As I’d like to think I’m an aspiring sabermetrician, or saberist (as Mr. Tango uses), I decided to test my skills and explore this research question. How did starters, who had 25 or more starts in one season and an ERA of 6.00 or higher in their final 10 starts, perform in the following season? This explores whether past performance, regardless of intermediary performance, adequately predicts future performance. Mr. Tango proposed this question as a way to explore the concept of replacement level. From his blog: “These are players who are good enough to ride the bench, but lose some talent, or run into enough bad luck that you drop below ‘the [replacement level] line’.” Do these players bounce back to their previous levels of performance, or are they “replacement level” in perpetuity?

To explore this, I gathered game-level performance data for all starters from 2008 through 2017 from FanGraphs, grouped by season. I then filtered out pitchers who had fewer than 25 starts and had an ERA less than 6.00 in their final 10 starts. This left me with a sample of 78 starters from 2008 through 2016 (excluding 2017 as there is no next year data yet). I assumed that a starter with an ERA above 6.00 was at or below replacement level. Lastly, as some starters were converted to relievers in the following year, I adjusted the following year ERA according (assuming relievers average .7 runs over nine innings less than starters: see this thread).

Seems like the 10-game stretch to end each season is a bit of an aberration. The following year’s adjusted ERA is much closer to the first 15+ games than the final 10 games for pitchers in our sample. In fact, the largest difference between any first 15+ game ERA and its following year adjusted ERA is .58 runs, in 2011. The smallest difference between any last 10 games ERA and its following year adjusted ERA counterpart, for comparison, is 1.7 runs, in 2009.

Using adjusted ERA corrects for the potential slight downward bias in our following year totals. Following year games started fell by ~9%, while reliever innings increased from zero to each season’s value. Relievers, on average, have a lower ERA than starters. As mentioned above, I adjusted each season’s following year ERA by .3 runs per reliever inning pitched (my assumed difference in runs allowed between starters and relievers per inning pitched). Another source for potential downward bias is sample size – of the 78 pitchers who fit our sample qualifications, only 69 pitched in the majors the following season. A survivor bias could exist in that the better pitchers in the sample stayed pitching, while the worse pitchers weren’t signed by a team, took a season off or retired.

What is driving these final 10 game ERA spikes? It has been shown that pitchers don’t have much control over batted ball outcomes. Generally, it is assumed pitchers control home runs, strikeouts and walks – the basis of many defense-independent pitching stats. Changes in these three stats could explain what happens during our samples’ final 10 games. Looking at each stats’ rate per nine innings, however, would be misleading, as each season exhibits uniform change (such as the recent home run revolution, or the ever-growing increasing in strikeouts). I calculated three metrics for each subset (first 15+, last 10 and following year) to use in evaluation: HR/9–, K/9– and BB/9–. All three are similar to ERA– in interpretation – a value of 100 is league average, and lower values are better.

Further, not necessary math details: for example, a value of 90 would be read as the following. For HR/9– or BB/9–, a value of 90 means that subset’s HR/9 or BB/9 is 10% lower, or better, than league average.  For K/9–, a value of 90 means that the league average is 10% lower, or worse, than the subset’s K/9. To create these measures, I calculated HR/9, K/9 and BB/9 for each subset and normalized them to the league value for each season – including the next year’s value for the following year’s rates. Then, I normalized these ratios to 100. To do that, I divided HR/9 and BB/9 by the league averages and multiplied by 100. Because a higher K/9 is better (unlike HR/9 and BB/9), I had to divide the league average by K/9 and then multiply by 100, slightly changing its interpretation (as noted above).

As mentioned above, the issue of starters-turned-relievers within our sample likely influences our following year statistics. I was able to adjust the ERA, but I did not adjust the rate stats – HR/9, K/9 or BB/9 – as I have not seen research suggesting specific conversion rates between starters and relievers for these.

Interestingly, our sample of pitchers improved their K/9– across the three subsets, despite having fluctuating ERAs. They were below average, regardless, but improved relative to league average over time. Part of this could be calculation issues, as league K/9 fluctuates monthly, and I used season-level averages in calculations.

