The 2017 season marked a career best for many players. As the season commenced we saw records broken, position depth expanded, and some truly remarkable moments.

Let me tell you why Troy Tulowitzki’s “elite level” is most definitely a thing of the past.

The shortstop position, specifically, is arguably the deepest in all of baseball, with names like Corey Seager, Carlos Correa, and Francisco Lindor bolstering the young crop of incredible talent. Of course there are also the rising stars in Didi Gregorius, Xander Bogaerts, and Addison Russell. Yet the one name who seems to be disappearing more and more each season is Troy Tulowitzki.

Tulowitzki is one of baseball’s best players over the past decade, and for a while he was heralded as the best shortstop in the league. From the year 2007 to 2015, in a Rockies uniform, Tulo wRC+’ed less than 100 once. In his two full “seasons” with Toronto he’s already wRC+’ed a new career low, 78.

Whether it’s the “Coors effect” or not, there is no denying that Tulowitzki was one of baseball’s finest players, and one of the more exciting to watch whilst with the Rockies — Coors Field in itself has a 27% OPS change due to its atmosphere, which gives a huge advantage to hitters.

Evidently so; Tulo’s road splits compared to his home ones were unbalanced.

Tulowitzki’s Road vs. Home OPS splits from 2007-2015

• 2007
  • HOME- .960 OPS
  • AWAY- .719 OPS
• 2008
  • HOME- .704 OPS
  • AWAY- .758 OPS
• 2009
  • HOME- 1.000 OPS
  • AWAY- .859 OPS
• 2010
  • HOME- 1.034 OPS
  • AWAY- .863 OPS
• 2011
  • HOME- .948 OPS
  • AWAY- .881 OPS
• 2012 *played 50 total games
  • HOME- .793 OPS
  • AWAY- .908 OPS
• 2013
  • HOME- 1.008 OPS
  • AWAY- .848 OPS
• 2014
  • HOME- 1.246 OPS
  • AWAY- .811 OPS
• 2015 *half season w/ COL
  • HOME- .831 OPS
  • AWAY- .697 OPS

Despite the lopsided splits, he still posted great numbers each season. However, the huge gap between his OPS per season on the splits should’ve raised some eyebrows, no?

During his tenure with the Rockies, Tulowitzki earned four All-Star appearances, two Gold Gloves, and two Silver Slugger awards, putting together a rather staggering resumé.

He posted a combined WAR with Colorado of 35.5, and posted a 5.0 WAR or better six times, making him one of the most consistent players in the league. So where or when did it seem to change?

The one large setback in Tulo’s Colorado career, and his biggest issue now, is his health. In his 12-year career, he’s only played 131+ games twice. He’s had issues staying on the field, and for that reason should be called one of the worst contracts in recent MLB memory. His Toronto days are an ugly reflection of his once-great Colorado ones.

Tulo since joining Toronto:

• 987 PA over 238 games
• .727 OPS (over three seasons)
• 101 wRC+ (2015 half with COL), 103 wRC+ (2016), 78 wRC+ (2017)
•  3.3 WAR (total over three seasons)

It can be argued that Troy Tulowitzki is washed up. His lack of production and inability to stay healthy make him more of a burden than an advantage for Toronto.

Tulowitzki was traded (in the summer of 2015) for prospects Jeff Hoffman, Miguel Castro, and Jesus Tinoco, as well as Jose Reyes, yet he has not been anywhere near the player Toronto was expecting to have for a few years.

Needless to say, it looks like the Rockies made the smart move offloading their star player.

His contract with the Blue Jays is a huge blemish on their team, which is full of horrid contracts. He signed a 10-year, $158-million deal with the Rockies back in 2011, and made $20 million with the Blue Jays this season. He appeared in just 66 games.

This is how his salary pays out until the end of the 2021 season:

2018- $20 million

2019- $20 million

2020- $14 million

2021- $15 million option, $4 million buyout

For a player that was already questioned by many because he had the luxury of playing for the Colorado Rockies, earning the initial contract he was given was a great deal if he stayed in a Rockies uniform for his entire career. However, some things are not meant to be.

