Archive for October, 2017

Thinking Like an MLB MVP Voter

Photo: Yi-Chin Lee/Houston Chronicle

Baseball season is coming to a close and the Baseball Writers’ Association of America (BBWAA) will soon unveil its votes for AL and NL MVP. The much-anticipated vote is consistently under the public microscope, and in recent years has drawn criticism for neglecting a clear winner *cough* Mike Trout *cough*. This being one of the closest all-around races in years, voters certainly have some tough decisions to make. This might be the first year since 2012 where it’s not wrong to pick someone other than Mike Trout for AL MVP.

Of course, wrong is subjective. The whole MVP vote is subjective. Voter guidelines are vague and leave much room for interpretation. The rules on the BBWAA website read:

There is no clear-cut definition of what Most Valuable means. It is up to the individual voter to decide who was the Most Valuable Player in each league to his team. The MVP need not come from a division winner or other playoff qualifier. The rules of the voting remain the same as they were written on the first ballot in 1931:

1.  Actual value of a player to his team, that is, strength of offense and defense.

2.  Number of games played.

3.  General character, disposition, loyalty and effort.

4.  Former winners are eligible.

5.  Members of the committee may vote for more than one member of a team.

It won’t do any good for me to saturate the web with another opinion piece on who deserves to win. It won’t change the vote, and I don’t think I could choose. My goal is rather to illustrate how BBWAA voters have interpreted these rules over time. Have modern sabermetrics driven any shifts in voter consideration? Do voters actually consider team success? Do voters unconsciously vote for players with a better second half?

I thought the best (and most entertaining) way to answer these questions would be to create a model that would act as an MVP voter bot. Lets call the voter bot Jarvis. Jarvis is a follower.

  1. Jarvis votes with all the other voters.
  2. It detects when the other voters start changing their voting behavior.
  3. It evaluates how fast the voters are changing behavior and at what speed it should start considering specific factors more heavily.
  4. It learns by predicting the vote in subsequent years.

I created two different sides to Jarvis. One that is skilled at predicting the winners, and one that is skilled at ordering the players in the top 3 and top 5 of total votes. The name Jarvis just gives some personality to the model in the background: a combination of the fused lasso and linear programming. And it also saves me some key strokes. If you are interested in the specifics, skip to the end, but for those of you who’ve already had enough math, I will spare you the lecture.

Jarvis needs historical data from which to learn. I concentrated on the past couple decades of MVP votes spanning 1974 to 2016 (1974 was the first year FanGraphs provided specific data splits I needed). I considered both performance stats and figures that served as a proxy for anecdotal reasons voters may value specific players (e.g., played on a playoff-bound team). For all performance-based stats, I adjusted each relative to league average — if it wasn’t already — to enable comparison across years (skip to adjustments here).  Below are some stats that appeared in the final model.

Position player specific stats: AVG, OBP, HR, R, RBI

Starting pitcher (SP) specific stats: ERA, K, WHIP, Wins (W)

Relief pitcher (RP) specific stats: ERA, K, WHIP, Saves (SV)

Other statistics for both position players and pitchers:

Wins Above Replacement (WAR) Average of FanGraphs and Baseball Reference WAR

Clutch – FanGraphs’ measure of how well a player performs in high-leverage situations

2nd Half Production – Percent of positive FanGraphs WAR in 2nd half of season

Team Win % – Player’s team winning percentage

Playoff Berth – Player’s team reaches the postseason

Visualizing the way Jarvis considers different factors (i.e. how the model’s weights change) over time for position players reveals trends in voter behavior.

Immediately obvious is the recent dominance of WAR. As WAR becomes socialized and accepted, it seems voters are increasingly factoring WAR into their voting decisions. What I’ll call the WAR era started in 2013 with Andrew McCutchen leading the Pirates to their first winning season since the early 90s. He dominated Paul Goldschmidt in the NL race despite having 15 fewer bombs, 41 fewer RBI, and a lower SLG and OPS. While Trout got snubbed once or twice since 2013, depending on how you see it, his monstrous WAR totals in ’14 and ’16 were not overlooked.

As voters have recognized the value of WAR, they have slowly discounted R and RBI, acknowledging the somewhat circumstantial nature of the two stats. The “No Context” era from ’74 to ’88 can be characterized perfectly by the 1985 AL MVP vote. George Brett (8.3 WAR), Rickey Henderson (9.8), and Wade Boggs (9.0) were all beaten out by Don Mattingly (6.3), likely because of his gaudy 145 RBI total.

Per the voting rules, winners don’t need to come from playoff-bound teams, yet this topic always surfaces during the MVP discussion. Postseason certainly factored in when Miggy beat out Mike Trout two years in a row, starting in 2012. See that playoff-berth bump in 2012 on the graph below? Yeah, that’s Mike Trout. What the model doesn’t consider, however, are the storylines, the character, pre-season expectations: all the details that are difficult for a bot to quantify. For example, I’ve seen a couple of arguments for Paul Goldschmidt as the front-runner to win NL MVP after leading a Diamondbacks team with low expectations to the playoffs. I’ll admit, sometimes the storylines matter, and in a year with such a close NL MVP race, it could push any one player to the top.

What can I say about AVG and HR? AVG is a useless stat by itself when it comes to assessing player value, but it’s ingrained in everyone’s mind. It’s the one stat everyone knows. Hasn’t everyone used the analogy about batting .300 at least once? Home runs…they are sexy. Let’s leave it at that.  Seems like these are always on the minds of MVP voters and that is not likely to change any time soon.

I’m sure some of you are already thinking, “What about pitchers!?” Don’t worry, I haven’t forgotten — although it seems MVP voters have. Only three SP and three RP have won the MVP award since 1974, and pitchers account for only about 7.5% of all top-5 finishers. As you can see in the factor-weight graph below, their sparsity in the historical data results in little influence on the model; voter opinions don’t change often, and their raw weights tend to be lower than position players. Overall, it seems as though wins continue to dominate the SP discussion, along with ERA and team success. While I would expect saves to have some influence, voters tend to be swayed by recency bias and clutch performance along with WHIP and WAR.

