.5 WAR. You get the idea. This year, Dan Vogelbach looks poised to burst onto the scene.

Vogelbach was dealt just before the trade deadline from the Cubs to the Mariners in a four-player deal that was basically just Mike Montgomery for Vogelbach, with a throw-in on each side. It was expected that the Cubs would trade Vogelbach, a notoriously bad fielder who can only play first base at best (where Anthony Rizzo is slotted for the near future), to an American League team who could deploy him at first base or DH if needed. However, there is little doubt about his offensive ability: at every stop in the minors where he logged at least 100 PAs, he put up at least a 126 wRC+ with at least a .150 ISO, 10% walk rate, and .350 OBP. Not to mention, he struck out in less than 20% of his PAs at every stop but one (where he struck out in 20.2%). Check out some of his important stats from last year, which was another solid year:

Team PA HR BB% K%
Mariners (AAA) 198 7 21.20% 17.20%
Cubs (AAA) 365 16 15.10% 18.40%
0.182 0.263 0.240 0.404 0.422
0.230 0.362 0.318 0.425 0.548
0.375 127
0.423 158

While his success with the Cubs’ Triple-A affiliate was partially BABIP driven, it was a larger sample, and he still maintained a solid ISO (.182) with the Mariners’ affiliate. Not to mention, he walked a ton, even more than he struck out after the trade. Either way, at each stop, he posted an OBP above .400, incredible plate discipline for a 23 year-old (now he’s entering his age-24 season). Walk percentage is an excellent predictor for future results, as it usually has an r-squared value in the .70’s from year to year. Thus, it isn’t surprising that Vogelbach received the most positive projection from Steamer this year for all incoming rookie hitters (in terms of wRC+).

Data from FanGraphs, photo by Gregg Forwerck/Getty Images, via Thanks for reading!

Cardinals, Carlos, Contact, and Command

After an incredible run culminating in a 100-win season in 2015, the Cardinals missed the playoffs in 2016 for the first time since 2010. What’s up with them? I attempt to answer that question by first looking at their most important pitcher.

The years 2011-2015 saw some incredible Cardinals teams. They won a title and made the playoffs every year during that stretch. In fact, the Cardinals made the playoffs 12 of the last 16 seasons before last year. They only missed the playoffs in back-to-back years once during that stretch. But last year, they won 14 fewer games than the year before, and missed the playoffs for the first time since 2010. Will they miss the playoffs again this year? What went wrong for them last year? Let’s take a look at one of their most important pieces, which could answer some of those questions.

Carlos Martinez was the ace of the Cardinals’ staff last year, pitching to a 3.04 ERA in 195.1 innings. But, despite the solid ERA, it appears Martinez took a significant step backwards last year. Below, I’ve included some his stats from his first four years in the majors, as well as a projection for this season for most stats (from Steamer):

Season Soft% Med% Hard%
2013 13.60% 64.80% 21.60%
2014 22.90% 50.40% 26.70%
2015 21.20% 51.20% 27.60%
2016 19.10% 51.30% 29.60%
Total 20.20% 51.90% 27.80%
2013 5.08 3.08 3.83 3.40 0.3
2014 4.03 3.18 3.54 3.45 1.3
2015 3.01 3.21 3.28 3.44 3.4
2016 3.04 3.61 3.81 3.97 3.3
2017 3.52 3.53 3.72 N/A 3.7
Total 3.32 3.36 3.57 3.65 8.4
Season G GS IP K/9 BB/9
2013 21 1 28.1 7.62 2.86
2014 57 7 89.1 8.46 3.63
2015 31 29 179.2 9.22 3.16
2016 31 31 195.1 8.02 3.23
2017 32 32 199 8.56 3.23
Total 140 68 492.2 8.51 3.25
2013 0.345 64.90% 52.30% 4.00%
2014 0.333 71.50% 51.20% 5.90%
2015 0.318 78.80% 54.50% 10.60%
2016 0.286 79.50% 56.40% 10.60%
2017 0.294 72.60% 52.90%  N/A
Total 0.310 76.70% 54.50% 9.20%

Let’s start with the good from these tables. This year, Martinez posted a career high in innings, games started, and ground ball rate. He’s also only 25, so he still has room to grow.