Tulowitzki’s player value during 2016 and 2017

• Batting: 1.8 (2016) / -.7 (2017)
• Base Running: -2.7 (2016) / -3.5 (2017)
• Fielding: 4.9 (2016) / -1.1 (2017)
• Positional: 5.5 (2016) / 2.9 (2017)
• Offense: -0.8 (2016) / -10.5 (2017)
• Replacement: 16.4 (2016) / 8.0 (2017)

For context, here are Carlos Correa’s past two seasons:

• Batting: 17.9 (2016) / 30.7 (2017)
• Base Running: 4.0 (2016) / 1.6 (2017)
• Fielding: -2.3 (2016) / -1.7 (2017)
• Positional: 7.0 (2016) / 4.8 (2017)
• Offense: 21.9 (2016) / 32.4 (2017)
• Replacement: 19.9 (2016) / 14.9 (2017)

There are clear indications that Tulo has lost a step. He didn’t even play a single game the entire second half of the season, after being placed on the 10-day DL with a hamstring issue. His health, bat speed, and glove work are all in question.

A key contributor to his demise is claimed to be the turf in Rogers Centre. Transitioning from the usual field in Colorado to a false grass in an indoor stadium midway through your age-31 season can be rather tough on the joints and muscles.

While Tulowitzki has had his moments in a Blue Jays uniform, there is no way that this was a move for the future, despite what general manager Alex Anthopoulos said following the trade back in 2015.

Anthopoulos on July 25th, 2o15: “I just think we got better, for the short and for the long term. Ideally, you don’t shop in the rental market; that doesn’t mean we’ll rule it out, we’re open to it, but our preference is always for guys who are under control and will be here for a while.” — “This is a long-term acquisition.”

Since acquiring Tulowitzki, the Blue Jays have been seemingly getting worse each season. While this may in no way be Tulo’s fault, the fact that his production has dipped drastically does indicate his lack of contribution.

• 2015 record: 93-69
• 2016 record: 89-73
• 2017 record: 76-86

The move “for the future” looks to be more of a “weight from the past” if anything. I find that Troy Tulowitzki was one of the best talents that baseball had seen, three or so years ago. Now he is holding his team back, and should be viewed as a washed-up player.

While Tulo’s power is still there — he posted hard-hit rates over 30% each season with Toronto — it is clear that he cannot perform anywhere near what he once was able to do. Whether you blame that on his injuries, the Coors effect, or whatever else it may be, there is a clear line that Tulo has passed into the downfall of his career.

Troy Tulowitzki’s value is diminishing yearly, and when it’s all said and done, the possibility of Toronto eventually just terminating his contract seems more and more likely. With each swing of the bat, and 0-for-4 performance, Tulo is just shooting himself in the foot. A once greatly valued and important player, he’s now a mediocre-tier shortstop, based on value. His age isn’t helping him — neither is the turf — and the fact that he is now seemingly slowing down in the field as well means the future is looking dimmer and dimmer for Tulo.

Although it can be said that it is “too early” to judge this trade, based on the lack of performance history for the players Colorado has received, it can be said that they offloaded the contract of Tulowitzki, and have seen better days because of it.

With his fantastic career behind him, Tulo most definitely will not be calling it quits. Because of his immense contract, and money he has pouring in, the long-tenured SS will likely be seeing more and more time off the field, and as a DH rather than out there every day.

At this point in his career, seeing as to how he seems to be frequently bouncing on and off the DL, Tulo’s value is diminishing each season. The fact that the Blue Jays still are set to owe him $58 million over the next three seasons, and how his “One Trade” clause has been used already by Colorado, does not sit well for them. While he sells tickets and jerseys, no one wants to come watch someone go 0-for-4 over the course of only playing 60 games. With the fall of Tulo comes the rise of the extremely talented pool of IF players that MLB has to offer.

We should be grateful for Tulo’s production over the past several years, but it is time for his once reserved place among MLB’s top shortstops to be dismissed.

Although this season for Giancarlo Stanton was one for the record books, this monumental display of power should not be enough to warrant a spot in the top 10 of baseball’s best position players.

While Stanton did have an impressive season to say the least, and with an NL MVP seemingly locked, he wasn’t even the best in the NL alone. With the NL being the easier of the two leagues, most certainly, it seemed that Stanton had every advantage there could’ve been given — aside from playing in Coors for 81 games.