What would an MVP article be without a prediction? Using the model geared to predict the winners, here are your 2017 MLB MVPs:

AL MVP: Jose Altuve    Runner Up: Aaron Judge

NL MVP: Joey Votto   Runner Up: Charlie Blackmon

Here are the results from the model tuned to return the best top-3 and top-5 finisher order:

It’s apparent that I adjusted rate and counting stats for league and not park effects given both Rockies place in the top 2. Certainly, if voters are sensitive to park effects, Stanton and Turner get big bumps, and Rockies players likely don’t have a chance. Larry Walker was the only Colorado player to win the MVP since their inception in 1993, but in a close 2017 race it might make the difference.

Continue reading below for the complete methodology and checkout the code on github.

A previous version of this article was published at sharpestats.com.


Statistical Adjustments

Note: lgStat = league (AL/NL) average for that stat, qStat = league average for qualified players, none of the adjusted stats are park adjusted

There were two different adjustments needed for position player rate stats and count stats.

Rate stat adjustment:  AVG+ =  AVG/lgAVG  

Count stats: HR, R, RBI

Count stat adjustment:  HR Above Average =  PA*(HR/PA – lgHR/PA)

There were three different adjustments needed for starting pitcher (SP) and relief pitcher (RP) rate stats and count stats.

Rate stats: ERA, WHIP

Rate stat adjustment:  ERA+ =  ERA/lgERA  

Count stats I: K

Count stat I adjustment:  K Above Average =  IP*(K/IP – lgK/IP)

Count stats II: Wins (W), Saves (SV)

Count stat II adjustment:  Wins Above Average = GS*(W/GS – qW/GS)


Fused Lasso Linear Program

I combined two different approaches to create a model I thought would work best for the purpose of predicting winners and illustrating change in voter opinions over time. Stephen Ockerman and Matthew Nabity’s approach to predicting Cy Young winners was the inspiration for my framework for scoring and ordering players. A players score is the dot product of the weights (consideration by the voters) and the player’s stats.

The constraints in the optimization require the scores of the first place player to be higher than the second place, and so on and so on. This approach, however, doesn’t allow for violation of constraints. I add an error term for violation of these constraints, and minimize the amount by which they are violated.

Instead of constraining the weights to sum to 1, I applied concepts from Robert Tibshirani’s fused lasso which simultaneously apply shrinkage penalties to the absolute value of weights themselves as well as the difference between weights for the same stat in consecutive years. This accomplishes two things: 1) it helps perform variable selection on statistics within years helping combat collinearity between some performance statistics, and 2) it ensures that weights don’t change too quickly overreacting to a single vote in one year.

However, this approach and formulation cannot be solved by traditional linear optimization methods since absolute value functions are non-linear. The optimization can be reformulated as follows:

To select the lambda parameters, I trained the model using the first 10 seasons of scaled data increasing the training set by 1 season each time and tested with the subsequent year’s vote.After in season statistical adjustments, I scaled the stats by mean and standard deviation of training data to enable comparison across coefficients. All position player stats were replaced with 0 for pitchers and vice versa.

References:

1. Ockerman, Stephen and Nabity, Matthew (2014) “Predicting the Cy Young Award Winner,” PURE Insights: Vol. 3, Article 9.

2. R. Tibshirani, M. Saunders, S. Rosset, J. Zhu, and K. Knight. Sparsity and smoothness via the fused lasso. Journal of the Royal Statistical Society Series B, 67(1):91–108, 2005.

 


The Three True Outfits

There is a new trend in baseball over the past decades. One that reflects a big change in the game: The three true outfits.

Until the 1940’s, there was essentially one way that players wore their uniforms: Baggy pants, tucked into socks. Everyone on the team looked the same; there was no variation in how the players wore their uniforms.

Then things started to tighten up. By the 1970s, the whole team was wearing their pants tight, tucked into socks. The style was dramatically different from before, but there was little difference between players. All uniforms were tight.

In the past decades, something different has occurred. Players on the same team technically wear the same uniform, but how the uniform is worn varies dramatically from player to player.

Some players wear their pants big and baggy, covering not only their socks but their shoes as well. Other players wear their pants tight. Still other players are somewhere in between, wearing their pants in a more standard size, slacks-style.

Other pieces of the uniform add even more variation across players. Socks are worn in or out. Hats are flat or curved, sitting straight on the head or off-center. Jerseys can be buttoned up or unbuttoned. Shirts can be worn under the jersey or not, and vary in sleeve length.

What was once one outfit has become at least three true outfits, if not more. Players wear their uniforms in a variety of ways, reflecting the increasing diversity of the players and the game.

People have been critical of some of the styles, particularly the baggy pants. A writer for The New York Times, for example, discussed the fashion criticism of baseball style in a 2013 article, “Baseball Pants, a Sore Sight for Eyes.” “The World Series is a showcase for not only the finest teams in the game,” he wrote, “but also, for about the 15th year running, the regrettable fashion trend of the baggy, pajama-pant look.” One member of the fashion industry concluded, “What was once a stylish game has gotten depressingly schlubby.”

But the styles being criticized are actually far older than 15 years; they are the styles of the past, the pants of Babe Ruth. Baseball players today are making traditional styles modern and choosing how they want to look.

This trend reflects trends in fashion overall. Rather than walking around in top-down-imposed, creativity-crushing, cookie-cutter versions of clothing and ourselves, we want to be freer today to express our individuality in our lives and in our clothing. This diversity and individuality is reflected not only in the clothes worn on the field, but in the style of play. Baseball players are making the uniform, and the game, their own. This is good for baseball.


Just How Valuable Was Chad Green?

For all the surprises the 2017 season had to offer, one of the more pleasant ones had to be the rise of Chad Green.

Once a starting pitcher, Chad Green was converted to a relief pitcher this season. It was, for technical reasons, his first full season. His repertoire of the four-seam fastball, cutter, and slider combine for a nasty usage of all three. While he did throw his fastball 69.4% of the time this past season, the slider made way with a 22.1% usage rate — the cutter came in at just 7.8% of the time.

Some contributing factors to Green’s remarkable season could be that he was able to change his approach from a guy preparing to go five, maybe six innings, to one who could use his best stuff for two or so. That allows him to throw harder, and riskier, for shorter amounts of time.