Now the bad: much of Martinez’s success last season was luck-driven. He posted a career low BABIP and a career high strand rate. The low BABIP doesn’t seem sustainable judging by this, because he had a career high hard-hit rate and he gets so many ground balls (which go for hits more often than fly balls do). Even though he had a weak exit velocity against him last year, the fact that this year it was slightly higher than 2015 and that he allowed more grounders should have meant a higher BABIP, not a lower one. For these reasons, FIP, xFIP, and SIERA (3.61, 3.81, and 3.97) were less fond of his work last year.

But, none of that is as troubling as this: Martinez’s strikeouts took a dive last year. After improving in that area in 2014 and 2015 (the latter year saw him post an awesome 9.22 K’s per nine in his first full season as a starter), his strikeouts bottomed out in 2016, falling more than one strikeout per nine. And the underlying plate discipline stats support the fact that Martinez wasn’t as filthy last year. Take a look:

Season O-Swing% Z-Swing% Swing% O-Contact% Z-Contact% Contact% Zone% SwStr%
2013 36.30% 65.60% 51.50% 65.90% 91.90% 83.10% 51.90% 8.60%
2014 36.10% 63.20% 48.80% 54.40% 84.90% 73.00% 47.10% 13.10%
2015 32.80% 62.50% 47.30% 57.90% 87.90% 77.20% 48.70% 10.50%
2016 29.20% 62.70% 46.70% 60.90% 87.30% 79.50% 52.40% 9.40%
Total 32.30% 62.90% 47.60% 58.70% 87.40% 77.70% 50.10% 10.40%

He posted an O-Swing percentage that was easily a career-low (leading to a career-low swing rate), a contact rate that was his highest since 2013, and a swinging strike rate that was his lowest since 2013. What was behind this?

Well, Martinez especially struggled against lefties last season. He struck only only 7.49 per nine and walked 4.28. It would appear that the reason for this is because his command slipped significantly. This is especially evident when his heatmap versus lefties in 2015 is placed next to that of 2016:

Screen Shot 2017-01-26 at 7.16.53 PM.png

Screen Shot 2017-01-26 at 7.17.33 PM.png

Martinez was working that lower outside corner much more effectively in 2015, a location that is excellent to use for a sinker-balling right-hander against lefties. However, in 2016, many of those pitches moved higher up and more inside towards the middle of the plate. So, I think the main culprit behind his decreased ability to garner strikeouts is diminished command. Maybe this is due to an injury? Martinez’s 2015 season was ended prematurely by a shoulder strain. Maybe the injury lingered into 2016?

He was lifted early from a start in May due to “fatigue”, and he did get better as the season went on, so maybe an injury was the case. In his last 11 starts, he managed to strike out 9.26 per nine on the heels of a solid 10.4% swinging strike rate. Still, this is an arbitrary starting point.

One other interesting tidbit about Martinez to consider is the fact that he has exceptional movement on all of his pitches–maybe the increased movement is making Martinez struggle to control his pitches. Consider this table:

Season Pitch xMov zMov
2013 FA -6.5 6.9
2013 FT -9.7 2.2
2013 CU 6 -3
2013 CH -7.6 4.6
2014 FA -5.1 7.5
2014 CU 3.9 0.7
2014 FT -9.1 2.8
2014 CH -4.4 4.5
2015 FA -5.4 7.7
2015 CU 5.2 -0.2
2015 FT -9.3 3.8
2015 CH -9.7 2.7
2016 FT -9.6 3.4
2016 FA -5.9 7.3
2016 CU 5.3 -1
2016 CH -9.3 1.1
Total FA -5.6 7.5
Total FT -9.4 3.4
Total CU 5 -0.5
Total CH -9.2 1.9

His four-seamer and two-seamer are both tailing away from righties and sinking more than ever. He clearly started throwing a different changeup in 2015 that moves much the same way as his fastballs, but is on average 8-10 MPH slower (excellent velocity separation with similar movement to his fastballs–that spells trouble for hitters). He also has another pitch that moves in the opposite direction, a slurve with nice bite. It’s worth noting that he’s upped the usage of his changeup as the pitch has improved:

Season FA% FT% CU% CH%
2013 51.10% 28.50% 16.40% 4.00%
2014 52.70% 18.10% 26.20% 3.00%
2015 33.50% 25.40% 25.80% 15.20%
2016 27.20% 30.10% 23.50% 19.20%
Total 35.50% 26.20% 24.40% 13.90%