Both HR/9– and BB/9– drastically get worse during the 10 start end-of-season stretch. These clearly drive the ERA increase. In fact, despite seven of the nine seasons’ samples having better-than-average HR/9 in their first 15+ starts, every season’s sample has a much-worse-than-average HR/9 in their last 10 starts, where eight of the nine seasons’ samples HR/9 are 40%+ worse than league average. Likewise, though less drastically, our samples’ BB/9 are much worse than league average in the last 10 starts subset. Unlike HR/9–, though, our samples’ BB/9– is worse than league average in the first 15+ starts subset. The first 15+ games’ HR/9– and BB/9– are identical to the following year’s values, unlike K/9–.

It appears that starters with an ERA greater than or equal to 6.00 in their final 10 starts, assuming 25 or more starts in the season, generally return to close to their pre-collapse levels in the following year. This end of season collapse seems to be driven primarily by a drastic increase in home run rates allowed, coupled with an increase in walk rate. These pitchers performed at a replacement level (or worse) for a short period and bounced back soon after. Mr. Tango & Bobby Mueller, in their email chain (posted on Mr. Tango’s blog), acknowledge this conclusion: “they are paid 0.5 to 1.0 million$ above the baseline… At 4 to 8 MM$ per win, that’s probably an expectation of 0.1 wins to 0.2 wins.” We can debate the dollars per WAR, and therefore the expected wins, but one thing’s for sure – past performance is a better predictor of the future than most recent performance.

– tb

Special thanks to Mr. Tango for his motivation and adjusted ERA suggestion.

Roberto Osuna, the Blue Jays young star reliever, has put together a very impressive resume in his 3-year career. Last season Osuna ranked 3rd in RP WAR (3.0) only behind Craig Kimbrel and Kenley Jansen in his age 23 season, and has also posted the highest cumulative WAR among relievers aged 20-23 years old in the last 40 years, while also producing the 2nd best FIP (2.69) and the moves saves (95).

Last July, Jeff Sullivan wrote a very compelling and in-depth article into the pure dominance Osuna was displaying on the mound; he was having a near perfect start to his season. He showed that across the board, Osuna ranked in the top 90 or 95 percentile in all of the major pitching statistics, proving that he had put it all together – matching his control to his skills. A few weeks before Jeff published his article (around June 25th), Osuna had missed some time for personal reasons, which was later disclosed as time away from the team to deal with anxiety issues. Roberto showed great courage speaking out to the public about his own internal struggles, but it was soon after that announcement that Osuna began to struggle on the mound.

It is both a difficult and a delicate analysis to undertake when analyzing the changes to Roberto’s performance last season. It is important to not read too much into certain trends and extrapolate that these derive from mental rather than physical, mechanical or strategic changes; however, this article will explore these changes to see why he suddenly began to struggle and how Roberto can strive to regain his top form for his 2018 season and beyond.

Roberto was at the top of his game in May and June and was putting up ridiculous numbers every time he took the mound. From July onward, Osuna began throwing his cutter and sinker much more frequently and threw fewer four-seam fastballs and sliders, as shown below:

The increase in his FC and SI usage and decrease in his SL and FA usage resulted in a change in his batted ball profile and strikeout potential. Osuna has a devastating slider with one of the best chase rates and swinging strike percentages in the league. He moved away from this pitch in favor of his sinker, which resulted in a lot more groundballs, as shown below. This change affected his BABIP, as it rose from .269 to .298.

Further, the large increase in his cutter usage resulted in a lot more hard-hit balls and he began to use it more often in high leverage situations with runners on base. His cutter usage increased from 15.7% to 37.4% with runners on base and this led to a plummeting left on base percentage. Last season Osuna posted the 2nd worst LOB% in the league among relievers at 59.5%. This is a statistics that jump off the page when juxtaposed with his fellow elite relievers who post metrics above 80 or even 90 percent. Below we can see just how drastic the drop was for him.