Green’s average velocity on his FB:

  • 2016- 94.3 mph
  • 2017- 95.8 mph

The fact that Green was able to focus in on his pitches more led to his posting a fantastic season. Green improved in every category possible, and put himself in the elite group of relief pitchers that baseball has to offer.

2016: (MLB: 45.2 IP/ 8 GS)

  • 10.25 K/9 to a 2.96 BB/9, with a 2.36 HR/9
  • 41.3% GB rate / 25.0% HR-FB rate
  • .269 BAA & 1.40 WHIP

2017: (MLB: 69.0 IP/ 1 GS)

  • 13.43 K/9 to a 2.22 BB/9, with a 0.52 HR/9
  • 26.4% GB rate / 6.7% HR-FB rate
  • .145 BAA & .74 WHIP

What that indicates is that Green’s pitches were better utilized when he was able to throw them at their maximum ability. Of course, naturally, with a smaller usage, there is a smaller room for error.

The biggest improvement for Green was his HR allowance. In 2016, over the 45.2 IP, he gave up 12 HR. In 2017, over 69.0 IP, he gave up a mere four. Green was able to strike out dramatically more batters, while lowering his GB rate from 41.3% in 2016 to 26.4% in 2017. Essentially speaking, Green just didn’t allow people to get on base.

In 2016, he faced 198 batters. He gave up 49 hits, walked 15 batters, and hit another. 55 batters allowed on base, leading to 26 earned runs. That equates to approximately a 28% allowance of runners on base.

In 2017, however, he faced 253 batters. He surrendered 34 hits, walking 17, and hitting two. 53 batters allowed on base, leading to 14 earned runs. That equals out to roughly 21% of runners on base.

Being only 26 years old, and the Yankees having him for the next four full seasons under their terms, it looks like the future is bright for Chad Green.

Green’s value was astounding this season. The ability to use him for multiple innings allowed the Yankees to use him for extended appearances, and they gave him the same rest as the other arms. What separates him from his teammate, David Robertson, is that Green (thanks to his SP past) was able to go multiple innings on command.

GREEN 2017 value & breakdown:

  • Green appeared in 40 games, throwing 69.0 IP (1.7 IP per)
  • His RAR (Runs Above Replacement) was 23.5
  • 2.4 WAR
  • BABIP Wins- 0.6

ROBERTSON 2017 value & breakdown:

  • D-Rob appeared in 61 games (CWS/NYY) throwing 68.1 IP (1.1 IP per)
  • His RAR was 18.5
  • 1.9 WAR
  • BABIP Wins- 0.8

While David Robertson is nominated for AL Reliever of the Year (along with Craig Kimbrel and Ken Giles), Chad Green is seemingly receiving no love from the MLB.

Kimbrel has to be most deserving of the three, posting an amazing 32.1 RAR and a 3.3 WAR.

Giles, on the other hand, is the worst of the three, and he posted numbers worse than Green. (18.1 RAR with a 1.8 WAR)

Chad Green was the Yankees’ go-to, or so it seemed. Whenever they were in a jam, Green would be brought in. Initially used as a sixth starter, or the “fifth-inning guy,” Green established himself as a huge piece in their bullpen.

Back in December of 2015, when the Yankees sent Justin Wilson over to Detroit for a pair of prospects, the word around the MLB was that it was a rather lopsided trade, in the Tigers’ favor. Wilson came off of a great season for the Yankees, in which he posted a 3.10 ERA over 74 appearances. Despite this, Cashman stuck to his guns and reinforced the fact that the Yankees needed SP help, more than another elite closer. When the trade was completed, the Yankees received Detroit’s number 6 and 19 overall team prospects. (Green was 19.)

Chad Green may not be the most exciting player the Yankees have traded for, but he sure may be the best valued. With him being under team control for the next four seasons, and the fact that he is still young and working on his offspeed pitches, it opens the way for future improvements. Can Green be better next season? We all saw what happened with Luis Severino when he improved his secondary pitches.

In Severino’s second season (2016):

  • 55.9% Fastball
  • 9.9% Changeup

2017:

  • 51.4% Fastball
  • 13.5% Changeup

Although it’s not a drastic change, the fact that he was able to regain that command and control over his changeup made way for him to catch batters off guard more, and change the eye levels. Green’s spread is not nearly as spread out as Severino’s is, and being a relief pitcher, it doesn’t have to be. Green’s fastball is thrown, again, 69.4% of the time.

If he can work on his cut fastball a little bit more, the possibilities can expand for Green. The swings and misses out of the zone would be greater, and the contact percentages against lefties would go down, because he would jam them in on the hands. Having the luxury of playing alongside Robertson, who throws a mean cutter (inherited from Mariano Rivera), and being able to surround himself with the amazing ensemble of the bullpen crew the Yankees have put together bodes well for Chad Green.

During the months of September and October, Green posted a 0.74 ERA, allowing just one earned run (not counting the postseason). He faced 44 batters, and gave up just seven hits, against his 17 strikeouts. Green never gave up more than four earned runs in any month of the entire season, and surrendered seven runs in both the first- and second-half splits. It is clear that Green was focused from the moment he came out of the pen.

While he only pitched 2.1 IP in “high-leverage” situations (27.0 in “medium” and 39.2 in “low”), I wouldn’t let that sway his stats in a negative connotation. Look for that to change this upcoming season, especially with Betances’ mental struggles. If I were to speak blindly right now, Chad Green would be my seventh-inning guy, with Robo in the eighth, and Chapman in the ninth. There should be a dramatic change in terms of “high-leverage” innings pitched for Chad.

Needless to say, Chad Green is a rather remarkable story, being that he was considered an add-on in the trade that was headlined by Luis Cessa. When the trade initially happened, Green was said to be the guy that “bridged the gap” for Bryan Mitchell if he were to struggle.

Chad Green will look to build on his remarkable first full season in the “Pinstripe Pen of Doom,” and help guide New York to that AL pennant next year.


Do Switch-Hitters Always Need to Switch?