Here’s how his 2017 season fared:

59 HR and 132 RBI paired with 32 2B. with a .281 / .376 / .631 slash line (1.007 OPS) 6.9 WAR / and a whopping 156 wRC+

Mind you, these numbers are indeed phenomenal, but they are not deserving of being named “Top 10” in baseball, let alone “NL MVP.” Giancarlo did what no one had done in over a decade, and that is hit 59 homers (Ryan Howard hit 58 in 2006). He surpassed every personal best of his entire career, and rewrote his own book — which was filled with injury questions, as well as his inability to hit for average.

However, factoring in the huge increase in the amount of home runs hit this season, Stanton’s monumental 59 is slightly less impressive.

% OF RUNS OFF OF HR

2017- 42.3 % (+2.1 %)

2016- 40.2 % (+2.9 %)

2015- 37.3 % ( / )

NUMBER OF HR HIT

2017- 6,105 (+495)

2016- 5,610 (+701)

2015- 4,909 ( / )

With this being known, there were 41 players with over 30 homers, as well as Kris Bryant, Bryce Harper, Jose Ramirez, and Mike Napoli being notched with 29.

Giancarlo Stanton’s career numbers should not boost him to the top-10 consideration, so why would one season justify such? Stanton is a career .268 hitter, and never hit more than 37 homers in a single go (although yes, he never played more than 150 games). Even with his AS recognition in 2014, in which he slugged 37 to pair with a 6.3 WAR season, he wasn’t even considered top-5 then. The drastic injuries that Stanton has faced, as well as his lack of defensive abilities and base-running abilities, mean his value is hurt. Even for the 2017 NL MVP, Stanton shouldn’t win.

59 HR- 1st in NL

132 RBI- 1st in NL

.281 AVG- 24th in NL

.376 OBP- 14th in NL

.631 SLG- 1st in NL

6.9 WAR- 2nd in NL

156 wRC+- 2nd in NL

Although Stanton did indeed have the edge in the majority of these categories, it is seen that aside from his impressive slugging percentage, he was not even top-10 in any other categories. If we’re being honest with each other, Anthony Rendon, Justin Turner, and Joey Votto all put together more impressive and stand-alone seasons.

Rendon- .301 / .403 / .533 slash with a 6.9 WAR and a 143 wRC+ over 605 PA at 3B

Turner- .322 / .415 / .530 slash with a 5.1 WAR and a 151 wRC+ over 533 PA at 3B

Votto- .320 / .454 / .578 slash with a 6.6 WAR (1B gets brutalized for WAR) and a 165 wRC+ over 707 PA (record number for walks taken in a season)

However, this discussion is not about whether or not Stanton should win MVP. It is whether or not Stanton should be considered a top-10 position player in the game of baseball. In my opinion the list currently stands as such:

1. Mike Trout
2. Jose Altuve
3. Bryce Harper
4. Paul Goldschmidt
5. Kris Bryant
6. Joey Votto
7. Josh Donaldson
8. Manny Machado
9. Buster Posey
10. Daniel Murphy

(with Rizzo, Judge, Lindor, Gary Sanchez, Freeman, Corey Seager, and Nolan Arenado in the territory)

The reasoning behind this list is both the strength of their position, as well as their career history and trajectories. Trout is easily the greatest player in the game, and shows no signs of slowing down. Altuve is the best infielder in the game right now, and I don’t see him ever hitting under .300 for the rest of his career. Harper is younger than Trout, and has already accomplished things that no player can imagine, and possesses five tools to his game. Goldschmidt, like Votto later on, is the epitome of consistency. Bryant, Donaldson, and Machado are all in a different breed of third basemen (Nolan not far behind) with their amazing offensive production, and defensive splits. Posey is the best catcher in baseball, and hits supremely well for average. And Daniel Murphy is the same as Posey, where he is a phenomenal contact hitter, with the power upside. With the other players in the area, all of them are young with upside, and their minor-league track records mixed with their current production at the major-league level lead me to believe they’re the real deal.

Stanton may barely crack T20 in my eyes. With the fact that he is too slow and lumbering in the basepaths, mixed with his horrid defensive splits (10 DRS, below average/ 6.7 UZR, below average/ -.5 dWAR), he’s a one-dimensional player. Stanton clearly is a generational talent, and possesses power like no other in baseball, but with his poor attitude and colossal contract, he should be labeled overrated. He is making nearly 30 million dollars per year, and for a player who has only surpassed a 6 WAR twice over his eight seasons, it makes you question how truly valuable he is.