Considering that his LOB% was such an outlier compared to his peers, it is important to delve further into how this occurred. Recent history shows how rare it is for a pitcher with such great skills and control to have such trouble with runners on base. Since 2000, there has only been one other reliever who had a FIP under 2.00 who had a lower LOB%. A contributing factor to his struggles with runners on base was his aforementioned change in pitch composition. Increased usage of his sinker increased his balls in play and BABIP, his increased usage of his cutter resulted in harder hit balls and his decreased slider usage decreased his strikeout rate at times where he needed it most. Before June 25th, Osuna had a 2.41 FIP, 29.4% strikeout rate, 0% walk rate and a .304 BABIP with runners on base. After his temporary absence, his FIP actually dropped to 2.02, despite striking out fewer batters (24.1%) and walking more batters (1.8%) but his BABIP increased to .378. His xwOBA of .274 versus his wOBA of .311 with runners on suggests that he got a bit unlucky in the second half of the season, so his high BABIP is likely a combination of poor pitch command or selection, poor defense behind him and bad luck on balls in play.

Osuna enjoyed such great success when getting ahead of hitters (.189 wOBA after 0-1) and especially with 2 strikes (.130 wOBA), that hitters began to be more aggressive earlier the count looking for something to hit hard. A combination of a loss in fastball velocity and poor pitch location, Osuna began to get hit harder in high leverage situations. The top two heatmaps are Osuna’s fastball location and the bottom two are for his cutter. The heatmaps on the left are before June 25th while the ones on the right are after June 25th.

Osuna began to leave his fastball up over the plate in a hittable spot, as opposed to up and in, where he could tie-up right-handed hitters and produce weak contact. His cutter went from a setup pitch or even a waste/chase pitch to a pitch that he threw for strikes. Since Osuna started to throw so many more cutters, of course, he had to throw more of them for strikes, but the problem was he was unable to command the pitch to the better areas of the zone. A likely reason why Osuna began throwing more cutters was because the drop in his fastball velocity, as it was losing its effectiveness.

Pete Walker the pitching coach for the Toronto Blue Jays recently discussed with reporters Roberto Osuna’s offseason and reflected on his 2017 season. He acknowledged that Osuna had a drop in velocity during the season, had some mechanical issues, which impacted his fastball command, and that perhaps he threw his cutter too often during stretches of the season. All of this can be backed up with stats. Both the Jays coaching staff and Osuna are aware of where he can improve to regain with elite form. Walker also alluded that perhaps Osuna’s off of the field issues had an impact on his performance last season. By interpreting some statistics through this lens we can see how it can appear that Osuna lost of a lot of his confidence on the mound, especially in high-stress situations.

In particular, Osuna struggled away from the Rogers Centre as his road ERA was 5.10 versus only 1.85 at home in 2017. Further, Osuna had the 2nd best home wOBA while on the road it was only ranked 48th best.

Osuna was still good in the 2nd half (1.80 FIP and 4.24 ERA) and overall had a great 2017 season, but when the pressure started to grow and the wheels started to spin, they usually fell off (i.e. on the road with runners on base). It is hard to say whether this is the result of a lack of confidence, his decreased velocity on his fastball and his subsequent increased usage of his cutter or if it was a bit of bad luck with runners on base. It is likely a combination of these factors that led to Osuna’s declining second half, but we shouldn’t forget how dominant he can be when he’s at his best. According to Walker, Osuna has put on some muscle this offseason to help him with his durability in maintaining fastball velocity. Just like for most if not all other pitchers, being able to command his fastball is pivotal to Osuna being successful. At the end of last season, Osuna saw a small up-tick in fastball velocity and retired all 15 batters he faced in his last 5 appearances of the season, which is an encouraging sign, but how will he handle adversity, when batters reach base in 2018? With some minor tweaking to his game, Osuna should be on track to bounce back and have another dominant season as the Blue Jays closer.

Spring is a time for optimism, in baseball and in life. Teams are starting to think about their opening day starters and more broadly, their starting rotations. Some rotations look “set” while some have a “battle for the 5th spot”. Some are toying with the idea of a 6-man rotation.

But here’s the thing: we know that (almost) every team will end up using a 6-man rotation, whether they like it or not. Eventually, your favorite team will need to call in reinforcements. This can happen because of poor performance or injury. But hey, we’ll cross that bridge when we come to it, right?

… when do you think we might come to it?