Switch-hitting is a rare yet valuable trait for hitters. It gives a player a certain versatility that eliminates the necessity for platooning. But it is not uncommon that a player is markedly more successful from one side of the plate. Take Lance Berkman, for example, one of the best switch-hitters of all time. Here are his career splits from the right side vs. the left side:

Handedness AVG ISO BB% K% GB% FB% wRC+
Left .301 .265 16.7% 16.8% 40.3% 39.9% 155
Right .259 .158 12.6% 15.0% 47.4% 33.2% 105

Berkman was better in every facet from the left side, hitting for better average, more power, and lifting the ball more while showing a better eye. How many of those lefty plate appearances came against lefties? 0. It makes sense that all his plate appearances would be L v R and R v L because pitchers are better facing hitters of the same handedness. But that is not always the case.

There are always reverse split guys, with both pitchers and hitters alike. We even had one in World Series Game 2. Rich Hill‘s splits are not aggressively reverse, but for his career his wOBA and xFIP vs. lefties are .305 and 4.39, respectively. He’s posted .305 and 4.02 against righties in the same categories. The clear difference is his 16.0% K-BB% vs. righties and 11.5% vs lefties. The numbers were much more reverse in 2017, albeit in a small sample. This year, Hill’s wOBA allowed was .374 vs. .253, his xFIP was 6.08 vs. 3.36, and his K-BB% was 25.2% vs. 7.3%.

So, let’s take an example from that World Series game. Marwin Gonzalez, the Houston Astros’ switch-hitting utility man, had four plate appearances (not counting an intentional walk). In his first one, he faced Hill, striking out swinging. In his second one, he faced Hill, striking out looking. Both came as a righty. The next two came as a lefty. In his third, he drew a walk from Ross Stripling. And everyone knows what he did in his fourth appearance.

Gonzalez’s success and failures in those appearances did not stray from what he has done all year. Here are his left and right splits:

Handedness AVG ISO BB% K% LD% wRC+
Left .322 .230 10.0% 19.7% 22.0% 154
Right .250 .217 8.2% 17.9% 14.6% 115

He clearly displayed that he drove the ball better from the left side of the plate. So, Hill is worse against lefties and Gonzalez plays like an All-Star as a lefty. Wouldn’t it make sense to have him hit lefty?

Obviously, it’s not that simple, and you aren’t going to try an experiment in the World Series and have him hit lefty. Gonzalez’ eye isn’t trained to hit left-handed pitchers from the left side. And all his success from the left side may be because he sees right-handed pitching really well there. It also may disrupt a hitter if they mostly hit lefty versus righties, but then infrequently go left on left for the occasional reverse-split guy. It could make hitters completely uncomfortable, and a hitter is highly unlikely to perform if he is uncomfortable. In truth, most factors point to it being a bad idea, despite what numbers might say.

However, experimenting with the idea during inconsequential situations may be a good idea. I looked at some of the switch-hitters of the past decade with clearly more success from one side to see if any had toyed with hitting LvL or RvR. The group included Aaron Hicks, Mark Teixeira, Jose Reyes, Jed Lowrie, Chipper Jones, Pablo Sandoval, Justin Smoak, and Dexter Fowler.

One guy stood out — Sandoval. He’s accumulated 114 plate appearances as a LvL in his career. Still a tiny sample, but a clear demonstration that he has tried. Sandoval’s struggles as a righty are well-known, as his career wRC+ as a righty is a 80, vs. 124 as a lefty. In 2015, it appears he shelved the idea of hitting from the right side. 112 of those 114 LvL appearances came that season. In that one stretch, he was still poor, posting a 59 wRC+ against lefties. So he went back to hitting from the right side.

There are only two other guys, Teixeira and Reyes, who seemed to even have experimented with it. Teixeira hit 48 times as a RvR, and Reyes did the same 43 times. Teixeira seems to have messed around with it his entire career, having 4-5 such appearances nearly every year. While the sample is essentially nothing, his 138 RvR wRC+ is higher than both his LvR and RvL. On the other hand, Reyes’ appearances randomly popped up in 2010 and 2015, with 13 and 20 those years, respectively. He showed no sign of significant struggle as a lefty those years, so the randomness is strange. His -8 RvR wRC+ spoke for itself, anyway.

No one in the last decade, at least to my knowledge, has fully employed the tactic. The few that did fool around with it had mixed results. However, the success of Teixeira points to the fact that if the hitter feels comfortable, it may be a smart decision. Given the right matchup, of course. I attempted to find the pitching matchups for Teixeira as a RvR, but Statcast returned no results. It’s a strategy that probably many have thought about, but none have really used. Throwing in another situation to be accustomed to for a hitter may just be too difficult. But if a switch-hitter feels comfortable, it could be a helpful ability to have in their back pocket.


Chris Taylor Has Been Great, But Expect Him to Regress

This article is not intended to take anything away from Chris Taylor. He made a great adjustment by improving his launch angle to turn into a productive hitter. To become an above-average hitter at age 27 after being basically a AAAA/bench type of player is quite amazing and not many can do that.

However, I read a lot of articles treating him like a star, and objectively, he is this season, since a 126 wRC+ and 4.7 WAR from a middle infielder is amazing.

Yet there are some concerns with him. He has some pop and now hits the ball at a solid angle, but his K/BB is not great. his K percentage was 25% this year. That is not super high and he might even be able to shave off another percent or two, but don’t expect a big jump here at his age. His BB percentage was 8.8%, which is OK, but not great for a relatively high-K guy. Overall, his K-BB% is definitely below average (16.2% for him vs 13.1% league average).

So to become an average or better hitter, he needs above-average power. He did improve his game power by improving his launch angle; however, 20 HR is basically just above average in these days, and his exit velo also is just about average (87.0 for him vs 87.3 league average). So there is raw power but it is somewhat limited. Now with the modern ball, you don’t need great raw power to hit it out, as Murphy or Altuve show, but since his LA is already about optimized at around 12 degrees (maybe 1-2 degrees can be added but then it would eat into BABIP), there isn’t much room for growth. I think around 25 should be his ceiling. Now 25 is great for a middle infielder, and Murphy and Altuve became elite hitters by raising their HRs to the mid 20s, but those two guys have a much better K-BB than Taylor — both are around 4%, vs the mentioned 16% for Taylor. Taylor simply needs his 25 HR to even become an average hitter while Murphy and Altuve are basically average hitters with “no” power (say 8 HR or so) and anything above that is positive.