He’s also throwing his four-seamer far less often, but that’s just because he has had to rely increasingly on his secondary pitches (which instigated the development of the changeup) as he has transitioned from a relief-role to being a full-time starter. Here’s some footage of Car-Mar’s awesome secondary stuff:

Changeup fooling Joey Votto (gif from FanGraphs):


Slurve from the 2013 World Series fooling Pedroia (gif from SBNation):


Here’s another changeup (I couldn’t resist) that fools Scooter Gennett (from



Compare the change to this awesome fastball (gif from PitcherList):


While the added movement may make his pitches harder to control, it also makes them harder to square up–so maybe Martinez can sustain a low BABIP after all. In conclusion, although the strikeouts declined last season, velocity and movement are still strong for Martinez; his skills certainly haven’t eroded. He already has an easy time keeping the ball on the ground (a skill that is becoming increasingly rare in today’s game) and he has two solid secondary pitches at age 25–he has a full skill-set, but he still has room to grow, since he’s so young.

The First Blockbuster Trade of the Offseason

On Wednesday night, the Diamondbacks announced that they shipped shortstop/second basemen Jean Segura, outfielder Mitch Haniger, and lefty Zac Curtis to the Mariners in exchange for righty Taijuan Walker and shortstop Ketel Marte.

In 2014, former player and manager Tony La Russa was hired to be chief baseball officer for the Arizona Diamondbacks, and former pitcher Dave Stewart was hired to be their GM. Stewart said the following when asked about analytics: “We’re not going to be an organization that’s going to [run on] 70 percent metrics. That’s not going to happen.” Oh boy. You just knew we were in for one heckuva ride. And Stewart did not disappoint. Last offseason, before the 2016 season, he made one of the worst trades in recent memory. He let go of Dansby Swanson, the first pick of the draft in 2015. Swanson has already reached the majors for his new team, the Braves: a shortstop with solid defensive marks, he put up 107 wRC+ in 145 plate appearances this past season as a 22-year-old. What made the D-Backs give up Swanson so readily? Well, they wanted Shelby Miller really badly. Yes, he was coming off of a season in which he pitched to a 3.02 ERA in 205 innings as a 25-year-old, but there were some obvious signs of trouble. His control had always been subpar (he walked 3.2 per nine in 2015), and he only struck out 7.5 guys per nine innings, below league average. Worse, his swinging strike rate was only 9.2%. SIERA and xFIP both believed his true talent from that year should have yielded an ERA above 4. And so, Miller was a total bust for the D-Backs in 2016. In 101 innings, he pitched to a 6.15 ERA. He was demoted to the minors for a time, where he performed better, but still… a 6.15 ERA?!?!

You might be thinking: Swanson for Miller? I guess that’s not SO bad. But wait: the D-Backs wanted Miller so badly that they threw in pitching prospect Aaron Blair and stellar outfielder Ender Inciarte. In his first two seasons in the league, when he was only 24 and 25, Inciarte garnered 6 WAR, behind some awesome defense. He would continue to flash the leather in his first season with the Braves, putting up a career-high 3.6 WAR. Blair struggled in his MLB debut, but he was just icing on the cake, and he did show flashes of potential, striking out 8.92 per nine in 71.2 innings of Triple-A ball as a starter in 2016.

So that’s how La Russa’s front office would be run. And the Diamondbacks struggled mightily last year behind him, despite an offseason spending spree. Changes were made after last season: they fired manager Chip Hale and GM Dave Stewart. However, La Russa remains. On the other side of this deal, the Mariners have been using analytics more extensively. They fired their GM Jack Zduriencik in the summer of 2015. Zduriencik was never savvy with analytics. According to former Mariners’ analyst Tony Blengino: “Jack never has understood one iota about statistical analysis. To this day, he evaluates hitters by homers, RBI and batting average and pitchers by wins and ERA. Statistical analysis was foreign to him.” However, the M’s hired former Angels’ GM Jerry Dipoto to succeed Zduriencik, and Dipoto had openly vied for more statistical analysis in the Halos’ front office. So, when I saw the headline “Diamondbacks aquire Taijuan Walker, Ketel Marte”, I assumed the worst, that the savvy Mariners had just ripped off the D-Backs. Did they? Let’s take a look at the Diamondbacks’ haul first.