We know, as do those in charge that teams use something like 11 starters per year (in 2017: 11.3). In a six-month season, how long does it take before the first reinforcements arrive?

In a few words, not very long. Some pitchers have injuries, some get moved to the bullpen, some sent to the minors. Either way, at least one of them will be gone pretty soon, so don’t name the puppy.

Of course, fate comes at different paces. In 2017, the Cardinals didn’t use a sixth starter until June 13th. And even then, Marco Gonzales only pitched because they had a double-header. In contrast, Junior Guerra, the Brewers’ opening day starter, was injured that same opening day. He wouldn’t pitch in the majors for another seven weeks (and it turns out, not very well either).

Half of teams used a sixth starter before April 25th. 90% of teams used a sixth starter before their 50th game.

Some of those sixth starters, along with their full-season WAR: Alex Wood (3.4), Mat Latos (-0.3), Mike Clevinger (2.2), Mike Pelfrey (-1.0).

We know that teams need depth. Not only that, but life comes at you fast.

Data: Baseball Savant

There has been a lot of concern over Shohei Ohtani, and his rough spring training performance recently. Considering the hype he has come with, it is only natural for people to react as strongly as they have. Given his track record in the Nippon Professional Baseball League, and the presence of his impressive physical abilities, it is frustrating to see him struggle.

What must be considered more seriously, is the significance of the transition Ohtani is making. There has to be better recognition of his being human. He does not speak the language in a new country where customs, culture, and even life philosophies are often very different than back home in Japan. Based on the information available surrounding his appearances hitting, and pitching, it seems that this is simply a guy adjusting to his new life in the United States.

Also significant are the differences between the Baseballs,  such as the NPB ball that has higher seams, as well as the mounds in Japan that are softer than the contrastingly more solid mounds in Major League Baseball. These are factors affecting Ohtani, and his transition, that must be considered.

To begin, Ohtani’s pitching mechanics and delivery as a whole, seem to be somewhat different than they were in Japan. His approach and intentions have looked to be the same, but the execution has been slightly off. These gifs are slowed down to show the differences in Ohtani’s mechanics in Japan during the 2017 season, and 2018 in Spring training. Take a look at the location and execution of his fastball in said seasons:

2017 in Japan:

2018 Spring Training:

The key aspect to watch here is the contrast in the times it takes him to bring the ball to the plate. In real time, from the start of his throwing motion to when he releases the Baseball, Ohtani throws the ball in 1.8 seconds in 2017. In contrast, during his most recent Cactus League start in the second gif, he releases the ball in 2.2 seconds following the beginning of his throwing motion. Is he trying to reach back for more velocity this spring? His mechanics seem to indicate such a suggestion.

Looking at the freeze frame just after he releases the ball, Ohtani’s arm slot is higher on the left than on the right. Ohtani’s back foot is higher than it was previously. His whole body is slightly more upright, his arm is further behind his lower half, and he is not as balanced on the left in comparison with the frame on the right.

He does not drag his back foot on the mound anymore, the way he used to in Japan. This has caused him to have less balance in his delivery to the plate, which will be explained further later on. It is likely that Ohtani has no interest in sliding his foot across the harder mounds in the United States, which is clearly hindering the execution of his mechanics.

Furthermore, he is opening his body more in his pitching motion this spring, than he used to in Japan. Being more upright means that it’s harder for him to get on top of the Baseball, which makes it more difficult to keep the ball down in the zone when he wants to throw it there. Having his arm behind his lower half as seen on the left, is putting more unnecessary stress on it as well.

His balance point is off on the left, too – This makes it more difficult for him to sync his arm and lower half, as well as locate his pitches. Ohtani has better control of his body in the frame on the right, thus allowing him to have more fundamentally sound mechanics.

Often, when a pitcher is not fully finishing his delivery, he (Hopefully someday She!) is overthrowing. Ohtani has indicated that he feels hardly any anxiety surrounding his performance, however it seems that he may be pressing a little, based on the contrast between the mechanical execution of his delivery in Japan, and here in the United States.