According to Marlins new CEO and part owner, Derek Jeter, the Marlins are “in a rebuilding process,” which Stanton responded to with “I want no part in a rebuild.”

What does the future hold for Giancarlo Stanton and his massive $220 million that is due? The world will just have to sit back, relax, and enjoy the show.

Let’s set the scene here. Top of the fifth inning, two out, two on. Your ace has come into the game, and given up the lead. All you’re looking to do is to minimize the damage. Just when it looks like you’re out of the jam with a big strikeout from Scherzer, the ball scoots between Wieters’ legs, and heads to the backstop. The one wrinkle, you might ask? Oh yeah, Wieters gets hit on the backswing by Baez. Now, there was no doubt in anyone’s mind that Baez hit Wieters, or so we think. The average casual baseball fan might be wondering if something could be called.

Some more experienced baseball fans may be inclined to say that was unintentional backswing interference, but in this scenario, that is wrong. Some may think that since Baez didn’t hit him intentionally, there should be no penalty.

Now for the good stuff. In the Official 2017 MLB Rulebook, the comment under rule 6,01 a) states:

“If a batter strikes at a ball and misses and swings so hard he carries the bat all the way around and, in the umpire’s judgment, unintentionally hits the catcher or the ball in back of him on the backswing, it shall be called a strike only (not interference). The ball will be dead, however, and no runner shall advance on the play.”

and the PBUC manual even goes slightly further to elaborate on this. On top of the official MLB ruling, it adds, “If this infraction should occur in a situation where the batter would normally become a runner because of a third strike not caught, the ball should be dead and the batter declared out.”

So was Wieters right to be frustrated with the non-call? Absolutely. Should Dusty have tried his case a bit further? Probably. Jerry Layne and his crew missed a call that ended up costing the Nationals two runs in a game that they ended up losing by a single run. If Layne gets this call right, does Scherzer get another inning? Does getting out of a jam wake up the Nationals’ bats for a big inning to propel them to the NLCS? I guess we’ll never know.

Everyone knows the strike zone alters based off the count. It shouldn’t, but umpires can’t help but be biased. If the count is 3-0, the strike zone will be more forgiving to the pitcher. If the count is 0-2, the zone will be more forgiving to the hitter. What does the zone look like for each possible count? Using Statcast detailed zones, let’s look at the called-strike rate on the corners for the last five years.

As expected, the lowest rate comes from 0-2 counts, and the highest rate comes from 3-0 counts. But the difference is shocking. A pitch in the same location is called a strike 26.46% more often, just because of the count. Here is the same table, ordered by increasing rate.

Four of the first five are two-strike counts, where umpires seem to favor the batter. The average rate in those zones in the past five years, regardless of count, is 22.45%. The rate on all two-strike counts is 13.16%, a good bit below the overall average. Hitters ahead in the count have nearly twice as many strikes called on them in the corner zone, as the rate spikes from 13.68% when they are behind to 25.99%.

What stands out is how much one strike can affect the umpire. The last four are all no-strike counts, and there is an over 10% difference between 3-1 and 3-0. One strike significantly changes how the zone is called. Balls, on the other hand, do not have the same effect on the zone. Two-ball and three-ball counts are up and down the list. The amount of strikes controls the way the zone is called.

It’s a given that the zone will expand to favor pitchers when they are behind, but the difference is surprising. A first-pitch strike is always preferred, but pitchers also get a significant amount of leeway as they fall behind.

I researched a potential cost of elevating before. I found a small but not significant correlation of launch angle and strikeout rate, and also a hint that hitters who elevate more might suffer in BABIP, especially if the guys pull a lot. That makes sense, since the BABIP on balls above 25 degrees is just 0.093. Some of that is pop-ups as sometimes FB hitters tend to hit more pop-ups, but even just looking at non-popped-up higher FBs (25 to 40 degrees), the BABIP is just 0.167. Even subsetting that for balls hit at 100+ MPH, the BABIP still is only .233, so that doesn’t help much.

However, that is not the whole story, as HRs are hits too. The BABIP might suffer, but if you hit a lot of homers, that can offset some of that. You can calculate that pretty easily. If the BABIP of higher FBs above 25 is 0.093, that means you need a HR/FB of around 20% to hit for a true average in play of .300. If you look at guys who hit no pop-ups, that requirement lowers to about 18% (.114 BABIP on balls between 25 and 60 degrees as non IFFBs). That doesn’t even really change for harder hitters, as the BABIP between 25 and 60 with 95+ MPH still is only .130, so HR/FB remains the limiting factor. High-pop-up hitters might require higher minimum HR/FB threshold to keep the OBP up.