Still only 24, Walker has flashed tremendous upside. His fastball sits 94, and he has a wide array of secondary offerings to back it up. He appeared to be poised for a breakout through his first nine starts last season, putting up a 2.70 ERA and a strong 8.46 K/9 with only 1.62 BB/9 (all of these marks would have been career bests). However, the rest of his season was derailed by foot and ankle injuries. He spent some time on the DL, but didn’t look quite the same upon returning, putting up a 5.12 ERA behind diminished skills in his last 16 starts. He underwent surgery last month to correct the problem, so there’s hope that he can regain his pre-injury poise. Plus, he still has at least 3 years of team control remaining.

After putting up 1.7 WAR in 57 games as a rookie in 2015, Marte seemed ready to be the Mariners’ shortstop of the future. However, he took a big step back last year, putting up a meager 66 wRC+ in 466 PAs while accruing negative defensive value. He walked in only 3.9% of his PAs, less than half league average, while still striking out at an 18% clip. He showed no power, with a 0.064 ISO. Despite running a .313 BABIP, his soft-contact rate was the 8th highest out of the 175 hitters with at least 450 PAs last year. His hard-contact rate was 5th lowest in that group. His average exit velocity tied for 439th worst out of the 513 hitters with at least 30 balls in play last season. On the bright side, he played markedly better in his first 167 PAs of the season, which came before he went on the DL with a thumb injury. Maybe that thumb injury sapped his power–he had been running a .333 BABIP, .103 ISO, and a 87 wRC+ before the injury, all solid numbers for a shortstop. Plus, he’s still only 23 and has at least 4 years of team control remaining.

So who did the Mariners get in return?

Their package is headlined by shortstop/second basemen Jean Segura, fresh off of a career year. Other than a solid first full season in 2013, Segura had failed to post a wRC+ above 70 before last year. But 2016 was different: always a capable defender, Segura also showcased some pop, running a .353 BABIP, .181 ISO, and a 126 wRC+, leading to a 5 WAR season. When the D-Backs acquired him after the 2015 season, it seemed like another questionable move, but the buy-low paid off in a big way. The 26-year-old has two more years of team control remaining.

The next player the Mariners acquired was Haniger, who made his MLB debut as a 25-year-old last year, putting up an 81 wRC+ with solid defense in 123 PAs. Before being called up, Haniger was enjoying a breakout in the high minors. In 236 Double-A PAs, Haniger ran a 156 wRC+. He looked even better at Triple-A: in 312 PAs, he ran a 185 wRC+. Although that was buoyed by 20 homers and a .370 BABIP, a .330 ISO at Triple-A is impressive regardless. It wasn’t like Haniger was a dud before this year, either: he was drafted 38th overall in 2012, and he went on to post a wRC+ above 100 at every stop in which he recorded at least 30 PAs. That includes an awesome 2015 showing at High-A ball, where he posted a 163 wRC+ in 226 PAs. He has at least 5 years of team control remaining.

Curtis was kind of a throw-in. He’s a 24-year-old left-handed reliever. He looked terrible in his MLB debut last year, tossing 13.1 innings of 6.75 ERA ball, with a staggering 10/13 K/BB ratio. However, he looked much better in Double-A and High-A last year, where he recorded a combined 52 strikeouts in only 20 innings. As a fastball-slider guy, he could be a solid lefty-specialist down the road.

One year ago, the Diamondbacks bought Shelby Miller high. Now, they’re the ones who are selling high. Although, Jean Segura did make some clear strides last year: he had a career high Hard%, career low Soft%, and a career low O-Swing%. His average exit velocity rose from 87.3 MPH in 2015 (average that year was 88.1 for hitters with at least 30 batted ball events) to 89.9 in 2016 (average was 88.7). Despite these developments, his Hard% of 29.7% was still lower than the league average of 31.4%. Even those who hit the hardest don’t consistently run .353 BABIPs (which is what Segura did last year). Plus, his BABIP was aided by the fact that he is an extreme ground-ball hitter–ground-balls go for hits more often than fly-balls do. Of the 146 qualified hitters last year, Segura had the 11th highest ground-ball percentage. Let’s compare Segura with another hard-ground-ball-hitter: Eric Hosmer. Hosmer ran only a .301 BABIP last year behind a 93.4 average exit velo (better than Segura’s) and he had the second highest ground-ball percentage (Segura had the 11th). It’s worth noting that Segura pulls the ball infrequently–his pull rate was the 8th lowest out of the 146 qualified hitters. This makes it harder for teams to shift on Segura, so it’s easier for him to get grounders through the infield. But at the same time, Hosmer had the 30th lowest pull rate, and he hits the ball harder and on the ground more often.