The finish of the delivery with his back leg swinging up as it always does, is more pronounced and noticeably higher on the left than on the right. Given that the pitches were thrown to similar locations in both frames, this is likely an indicator of him putting more effort into his delivery:

His non-throwing arm and glove are much higher on the left, and his pitching arm is visible on the left while it is not on the right. His left arm is actually turned up-and-out in his pitching with the Angels, whereas in Japan his arm is folded inwards, and is much closer to his body. This is simply further evidence of his seemingly increased level of effort while pitching this spring.

There is also the possibility that he is hurt, as his change in mechanics would support, too. Maybe his elbow is not as healthy as it has been made out to be. Regardless of the cause, Ohtani is not himself at the moment.

What is interesting, is that the pace of his delivery has slowed, while also becoming more stiff and less explosive. The abilities are there for him to perform at a much higher level, and it would really help him to stay within himself more and execute the fundamental aspects of his delivery.

It is likely difficult for him to adjust to the mounds in the United States, which could be affecting his delivery and mechanics significantly. Above all else, it seems that this is a case of a 23 year-old acclimating to a completely new country and culture. He is learning countless new things about life here, and his poor performances this spring seem to be a reflection of the recent change in his life, more than anything else.

The most glaring issue in his pitching thus far, has been in his mechanics. The pitches he is throwing are objectively impressive, they just aren’t being placed where Ohtani wants them to be as a result of his delivery being out of sync. He is absolutely fine, and simply needs to make a few adjustments to get back to being the potentially dominant pitcher many envision.

Video in this piece was taken from MLB.com.

As I’m sure you know, Major League Baseball is toying with the idea of putting a runner on second base sometime around the 12th inning. While I’m not doing this to argue its validity or lack thereof, I’m going to discuss and evaluate some scenarios that could happen under those conditions. It won’t be anything groundbreaking; I’ll be demonstrating the metrics involved with a team under the various circumstances I induce.

The following scenarios are played out to score at least one run in a given inning. Top or bottom of the inning, I envisage the same sort of conditions will play out for both teams. And because there is never any telling what part of the order will start with this setup, I speak in generalizations.

I’ve thought about what would be the likeliest of moves under this arrangement and I’m going to guess it would come down to the most boring events in baseball; the offense bunts the runner to third or the pitcher intentionally walks the first batter attempting to set up the double play. Of course, there will be times when the managers decide to simply attack the situation as-is. That’s more of a volatile situation and therefore much harder to work with.

First, the basics. From 2010-2015, having a runner on second base with no one out produces the following:

• The predicted number of runs scored is 1.100
• The percent chance of scoring a run under those conditions is 61.4%

So from the get-go, the offense is expected to score a run in three out of every five chances.

Play the bunt or a standard defense?

Let’s start off with the first of two scenarios; the bunt to move the runner over to third. I feel like this is the most likely action but also the most difficult to work with because of varying defensive strategy. Will the defense make an anticipatory shift for a bunt or will they be in ‘straight up’ formation? In 2011, Bill James found out that bunting in sacrifice situations produced a .102 batting average. Not like we needed that because we could have guessed that you’re going to be out roughly 90% of the time.

To bunt or to swing away?

So assume the hitter lays down a bunt that moves the runner while making an out at first. Run expectancy is now 0.95 with a 66% chance of scoring a run. Your run expectancy went down 0.15 runs BUT you increase your chances of scoring by a little less than 5%. Would bunting make sense to you as a manager? Taking out any sacrifice-type contact, if your hitter produces an out and the runner has to stay at second, your run expectancy drops to 0.664 and the chance of scoring a run plummets to roughly 40%. Still feel the same way (regardless of the hitters bunting ability)?

Walk or pitch to the next hitter?

Keeping with the initial decision, we have a runner on third and one out. Pitch to the next hitter or put him on to set up the double play? Our strategy could be further altered because at this point the defense might be inclined to bring out a ground-ball pitcher or create a split situation (lefty vs lefty and vice versa). But again, let’s go with the assumption that the team will do the safest thing by having the next hitter walked. That puts runners on first and third with one out. That decision causes run expectancy to jump back up 0.18 to 1.13 and but the probability you’ll score at least one run drops to 63.4%. Would you make that same call (remember, we are in a vacuum)?