A good example is prime Pujols. He was no Bautista/Dozier HR-or-out type of elevator, but his BABIP was only around league average while his average was higher than his BABIP, due to low K and high HR/FB rates. Thus, he could hit for the same average as Miggy, who routinely had .330+ BABIPs but slightly worse K and HR/FB rates.

Here is a table showing wOBA for different LA/EV combinations. I used 87 as a cutoff because that was the 2017 league average. Minus 10 to plus 5 was taken as more “line-drive grounders” while <-10 was used for chopped grounders and anything above 60 as a pop-up, so I did not divide that more. Keep in mind those are all hits and not hitters/average EV.

You can see that higher EV guys have a higher effective LA range. The very soft group actually was a little less sensitive for EV in FB angles, probably because there are a lot of bloopers in that range. Thus that might not apply that much for guys who routinely hit that soft, and thus are played shallower.

The slightly below average group was effective between 5 and 25 and then had a sharp drop-off. With the slightly above average group, the grounders get a little more effective, the peak at the line-drive angles gets a little higher, but there still is a big drop-off around 25 degrees, actually even starting above 20 degrees.

Now it really changes in the hard-hit range (95+) and especially the really hard-hit balls (100+, 110+). The really hard hitters stay effective until almost 45 degrees, meaning they do much better in the non-popped-up but high outfield fly balls (pop-ups are not sensitive to EV and always produce nothing). Those real power hitters (not the Murphy/Altuve type elevators, but guys like Gallo, Sano, Stanton, Judge who can really hit it) thus should hit a lot of fly balls to the OF.

The slightly above average power guys can still benefit from elevating, but then a few things must be true:

1)at least low-ish K rate. This is seen with Altuve and Murphy who don’t hit super hard but for great production

2) The elevated balls shifted towards the LD range and away from the high OF FB range, i.e. a very narrow LA range. Murphy here ideally is again a prime example because he hits very few grounders without a really high FB rate

3) Ideally a low pop-up rate

So it really depends on the type of hitter how they should approach. The hard hitters are always quite effective, even with grounders, but still they need to elevate since the grounders are only around average, but they usually have low defensive value and high Ks and thus need to compensate something. The really hard hitter is rarely truly terrible even as a grounder machine (see Christian Yelich), but if there are higher Ks and no defensive value they might still be bad players. Also despite grounders being less bad, the gap between grounders and FBs is still getting larger, so they have more to gain by elevating. Thus it makes sense for them to go into the OF FB range.

For the really low power hitters it doesn’t really matter unless they slap it straight into the ground, which still is a bad idea for them.

And the average power hitters should shoot for the low-line-drive range unless they are able to have a very narrow range and avoid the high OF FBs; then they can elevate up to the 15-20 range without a penalty (Daniel Murphy type).

Watching the Yankees and Twins playoff game last week, I noticed that it seemed the strike zone was pretty tight. This was just one playoff game and a few pitches, but I thought of the possibility of a shrinking strike zone in the playoffs, as umpires may be less forgiving.

Baseball Savant would not let me run a query for all seasons, so I divided my data queries into three-year increments, dating back to 2009. First, for each three-year set, I found the total called strikes and balls (pitches not swung at) and calculated what percentage were called strikes for the regular season and the playoffs.

The zone grew a little from the regular season to the playoffs in 2015-17 and 2009-11, but shrunk a little in 2012-2014. So no indication of any sort consistent strike-zone change.

Using the Statcast detailed strike zones, I looked at the same called-strike rate on zones 11, 13, 17, and 19. These zones are the corners of the strike zone, with half of the area in the zone and half outside of it.

There is a clear change here, and not in the direction I thought it would. There is a 3% average increase of called strikes on the corners here. Not a huge change, but certainly a difference-maker. Looking at just this season, the called-strike rate on the corners has increased from 21.88% in the regular season to 24.14% in the postseason.

Let’s look at the rest of the edges of the strike zone (area between the corners).

Not nearly the difference of the corners, but an average of a 1.58% increase. There is definitely a trend of strike-zone expansion.