In addition, Segura’s power boost and high BABIP were probably aided by the arid environment of Arizona. According to park factors on FanGraphs, Chase Field (home of the D-Backs) was the third best hitters park in 2014 and 2015. This, coupled with his extreme ground-ball tendencies, makes Segura’s improvements in the power department look fluky. His power numbers should certainly come back down to earth in the pitcher-friendly Safeco Field–the sixth worst park for hitters in 2014 and 2015. Couple that with expected regression to the mean, and Segura’s ISO should be much closer to his career (.117) than what he managed last year (.181). When Segura’s power and BABIP regress, he won’t have much to fall back on offensively. His career walk rate of 4.6% is far below the league average of 8.2%, so it’s easy to see him struggle to reach base.

Curtis struck out 52 guys in 20 innings in the minors. Haniger had a breakout performance in his first taste of the high minors, and put up an average exit velocity of 93.1 in his MLB debut. In other words, they both showed promise, but they have yet to put it all together. On the surface, it looked like Segura put it all together last year, but there are some troubling signs if we look deeper. Walker and Marte, on the other hand, are coming off of unimpressive seasons, but have been successful in the past, and they are both recovering from injuries that have probably hindered their performance. Overall, I’m surprised: I think this is quietly a nice move for the D-Backs, selling high on Jean Segura and buying low on Walker and Marte. Even though the D-Backs have to give up a couple of exciting prospects in the process, they are both far from a sure-thing.

Data from FanGraphs and Baseball Savant. Picture: Hannah Foslien/Getty Images, via Seattle Times. Quotes are from ESPN:

Thanks for reading!





Contract Year Phenomenon: Myth Or Truth?

The Contract Year Phenomenon refers to the statistical inconsistency in which players perform at much higher level than they usually do during the final year of their contract, but return to original form once they sign their new (and usually larger) contract. Some studies have shown that performance during the final year of a contract can increase, on average, by 5%, while others have shown that the Contract Year Phenomenon is a complete myth (negligible increase or decrease in performance).

There are 3 leading theories for why the Contract Year Phenomenon may (or may not) exist, which we will analyze below:

The most commonly accepted theory, despite its lack of statistical merit, is that players simply play better because of the extra incentive. Quality performance in the final year of a contract usually has a direct correlation to receiving a larger contract, which some would argue causes players to “try harder”. Since players are “trying harder”, this supposedly would lead to better performance, thus explaining this statistical anomaly. While this theory makes sense, it has one gaping hole that makes me question the validity of this theory: why wouldn’t players always be trying their hardest? This theory is assuming that players are not always trying their hardest, which I don’t necessarily believe is true, undermining this potential theory.

Another popular theory, but is not even remotely as widely accepted as the first, is that players are simply less skilled after they sign their contract than they were before. One of the most popular times to sign contracts, for all sports, is in the 27-29 age range, which is when most players are finishing up their first real contract (excluding rookie contracts). Unfortunately, this signing happens at a very similar time to when most players exit their prime and begin their demise (usually happens around age 28). This odd occurrence would certainly explain why the Contract Year Phenomenon exists.

The final, and least likely, of the 3 theories is that the Contract Year Phenomenon exists purely because of luck. Considering that studies only found a 5% increase, while others found no increase at all, it appears that we shouldn’t rule out luck as a possibility.

Let’s explore the 2 types of contract year phenomenon players, as well as the 2 types of reverse contract year phenomenon players to see if it will help give us a better understanding of whether the contract year phenomenon actually exists.


Prototypical Contract Year Phenomenon Player:

The player performs significantly better than he usual does in the final year of his contract, leading to him receiving a huge contract. In the year following the signing of this contract, the player returns to his original, or even potentially worse.

DeMarco Murray, a talented, but volatile running back, is the figurative poster boy for the “contract year phenomenon” after his disaster in Philadelphia. Photo Credits: Getty Images

Prime Example: DeMarco Murray, RB (Cowboys, Eagles, Titans)

2014: 2,195 yards from scrimmage, 14 total touchdowns

2015: 1,024 yards from scrimmage, 7 total touchdowns

2016 (through 7 games): 825 yards from scrimmage, 7 total touchdowns

As discussed earlier, DeMarco Murray is the poster boy for the Contract Year Phenomenon, as he played spectacularly in the final year of his contract, but followed it up with a year that was downright terrible (he signed his contract at the end of the 2014 season). However, in 2016, he returned to his original form, which perfectly matches the mold for a prototypical Contract Year Phenomenon player.