Runners on first and third with one out produce the following expectancy:

• Average number of runs scored is 1.130
• The chance of scoring a run under those conditions is 63%

One of a couple of outcomes will follow should you elect not to intentionally walk the hitter. He will drive in the run by putting the ball in play various ways (sacrifice fly, fielder’s choice, hit, etc) and accomplish what the offense set out to do; score at least once to put the pressure on the home team. Or, the hitter could strike out, ground out (which could turn into a double play, an out at home, etc) or fly out.  If contact is made, this could alter our base-out states: two outs and runners at various bases (first and third, second and third, second or first should the runner somehow get thrown out at home). Due to the randomness of contact in this event, we’ll stay with the intentional walk.

To bunt or to swing away, pt II?

So what about the offensive strategy for first and third, one out? The options are much more vast. You could sacrifice bunt to move a runner over to second (assuming the runner on third is held up), thereby dropping run expectancy to 0.580 and dropping your scoring chances to 26%. The risk here is having the batter somehow bunt into a double play; runner at third is tagged/thrown out and the batter is thrown out at first. Do you, as a manager, take the initial risk that set up this problem? It is challenging to turn a double play on a bunt but if the defense is ready, it makes it easier to do so.

This time, let’s assume the hitter botches the bunt to the first base side and the overeager runner is thrown out at home (or caught in a rundown), runner safe at first. Now, with two outs, there’s a runner on first and second, we sit at a very poor run expectancy of 0.429 and have just over a one in five chance of driving in that run.

Walk or pitch to the next hitter, pt. II?

At this point, again with neutral context, you can walk the batter to load the bases, (if the hitter is too good and the next isn’t great, etc.) or you can just pitch to the batter (maybe bringing in a bullpen specialist). Walking the batter gives the offense a 10%better chance of scoring and a .33 increase for run expectancy.

If you elect to pitch to the batter either the final out is made or runs score. Walking the batter loads the bases and forces the defense to hope for the best. The latter situation would actually produce the most excitement; a crucial decision would need to be made. Either way, my tangent baseball universe will end; three outs, inning over or the needed run(s) score.

While I don’t necessarily agree with or enjoy the thought of the game being altered in this way, it could produce some interesting strategical decisions and test the maneuvering skills of team managers.

This post and others like it can be found over at The Junkball Daily.

Let’s start off with a guessing game. Below are two players. Try to tell who they are.

So, who are they?

Maybe the title of this post helped you figure it out. They’re both Jonathan Lucroy. Player A is Lucroy in 2016, when he was worth more than four wins. Player B is him in 2017 when he was barely worth one win. But these two lines represent the same player in name only. In 2016 Lucroy was the most valuable catcher in the game. And then last year, he was the fourth-worst.

Moving down the chart above, one could reasonably tell Lucroy’s story. Maybe the difference on balls in play is what drove him from about 40% above league average at the plate to about 10% below league average. But that wasn’t just bad luck; his contact numbers probably justify the drop. Driving the ball with less authority means hitting more playable dinkers. That creates lower BABIP and wOBA. It’s also not going to help if you hit an additional 16% grounders from one year to the next, which Lucroy did, because, those playable dinkers are the worst playable dinkers a hitter could generate.

In some sense, catchers aren’t supposed to be as good as Lucroy has been in the past. Expecting him to stay that good forever would be silly. But so would expecting him to fall off the edge of a flat earth into the same relative nothingness as Martin Maldonado. Jeff Sullivan broke down Lucroy when he was traded to the Rockies last season and found that in addition to his offensive stats cratering, so had his previously excellent framing numbers. He went from being one of the game’s very best at stealing strikes to being one of its very worst. So maybe Father Time had simply claimed eminent domain instead of moving next door. 

The numbers bear out Lucroy’s fall as much as numbers can. But the same thing that makes them so endearing — their blindness — sometimes means they still aren’t telling the whole story. Below are two gifs. On top is Lucroy as a Brewer in 2016, driving a JC Ramirez fastball up the middle. Below is Lucroy as a Rockie in 2017, pulling off of a Ross Stripling slider.