This also begs the question of whether Rob Manfred’s initiative to raise the bottom of the strike zone has had any effect. There was worry that umpires had become too trigger-happy with pitches around the knees. Looking at only pitches in the bottom edge of the strike zone, the called strike rate in 2014-16 for the regular season was 34.78%. In the 2017 regular season, it was 33.85%. So it appears there was definite change. But has Manfred’s wish stayed consistent in the playoff?

The called-strike rate in the zones bordering the bottom of the strike zone (through October 9) is 37.38%, nearly four percentage points higher than the regular season. So umpires are not meeting Manfred’s hopes in the playoffs thus far.

We can’t be sure of how this affects playoff games, but Dustin Pedroia struck out looking on a bottom-corner pitch barely in the zone with the bases loaded. Maybe if it were like the regular-season strike zone, we would be talking about an Astros and Red Sox Game 5. Obviously we cannot assume anything, but it’s hard to argue this does not change the game at least a little.

Clearly, my initial inclinations watching the Yankees and Twins play were wrong. I was surprised to discover the zone actually expands, not shrinks, in the postseason. In a climate that is already more difficult for hitters, as most teams are pitching their best stuff, it is only making postseason hitting even more difficult.

To wrap up the season, let’s take a look at the winners of leaders of some interesting sabermetric categories. Not all of these are meant to be indicative of a player’s skill; rather just interesting notes. First, hitters:

Three True Outcomes

To measure this, I added players K%, BB%, HR/PA, and HR/H together.

1. Joey Gallo, 1B/3B, Texas Rangers
2. Aaron Judge, RF, New York Yankees
3. Chris Davis, 1B, Baltimore Orioles

This leaderboard surprises no one. It’s essentially Gallo, then Judge, then everybody else. Davis is in third, but he has Giancarlo Stanton and Khris Davis right on his heels.

Good Contact

I utilized Statcast’s xwOBA and players’ Hard%, while also setting contact minimums, to calculate a measure of guys who make consistent, hard contact.

1. Paul Goldschmidt, 1B, Arizona Diamondbacks
2. Corey Seager, SS, Los Angeles Dodgers
3. Nelson Cruz, DH, Seattle Mariners

Two stars and then an aging former star.

Plate Discipline

Z-O Swing% was used to measure discipline.

1. Joey Votto, 1B, Cincinnati Reds
2. Jed Lowrie, INF, Oakland A’s
3. Freddie Freeman, 1B/3B, Atlanta Braves

Votto has long been one of the kings of plate discipline, and he’s still getting better. Lowrie is quite a surprise, but Jeff Sullivan recently dubbed him as one the league’s most improved players.

Contacters 

I used O-Contact% + Z-Contact% to give more weight to making contact outside of the zone.

1. Melky Cabrera, LF, Chicago White Sox/Kansas City Royals
2. DJ LeMahieu, 2B, Colorado Rockies
3. Joe Panik, 2B, San Francisco Giants

All of these guys are sticking with career norms as contact hitters.

Hackers

Z-Swing% + O-Swing% to see who hacks at everything.

1. Corey Dickerson, OF, Tampa Bay Rays
2. Avisail Garcia, RF, Chicago White Sox
3. Adam Jones, CF, Baltimore Orioles

Dickerson and Garcia opened the season with impressive breakouts that slowly diminished throughout the year. Jones kept doing what he does.

Now, the pitchers:

Contact Managers

Looking at GB%, IFFB%, soft contact rate, and xwOBA allowed.

1. Dallas Keuchel, SP, Houston Astros
2. Brad Peacock, SP, Houston Astros
3. Corey Kluber, SP, Cleveland Indians

Keuchel has established himself as the ground-ball king. Kluber and Peacock are fourth and eighth in K/9, so their inclusion is impressive.

Swing Generators

Z-Swing% + O-Swing%

1. Masahiro Tanaka, SP, New York Yankees
2. Madison Bumgarner, SP, San Francisco Giants
3. Jake Odorizzi, SP, Tampa Bay Rays

Tanaka had a rough season, while Bumgarner did not play much of the season. Odorizzi was quite terrible, posting a 5.34 FIP.

Whiff Generators

Z-Contact% + O-Contact%. Lower is better.