Extreme Fallout Post-Contract:

The player performs significantly better than he usual does in the final year of his contract, leading to him receiving a huge contract (same as above). In the following years, the player’s performance drops substantially below his usual, instead of returning to original form.

Albert Pujols, an all-time great nearing 600 career HR’s, was one of many to fall victim to an extreme case of the “contract year phenomenon” after cashing in on a massive contract. Photo Credits: Pablo Martinez / AP Photo

Prime Example: Albert Pujols, 1B/DH (Cardinals, Angels)

2011: .299 BA, .366 OBP, 0.25 HR/9, 5.1 WAR

2012: .285 BA, .343 OBP, 0.19 HR/9, 4.6 WAR

2013: .258 BA, .330 OBP, 0.17 HR/9, 1.5 WAR

After signing one of the biggest contracts in sports history back in 2012 (10 years, $240 million guaranteed), the quality of Pujols’ play declined sharply, making him an example of an extreme fallout contract year phenomenon. While Pujols regressed, but not too significantly, in 2012, 2013 was a completely different story, as Pujols now reestablished himself as an average hitter, not a world-class one.


Sustained Contract Year Performance:

The player performs at a very high level in the final year of his contract leading to a big payday, but he is then able to sustain this level of performance in years following the signing of the contract.

Daniel Murphy, quite possibly the most clutch postseason performer in recent MLB history, is one of few athletes who have sustained their “contract year performance”. Photo Credits: Brad Mills – USA TODAY Sports

Prime Example: Daniel Murphy, 2B (Mets, Nationals)

2015 (including postseason): .285 BA, 21 HR, 84 RBI

2016 (including postseason): .349 BA, 25 HR, 110 RBI

After a postseason for the ages back in 2015, Murphy signed a huge contract this past year with the Nationals. Unlike most other players who are unable to sustain their stellar postseason performances, Matthew Dellavedova for example, Murphy sustained, and even increased his incredible quality of play, especially his power hitting, which is quite remarkable for a second baseman.


Reverse Contract Year Phenomenon Player:

The player performs at a consistent level in years leading up to and including contract year and signs a reasonable contract (for his production). However, after signing the contact, unlike the 3 others, his performance substantially increases from what it used to be.

Steph Curry, the first unanimously-voted MVP in the history of the NBA, is among the many athletes who have experienced a “reverse contract year phenomenon”. Photo Credits: Stephen Dunn / Getty Images

Prime Example: Steph Curry, PG (Warriors)

2010-11: 18.6 PPG, 2.0 3PM/game, 1.91 Assists/TO

2011-12: 14.7 PPG, 2.1 3PM/game, 2.12 Assists/TO  *26 games*

2012-13: 22.9 PPG, 3.5 3PM/game, 2.25 Assists/TO

2013-14: 24.0 PPG, 3.3 3PM/game, 2.27 Assists/TO

Curry was an above average guard for his first 3 years in the league, and signed a fairly large contract extension back in 2012, essentially making him the “face” of the franchise. However, it was what he did after his contract extension that has made him the best player in the world. Instead of regressing, Curry did simply the opposite; he became better. In nearly every important statistic, most notably points per game and 3 pointers made per game, Curry greatly improved, which has made him an elite player.


Now that we have evaluated the possible evidence that would suggest the Contract Year Phenomenon exists as well as the different types of Contract Year and Reverse Contract Year Phenomenon players, it has become much more apparent whether this phenomenon actually exists. And the evidence overwhelming suggests that the Contract Year Phenomenon is much more of a myth than truth. As discussed earlier, studies regarding this phenomenon have been wildly inconsistent, as no two studies have confirmed the same results even though they have looked at fairly similar data. So far, luck seems like the most likely culprit, not extra incentive. In addition, it appears no more likely for a player to experience a Contract Year Phenomenon that to experience the reverse, thus leading me to conclude that the Contract Year Phenomenon is a myth.


Data courtesy of ESPN, CBS Sports, FOX Sports, Sports Reference, and Football Outsiders. Thanks for reading!

Written by Jason Platkin

Cover Photo Credits: Mitchell Leff/Getty