Using my K-BB-ISO stat, Taylor’s -0.05 was about average. What made him elite was mostly his .361 BABIP. Now BABIP is not all luck and he does have a relatively low pop-up rate, and he also pulled just 38% of the time, meaning he is not super susceptible to the shift, but still his 87 MPH exit velo and 32% hard-hit rate are not marks of super great batted-ball quality (about average). He did have a 22% LD rate which is above average, but not amazing either.

Now, he is not slow, so I would maybe give him a .310 BABIP, but even then he will drop off quite a bit.

The xwOBA stat supports that, as his was .331 (around league average) vs. his actual wOBA of .368.

My projection for him next year would be around a 105 wRC+ and maybe a .265 average. Again, that is amazing for a middle infielder who basically was a bench player a year ago, and he should be worth at least like 3 WAR or so, but I would not overpay for him in fantasy. He did improve a lot, but he is no Turner/Murphy/Altuve because he doesn’t have their contact ability.


A Whiff of Failure: The Texas Rangers and Rougned Odor

Rougned Odor had a disastrous 2017. Yes, he played all 162 games, which is not bad, and he hit 30 homers, which is not bad, but everything else was really, really bad. His slash line (.202/.254/.397) looks like that of an aging backup catcher. He was dead last in wRC+, behind even Jose Peraza. Behind even Dansby Swanson. Behind even Alcides Escobar, for God’s sake.

There have been 258 player-seasons where the player was in the lineup for all 162 national anthems. Odor’s was the eighth-worst as measured by bWAR (-0.2); in only 11 of these seasons did the player “achieve” a negative number. Most of these were either light-hitting middle infielders (players like Neifi Perez, the guy Alcides Escobar wanted to grow up to be) or aging diplodocuses (diplodocii?) like Pete Rose, still munching palm fronds (but no longer hitting much) at age 41. There are, however, two young power hitters among those 11, the 22-year old Ron Santo and the 25-year old Matt Kemp. Those with stock in Odor, Inc. will look to these seasons for inspiration, but they provide only limited hope.

Take Santo first. His poor 162-game season (at age 22) came a year after his first full year in the majors in 1961, a successful year in which he hit 23 homers, had an .841 OPS, and a wRC+ of 119. In 1962 Santo seemed to (very uncharacteristically) lose the plate. His walk rate dropped, his strikeout rate spiked, and his power plummeted. He hit only six fewer homers in 1962, but his ISO dropped by 60 points. (One can almost hear the retrograde Cubs coaches of the time telling Santo he needed to swing more and to stop being so patient.) The power would return in 1963, and the patience in 1964. Santo would never again have a walk rate below 10% until his depressing denouement with the White Sox in 1974.

Kemp’s career followed a somewhat similar path. The Bison had already assembled two effective offensive years before taking a long stride backward in 2009, his age-25 season. A far different player than the patient Santo, Kemp was always more of a close-eyes-and-swing-hard type, but the Ks really overwhelmed him in 2009, as his strikeout rate jumped almost 5% to 25.4%, the highest he would ever have in a fully healthy season. Some of Kemp’s retreat, however, could also be attributed to bad luck, however; he had the lowest BABIP of his career that year. And to be fair, other advanced metrics are not as harsh on him as bWAR — fWAR gave him a nice round zero that year, while his wRC+ checked in at 106, hardly encouraging for a supposed power-hitting outfielder, but hardly disastrous either. Kemp would go on the next season and win the MVP not win the MVP because Ryan Braun would — by assembling similar offensive rate stats as Kemp in 60 fewer plate appearances while playing poorer defense. With Kemp coming off a severely disappointing season and Braun not yet coming off his steroid exposure, this is perhaps more evidence that MVP awards are indeed path-dependent.

But I digress. The topic for today’s class is Rougned Odor, and one can see some similarities between his career track and those of the two power hitters just described. He’s coming off two solid years as a regular, and at age 23 is still young enough to turn things around and build a successful career. His team, i.e. the people who should know the most about him, thought enough of him to keep running him out there day after brutal day for the whole season, never benching him or sending him down. Chicks and everyone else dig the long ball, and like Santo and Kemp he’s clearly got that.

Not all the auguries are pleasant, however. Odor lacks even Kemp’s patience: his walk rate went up in 2017 to a still Rhode Island-sized 4.9%. Odor has the eighth-worst walk rate among active major leaguers. Odor’s career strikeout rate of 20.9% is better than Kemp’s, but his strikeouts ballooned to over 25% in 2017. Only Javier Baez, who recently filed a patent application on the letter “K”, had a higher rate among qualifying second basemen last year. This could be a good thing, though, in the sense that both Santo and Kemp had strikeout spikes during their bad years, which they both corrected, and Odor could too. Like Kemp, Odor also had a bad BABIP year, 50 points below his career number. Some of Odor’s next season, assuming he plays, will be a dead cat bounce; however bad Odor is, he’s almost certainly not as bad as the 2017 Odor.

But the lack of walks leaves him little room for error. And his minor-league track record is less impressive than those of Santo or Kemp, both of whom amassed an OPS of over .800 in the minors, and proceeded to do the same in the majors. Odor’s career minor-league OPS is .784, which is good but not great. Admittedly the statistical analogy is imperfect, but Whit Merrifield OPS’d at .784 in the majors at the keystone this year, good for ninth among second-base qualifiers. Advanced metrics yield a similar conclusion: Odor had a 106 wRC+ in his best season (in 2016). That’s Yangervis Solarte’s career mark, placing YS 16th among active second basemen. The signs, such as they are, don’t point to a Santovian, or even Kempian career, but rather a player whose upside is that of a first-division starter rather than an All-Star.

The Rangers would probably take that. They don’t have an obvious replacement for Odor at second, with Jurickson Profar’s career now a tire fire and Willie Calhoun apparently not fit for purpose at second. Hanser Alberto? No, probably not. Odor has shown he can strike out less, and indeed in the minors his strikeout to walk ratio was just a little over 2:1, much better than the 5:1 rate he’s shown at the majors, a rate that has washed out players like Wilin Rosario and Will Middlebrooks. If Odor can hold or build on his gain in patience (albeit from a very low base), lower the whiffs back to at least his career rate, and get some balls in play to go his way, he can return to his playable previous form.

And yet. It wasn’t long ago that the Rangers looked like a hotter, humider version of the Dodgers: a very good major-league team that could stay very good for a very long time by retooling on the fly rather than having to tank and rebuild. Remember these guys?