1. Robbie Ray, SP, Arizona Diamondbacks
2. Corey Kluber, SP, Cleveland Indians
3. Max Scherzer, SP, Washington Nationals

These guys are two, four, and three in starter strikeout rate.

Commanders

Lowest walk rates.

1. Josh Tomlin, SP, Cleveland Indians
2. Jeff Samardzija, SP, San Francisco Giants
3. Clayton Kershaw, SP, Los Angeles Dodgers

Tomlin did not pitch well all year, but he quietly posted an incredible 0.89 BB/9.

Off-Speeders

Guys who threw the highest rate of off-speed pitches.

1. Lance McCullers, SP, Houston Astros
2. Jordon Montgomery, SP, New York Yankees
3. Madison Bumgarner, SP, San Francisco Giants

McCullers’ crazy curveball throwing is well known. Montgomery features a lot of curveballs and changeups, while mixing in sliders. Bumgarner throws a heavy dose of sliders, and includes curveballs every so often.

There isn’t much to this. I’m sure there are many categories I could have added. I just wanted to throw out some information that people might be interested in.

In some FanGraphs articles, Z-O swing percentage is thrown around as a measure of plate discipline. That makes sense because generally when a hitter swings at strikes, good things happen, and if he swings at balls, bad things happen.

To test if that stat is really better, I looked at the 2017 leaderboard. I looked at the wRC+ of the top 30 and bottom 30 hitters with Z-swing%, O-swing%, and Z-O swing%. Here is what I found:

There is a slightly positive effect of Z-swing, but a much stronger effect of both Z-O swing% and O swing%. At the top, the low-chaser and high-differential guys do about the same, while the bottom chasers do even worse than the bottom differential guys.

If you widen the search for top half and bottom half you get that picture:

Z-swing has no effect at all, and the differential is slightly better than the chase rate, but not by much.

Overall, the Pearson value for differential was a positive .42, for the chase rate it was .32 (used 100 – O-swing% to get positive value), and for Z-swing there was almost no effect (.07). So the differential is a bit better, but the effect isn’t huge; it is probably like with OPS+ and wRC+ where one is mathematically more elegant and correct but the actual values won’t differ much.

I also dissected the hitting into the components OPB, ISO and BABIP.

The result is quite interesting. The differential (+27 ISO points) does clearly better in the power department than chase rate (+7); in fact, even Z-swing had a more positive effect (+17) on power than a low chase rate.

With OBP, that is reversed. Here, the chase group does better than the differential group, while a high Z-swing rate has a negative effect.

With BABIP there was a very small positive effect of differential and Z-swing, and no effect of the chase rate, but the effects are almost non-existent.

So we seem to have two opposing effects here. Being more aggressive in the zone helps the power but seems to slightly hurt the OBP (of course there probably is a bias that aggressive hitters in the zone are often also aggressive outside, but still). And for OBP, chase rate clearly is king, while it doesn’t really have an effect on power.

Still, that might have an effect for certain hitters and especially pitchers, but overall the advantage doesn’t seem to be big, even though it is a bit due to coincidence due to the opposing effects.

This is the final part of my pitch-ranking data. Let’s start with the top 25 overall pitches, starters and relievers combined.

Top Pitches:

We have two pitchers that show up twice — Corey Kluber and Sonny Gray. Kluber has arguably been the best pitcher in baseball in 2017, so that is unsurprising. However, Gray as his only two-pitch counterpart is unexpected. Gray is by no means a poor pitcher, but not the same level as Kluber. Jaime Garcia and Tyler Chatwood are the only guys on this list who jump out as poor pitchers, in 2017 at least. Luis Castillo and Jacob Barnes are probably the only guys on this list who are completely unfamiliar for most. Castillo’s future looks bright, where Barnes looks less significant.

I’m sure some have been wondering: What are the worst pitches?

Applying some context, these are certainly not the worst pitches in the game. Just the worst thrown consistently. Every pitch had to reach a minimum number of times thrown to reach this list. These are not the absolute worst pitches in the game, but make no mistake, they are still truly awful. The bottom ten of over 700 pitches. Anyway, here are the ten worst that I measured:

Two names jump out immediately in that list. Dellin Betances and Johnny Cueto. However, considering the widely-known struggles of those two, it’s not nearly as shocking as it might have been last year. Justin Grimm has been downright atrocious, so it’s fitting to see him there. The same goes for Jason Grilli. And Jordan Zimmermann. Kevin Gausman was awful, but has turned it around. Mike Leake has done the exact opposite of that. This is the first time I have seen Warwick Saupold and Paul Blackburn on a list of any kind, good or bad. Blackburn has actually been solid in a small sample for the A’s in his rookie year. Montgomery has continued to provide quality long-relief innings and spot starts for the Cubs.

This was just my first trial run playing around with pitch values. I will continue to work towards a better formula and continue to post in the future. I will post the Excel file with all the pitches and data I used for calculations. Feel free to add, but please don’t change or delete any of the original information.

Pitch Data Excel File

We are yet to establish a truly effective method of measuring the effectiveness of a pitch and comparing pitches. One of the main problems with attempting to evaluate a pitch on it’s own is nearly impossible. If a pitcher has an exceptional fastball, that is going to elevate his slider. Another pitcher may have a slider with more “stuff,” but it will not rank as well without the other effective pitches in his repertoire.

I will attempt to create a method here that will allow us to measure effectiveness in an improved way, although there is no guarantee here that I will succeed.

Let’s start with the main things a pitch has to be effective. In theory, a perfect pitch would be thrown in the zone and generate whiffs, while allowing weak contact when it is put in play. Obviously, it is unreasonable to expect a pitcher to generate lots of whiffs inside the zone against major-league hitters, so throwing outside the zone is a necessity in baseball to get swings and misses.

So, I used two evaluators for pitch effectiveness. I formed my own measurement, Swing%+Whiff% (Sw+Whf%). Since many pitches are meant not to be thrown in the strike zone, I did not include Zone% or Strike%. The Sw+Whf% should evaluate the ability of a pitch to get swings, and swings and misses. That evaluator covers the “stuff” component of the pitch. For the second evaluator, I used xwOBA (expected OBA), which gives a “true” wOBA based off exit velocity and launch angles. This covers the contact management component of the pitch. These are not all weighted for the part they play in run scoring, so it is not perfect, but they should give us a solid idea of what a pitch could do.

Obviously, different pitches will have different average values for these evaluators. A breaking ball is going to create more whiffs than a fastball. Fastballs are easier to hit, and thus will have a higher xwOBA. These evaluators themselves can not be used to compare different types of pitches. This is where the Z-Scores come in to play.

A Z-Score measure how much something deviates from average. First, we take the standard deviation and mean of a data sample. Then, for the Sw+Whf%, we subtract the mean from the individual’s Sw+Whf%, and divide that number by the standard deviation. We have our Z-Score! If the Sw+Whf% is higher than average, the Z-Score will be above zero, which means it is better than average. If the Sw+Whf% is lower than average, the Z-Score will be below zero, indicating the pitch is worse than average. It is the same thing for xwOBA, except for xwOBA lower is better. So instead of subtracting the mean from the individual’s xwOBA, we subtract the individual’s xwOBA from the mean. Add the two Z-Scores together, and we have our total Z.

Example:

The average Sw+Whf% on four-seam fastballs, for pitchers with a minimum of 500 four-seamers thrown, is 63.78. The average xwOBA allowed on these is .347. Chris Sale owns an 85.89 Sw+Whf% and .238 xwOBA on his four-seam fastball. The Sw+Whf% STD is 7.14 and the xwOBA STD is .038.

Sw+Whf% Z-Score: (85.89-63.78)/(7.14) = 3.08

xwOBA Z-Score: (.347-.238)/(.038) = 2.86

Total Z-Score: 3.08 + 2.86 = 5.94

Sale’s 5.94 is an incredible score, with second-place Jacob deGrom sitting at 4.81, over 1 below Sale. After that, no one else even reaches 3.5. The Z-Score has no unit, so it can be slightly confusing. It is a measurement of how many standard deviations above or below average something is.

A few things to be careful of here. These numbers are not predictive. They are simply meant to measure the effectiveness of a pitch and allow us to compare different types of pitch in a more simplified way than run values. It is just a fun statistic to look at, not something used to project the future. We also have the same problem as run values. It is impossible to look at a pitch by itself, as a good fastball will elevate a good slider. I am attempting to determine something that will allow us to better differentiate a player’s specific pitches from each other, but for now, we have this. I will be posting all the specific pitch data and tables for each pitch for starters and relievers and doing some analysis in the next few days. This is just the introduction.