Baseball America’s Top 10 Rangers Prospects, 2012

  1. Jurickson Profar
  2. Martin Perez
  3. Mike Olt
  4. Leonys Martin
  5. Neil Ramirez
  6. Cody Buckel
  7. Jorge Alfaro
  8. Christian Villanueva
  9. Rougned Odor
  10. Matt West

To use a colloquialism I am given to understand is occasionally employed in Texas, that’s a lot of dry holes. Perez has become a serviceable league-average starter. They turned Alfaro (and most of what is now the Phillies farm system) into Cole Hamels. They gave Matt West the opportunity to explore the ancient and mysterious wonders of Japan. But that’s about it. Odor may yet break out and become a superstar — the Matt Kemp future is not completely out of reach. But the Rangers’ more achievable goal is to turn Odor into Yangervis Solarte. There are, to be fair, worse possible outcomes.

But, once upon a time, there were also better ones …


Embracing the Fly Ball Revolution

Baseball players are smart people. Over the past few years, they’ve figured out that ground balls are actually bad, so they stopped hitting them. Players like Yonder Alonso and Francisco Lindor started hitting more fly balls and, in turn, hit a lot more home runs. The entire league has caught on to this trend as well. In fact, as many of you may know, the MLB set a record this year, hitting 6105 home runs, nearly 500 more than the previous most in 2000. Now, this also has a lot to do with the fact that the ball may or may not juiced (which it more than likely is), but nevertheless, players have learned to adapt. Although the league FB% and GB% aren’t at extremes, it is very evident by the increase in home runs that the league has shifted towards a fly-ball mentality. Jeff Sullivan did a great breakdown of this earlier in the year, where he showed that the league-average exit velocities and launch angles and are all-time highs for the Statcast era. Players are making better contact at higher launch angles, and that’s something that the league has caught on to.

Players like the before-mentioned Alonso have changed their swings completely to full take advantage of the fly-ball revolution. Their swings prey on pitchers who throw low in the zone, and because of this, pitchers have adapted in turn. Teams like the Red Sox and the Rays have led the charge in throwing high fastballs, while pitchers like Trevor Bauer and Lance McCullers Jr. have started throwing a lot more breaking balls. The intention of this post isn’t to figure out what pitchers can change in order to succeed, but what pitchers already have the skillset to embrace the current fly-ball environment. For this search, I wanted to focus on a few different things: pitchers who already throw high fastballs, pitchers who give up a lot of fly balls and soft contact, and pitchers who induce the weakest contact according to Statcast.

The league-average fly-ball rate is 35.5% and the league-average hard-hit rate is 31.8%, so I looked for pitchers with a greater fly-ball rate and a lower hard-hit rate than the league average. As for the Statcast data, I looked for pitchers who induced the most pop-ups and fly balls who also induced the poorest contact on those balls put in play. Statcast also helped me find who threw the most fastballs up in the zone. I’ll list a few of the pitchers who have already embraced the fly ball and then go a little more in-depth on some guys who can look to break out in 2018 if they continue in their ways.

One name that immediately stuck out to me is Chris Sale, who has a case to win the American League Cy Young this year. Sale lives in the top of the zone and induces a ton of soft contact, but he also has the other dimension of striking literally everyone out and not giving up many home runs. Sale’s skillset makes him one of the best pitchers during the fly-ball revolution. Below him, there are a few more established names, like Ervin Santana, Marco Estrada, and Jeff Samardzija, a group of solid pitchers who strike out a decent number of batters, but not a ton, and also have some home-run problems. That being said, all of them had an fWAR of 2.9 or higher, proving them to be successful against opponents by learning to love the fly ball. The next few names that’ll get listed off are up and coming players who haven’t had much exposure and are still adjusting to the league. I’ll be giving a short profile for each.

Ariel Miranda

Now, I know what you’re thinking: Ariel Miranda is, in fact, a pretty bad pitcher. I’m not trying to say he’s good, but I’m saying there are some faint glimmers of potential here. Miranda is a 28-year-old lefty who found himself pitching in what was the Mariners’ desolate wasteland of a starting rotation in 2017. Due to a multitude of injuries, Miranda started 29 games for Seattle and was, in all reality, bad. This was mainly due to the fact that he allowed an egregious 2.08 HR/9, but thankfully, we know that home-run rate fluctuates from year to year. His over-inflated HR/9 is definitely caused in part by a 52.5% fly-ball rate and a fastball with a lot of rise, but Miranda never had a HR/9 over 1.0 in the minors, so there’s a chance he can rebound and use his ability to generate soft contact in the future. In 2017, he had a below-average hard-hit rate, and according to Statcast, 5.9% of his pitches resulted in weak, fly-ball contact.

Eduardo Rodriguez

After an impressive 2016, Eduardo Rodriguez continued to succeed in 2017 despite injury. In fact, he may be the most promising of this bunch. Although he has a lower fly-ball rate than Miranda and his opponents make better contact, his HR/9 is much better at 1.25. Rodriguez also strikes everyone out, showcasing 9.83 K/9 with great stuff, including a plus change. Rodriguez has already shown he can succeed in the league and it looks like he’ll continue to do so.

Reynaldo Lopez

Lopez was one of the key pieces in the Adam Eaton trade of last offseason. Lopez only pitched in 8 games last year for the White Sox, and although the stats weren’t super impressive, there’s a lot of reason to be optimistic. He throws very hard and throws 31.4% of his fastballs up in the zone, while also being in the upper echelon of creating weak contact. 6.78% of his pitches resulted in weak fly-ball contact, and Lopez also posted a great 27.8% hard-hit rate. If he can keep his control under wraps, while keeping the ball in the yard like he did last year, he could break out in 2018. The only thing that could be an issue are his strikeouts, but his numbers in the minors suggest those will catch up.

Ben Lively

I’ll be honest: I didn’t even know Ben Lively was a baseball player until a day ago. Lively surprised in 2017, coming basically out of nowhere and posting a pretty average year, but I don’t think a whole lot of people even saw that coming. He didn’t strike anyone out, but he also didn’t walk a whole lot of people, and did a decent job of keeping the ball in the yard. Lively also throws the ball up in the zone and gives up 44.2% fly balls. He’s probably the most vanilla out of all of these pitchers, but the fact that he gives up below-average hard contact (30.2%) means that he could continue to surprise in this environment.

Brock Stewart

As if the Dodgers didn’t have enough exciting young players, Brock Stewart is yet another electric arm with good velocity who came up as a starter, but also could profile as a reliever. Stewart was very good at limiting hard contact; only 22.5% of his hits resulted in hart contact. That being said, he didn’t throw up in the zone very often and gave up the lowest amount of fly balls at 40%, but his HR/9 was below average at 1.05. Now, it’s debatable whether or not Stewart is a true fly-ball pitcher, but his fly balls when he gets them are very weak, so I’ll give him a pass.

It will be interesting to see where these starters go in 2018, and whether or not these assumptions actually mean anything. It could be that they’re just bad, and that hitters will just crush everything that they throw. But, I like to think that if hitters have dramatically changed their swing planes to focus on low balls and are struggling to catch up to high pitches (and when they do, the ball is hit very softly), then maybe this group will have a chance. Baseball is a game of adaptation, and fortunately for these guys, their skillsets fit that adaptation, so it will be interesting to see what 2018 holds.


Kershaw Has a Problem That Isn’t Really a Problem

As one of the greatest pitchers of our generation, one might think that it is extremely unlikely that Clayton Kershaw would have what we would consider a ‘problem.’ As a seven-time All-Star, a three-time (potentially four-time) Cy Young winner, and an NL MVP, Kershaw has been the model of consistency over the past number of seasons, and as his career progressive ERA would dictate, he gets better each and every season. But if there were one knock on Kershaw, especially over the last season, he has been extremely prone to the long ball. His HR/9 rate in 2017 was 1.18, significantly higher than his previous high, which rang in at 0.92 in 2008. Between 2008 and 2017, the highest HR/9 during that span was 0.63 in 2012.

Also at a career high this season was his HR/FB rate. This season, he came in at 15.9%, compared to his previous career high, which also came in 2008, at 11.8%. So it wasn’t just an increased number of fly balls that led to his inflated HR/9, but as we can see with the high HR/FB rate, more of the fly balls hit left the yard.

Expanding on that even further, in his regular-season career, Kershaw has given up 128 home runs. Of those 128, 75 of them have been solo home runs (58.6%). This season, of the 23 home runs Kershaw surrendered, 15 of them were solo shots (65.2%). League-wide this season, of the 6105 home runs that were hit, 3495 were of the solo variety. This is 57.2%. Kershaw’s career average is on par with the major-league average, but this year, there is a significant spike in the percent of solo home runs that Kershaw gave up. Is this because Kershaw took it easy with the bases empty? Or because hitters have finally realized that stringing together three hits in an inning off of Kershaw can seem about as impossible as licking your elbow? (Real question is how many of you just tried to lick your elbow.)

Whether or not 2017 will turn out to be an outlier for Kershaw in terms of the home-run ball remains to be seen. Will hitters continue on the same trend, thinking that the long ball is the only way to beat Kershaw? Only time will tell. As for things we do know, while giving up the most home runs of his career, Kershaw still remained near the top of the list of best pitchers in the game. And while he missed six starts in July/August, he will still receive numerous Cy Young votes, although I predict he will come up short.

Kershaw, as proven last Thursday night in the Dodgers’ 11-1 rout of the Cubs to clinch the NL Pennant, remains terrific. The home run that Kershaw gave up to Kris Bryant was a cheap one. The ball was hit at 94mph, at a 32 degree launch angle. The expected average given that combination is an abysmal .136, and is a home run just 6% of the time (via Mike Petriello). Granted, not all home runs that Kershaw gives up are like that, but maybe Kershaw just ran into some bad luck this past season.

So given Kershaw’s resume, and the fact that he somehow finds a way to lower his career ERA each and every season, just how good could Kershaw be next year if he fixes his “problem?” The sky’s the limit, and if anyone could reach the sky, it would be Kershaw.


Assessing the Mets’ Catching Situation

In the middle of the 2017 season, it looked as though the New York Mets were in dire need of a serviceable catcher. Now, heading into the offseason, it looks as though the position will actually be one of their last priorities.

For the past four seasons, the Mets’ catchers have been led by the inconsistent and oft-injured Travis d’Arnaud. d’Arnaud was called up in 2013 and struggled mightily right out of the gate with a 60 wRC+, but figured things out a bit in 2014 when he played in 108 games while providing roughly league-average offense and an overall 1.3 WAR season. He had his best offensive season in 2015, but he missed a lot of time due to injuries, playing in only 67 games with an impressive 130 wRC+. 2016 was a down year for him as he played in only 75 games and had a down year at the plate. 2017 was the best year for him health-wise, as he set career highs in most counting stats. However, he had a mediocre and inconsistent year at the plate, and until August 19th, he was batting just .231/.279/.400 (76 wRC+). d’Arnaud was once a well-regarded prospect, but he seemed to molding into an inconsistent mediocre offensive catcher. And this doesn’t even include his struggles with throwing out runners.

And the problem was, there was nobody behind him who could do a serviceable job at catcher every day. d’Arnaud’s offense may have been underwhelming, but it was at least good enough to keep him in the lineup regularly. From 2014-2016, the Mets ranked 26th of the 30 teams in cumulative catcher wRC+ and 27th in cumulative catcher WAR. d’Arnaud was mediocre and oft-injured while the six other catchers who filled in for him in that time frame ranged from bad to downright awful. Five of those six were veteran backup/minor-league catchers who you shouldn’t have expected much from, but one of them was particularly disappointing, and that was former 2012 2nd round pick Kevin Plawecki. Like d’Arnaud, the Mets once viewed Plawecki as a potential future franchise catcher, and while Plawecki did prove to be better defensively than d’Arnaud, with a much better arm and better pitch-framing, his hitting was unfortunately pathetic, as in this three-year time span he collected 409 plate appearances and a terrible .211/.287/.285 batting line. Unsurprisingly, Plawecki also collected a lot of time in Triple-A during this time, and he continued to mash down in the hitter-friendly environment of Las Vegas, but he just could never things out with the bat at the major-league level.

Plawecki started the 2017 season in the majors, and through May 21 he collected 28 plate appearances and batted just .125/.214/.167. One noticeable thing about his offense despite his struggles was that he continued to post a pretty good walk rate of 8.2% and a surprisingly respectable 22.1% strikeout rate. His overall batting profile looked pretty mediocre, and his batted-ball direction profile was pretty even in terms of using all fields. The main problem for Plawecki was that he just wasn’t hitting the ball hard enough or hitting enough line drives.

Plawecki then spent a huge chunk of the season in Triple-A, where, as always, he hit really well, and then he returned on August 19th and completely turned things around. The sample size was still relatively small, but in the 90 plate appearances Plawecki had to close out the season, he hit .303/.411/.474, good for a 137 wRC+, and he did this while posting a fairly normal .333 BABIP. His walk rate went from good to great, as he walked 13.3% of the time while striking out only slightly more at 14.4% of the time. This is a manager’s dream nowadays, in an era where hitters are striking out more than ever, and Plawecki managed to do this while improving greatly in the contact he made, the quality of contact and most importantly, his power. Until his late-season turnaround, he had always had an ISO far below .100, which is awful, and he improved that mark to an above-average .170. Plawecki had finally converted his success in the minors to the majors, and it’s really impressive how he improved in every area of his game. He increased walks, decreased strikeouts, increased contact and increased power. Obviously he still has a little ways to go before he establishes himself as a reliable starting catcher, but if this hot streak proves to be more than just a fluke, Plawecki could actually blossom into one of the most well-rounded catchers in the game. The charts below show how significant and surprising Plawecki’s resurgence was.

Kevin Plawecki From 4/21/15 to 5/21/17

 Season  AVG  OBP  SLG  ISO  wRC+  BB%  K% PA
 2015  .219  .280  .296  .077  59  6.6  23.3  258
 2016  .197  .298  .265  .068  58  11.3  21.9  151
 2017  .125  .214  .167  .042  8  7.1  14.3  28

Kevin Plawecki from 8/19/17 to 10/1/17

 Season  AVG  OBP  SLG  ISO  wRC+  BB%  K%  PA
 2017  .303  .411  .474  .171  137  13.3  14.4  90

Relatively small sample size aside, this was still extremely encouraging of someone who was seemingly molding into a classic AAAA hitter and disappointing prospect. He looked like a completely different hitter when he came back, as he was more selective and had a quality at-bat seemingly every time he came to the plate. So all hope is in fact not lost for Kevin Plawecki.

But what’s just as notable about Plawecki’s hot streak is that it must have fired some competition into d’Arnaud, who turned his season around with an even hotter streak of his own in this time period. From when Plawecki returned from the minors, August 19th, until the end of the season, d’Arnaud slashed an impressive .297/.350/.571 (141 wRC+) after that bad start I mentioned earlier of only a 76 wRC+ until that point. Like Plawecki, d’Arnaud accomplished this new level with a sustainable BABIP (.279). Here’s a chart of what d’Arnaud did through August 19th vs. what he did after.

Travis d’Arnaud From 4/3/17 to 8/19/17

Season AVG OBP SLG ISO wRC+ BB% K% PA
2017  .226 .272  .397  .171  73  5.8  17.8  276

Travis d’Arnaud From 8/20/17 to 10/1/17

Season AVG OBP SLG ISO wRC+ BB% K% PA
2017  .297 .350  .571  .275  141  7.0  10.0  100

Like Plawecki, d’Arnaud began walking more, striking out less, and hitting for power, all extremely good signs. d’Arnaud is more of a power-hitting catcher than Plawecki, as he is below average in drawing walks, while Plawecki is more of an OBP-centered player who also happens to have an above-average amount of power with his big, muscular body type. If they can really use these tools to their full potentials like they did in their late-season surges, they can both be quality starting catchers or at the very least, one can be a solid backup for the other.

In addition to d’Arnaud and Plawecki, the Mets also have a catcher rising through their farm system to keep an eye on named Tomas Nido, an eighth-round pick in the 2012 draft (the same draft that Plawecki was picked in). Nido’s not a huge prospect, but the Mets are still excited and optimistic with him and believe that he has the tools to be a starting catcher. Nido is described by fangragsports.com as “a very strong and powerful catcher. He has an ideal frame to be a catcher in professional baseball.” The 23-year-old is 6’0′ and 210 lbs, so he has the frame and strength, but it is also mentioned that he has an aggressive approach at the plate and has a long swing that he uses to try and blast home runs, and scouts wish he could tame that swing a little to try and hit for a better average. Nido didn’t hit much in rookie ball or A-ball, but he hit very well in High-A ball in 2016 when he hit .320/.357/.429. Unfortunately, he didn’t make a great transition to Double-A this year, where he hit just .232/.287/.354. He got a late September call-up to the majors at the end of the season and got three hits in his first six at-bats before collecting a tough 0-4 day in the final game of the season, so he ultimately went 3-10 at the highest level. Nido is a good defensive catcher, and figures to spend all or most of 2018 in Triple-A Las Vegas, where hopefully the hitter-friendly environment will allow him to really find his swing and have a chance to produce at the major-league level. Nido has no one tool that overwhelms, but if he puts it all together he has a chance to be a solid major-league catcher.

Overall it seems as though the Mets have more depth at the catcher position than they realized if d’Arnaud and Plawecki’s late-season surges mean anything. d’Arnaud is an established mediocre starting catcher with potential for much more, while Plawecki and Nido are still yet to really establish themselves in the majors and are going to need a little more development before the Mets can commit to either one of them as a starting catcher. But these hot streaks and the continued development of Nido should leave Mets fans excited for the potential of a great major-league catching tandem. And due to this newly realized depth at the position, it would no longer make sense to spend money on someone like Jonathan Lucroy in free agency, as it may have made sense three months ago. At this point in Lucroy’s career, the extra money spent wouldn’t be worth the slight upgrade, or possibly even downgrade, of Lucroy compared to what they have now. What the Mets need to do next season is give both d’Arnaud and Plawecki a fair shot, and whoever hits more gets to play more, while keeping note of Nido’s development in case he is needed at the major-league level. But the Mets should feel fairly comfortable with their in-house catching options and it should be one of their last priorities heading into the 2017-2018 offseason.


The Fall of Troy Tulowitzki

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.