Above, the Angels defense was presumably playing at double play depths, making a play up the middle more accessible, if still difficult. Thought it was a grounder from Lucroy, it was a screamer, coming off the bat at 100.7 mph (he averaged 87.6 in 2016). Below, Lucroy forced Corey Seager to make a bit of a play, but Seager was able to because the ball only came off Lucroy’s bat at 88.4 mph (he only averaged 85.1 last season). Both pitches were in the middle third of the plate. The swings are similar enough. But check out the stills below as the ball arrives at the plate.e.

In this picture, from when he was still a Brewer, Lucroy is very much in control. He’s square, and his body is getting ready to move together. All the MSPaint lines are moving in the same direction, showing that his kinetic chain is tuned up. That basically means his big muscles were ready to transfer power to his little muscles. The next frame shows it stayed that way. The swing is coming from his center of mass. Sure, he grounded out, but he was together. Groundouts happen.

But look at this still, from when Lucroy was a Rockie last year, and good grief. His body is moving in so many directions it looks like it’s in a traffic jam. His hands are going down and away, his hips are pulling in the other direction, and his legs are digging directly ahead. The kinetic chain is nowhere to be found, and Lucroy’s one body is effectively acting in three independent manners. Doing that on a regular basis would go a long way toward explaining his sudden inability to drive the ball, and how he lost 2.5 mph of exit velocity on average per batted ball. 

Lucroy’s legs being hurt, but not enough to sideline him to ensure they’re healed, could explain an inability to rely on his core to support his kinetic chain. However, per Statcast, his sprint times were nearly identical between 2016 and 2017. In fact, he was actually .2 seconds faster last year than the year before. But that’s only his legs. Maybe he had an issue with his core — a set of big muscles —  that kept his swing from staying in sync and glove from reacting as well when framing.

Baseball Savant only has so much video to examine. Lucroy’s broken kinetic chain in 2017 appears to be pretty consistent, though. And sure, these were different pitches, from different pitchers, with presumably different camera angles. I can’t tell you the ball was at the exact same distance from Lucroy in each instance. But a nagging injury influencing a mechanical flaw isn’t entirely implausible, even if speculative.

If Lucroy can smooth out his mechanics and is even half of what he used to be, that’s still twice as much as he was last year. Or maybe he did just fall off a cliff. But at one year and 6.5 million, it’s easy to understand why the A’s would want to find out. 

—

Mystery player data from FanGraphs. Gifs made with Giphy; videos from Statcast.

Now that most rosters have been finalized ahead of opening day, there can be more specific speculation as to how certain groups of players on teams will perform.

As the use of bullpens becomes more significant in baseball, it is increasingly important to consider their performance. The Yankee bullpen is looking fantastic, which is fairly obvious to most at this point in time. A bullpen that is especially intriguing heading into this season is that of the Padres. While the team is not expected to contend this season, their bullpen is lining up to be quite unique.

Outside of Brad Hand, this is a group of relievers hardly anyone has ever heard of. Either because they simply have not played in the Major Leagues at all prior to this year, or have had mediocre performances in their time at the Major League level, these guys seem pretty lackluster to the average person.

This begs the question: Could the Padres have a trio of relievers similarly dominant to that of the Yankees’ Aroldis Chapman, David Robertson, and Dellin Betances? The idea is ambitious, however, the trio of Brad Hand, Kazuhisa Makita, and Kirby Yates have shown themselves to have the potential to be just as good this season. These three are players who have immense potential as relievers, whose variety of arm angles, and styles of pitching could be set to give opposing hitters fits this summer.

The bullpen is obviously led by Brad Hand, who will be the Closer for the Padres – What makes him unique is that he throws a lot of innings, and truly doesn’t care whether he’s pitching the ninth, or the earlier innings of a game. This means he can be used in the most high-leverage situation of a game, which is the ideal way for relievers to be used, a-la-Andrew Miller in the 2016 postseason.

Padres manager Andy Green said of Hand: “I’ve never been around a pitcher that takes the ball as willingly and as often as he does.” Hand pitched 79.1 innings for the team in 2017 – 6th most among all relievers in Baseball and first among Closers. With 11.8 K/9 in that many innings, take a look at the slider that generated a 21.2% whiff rate in 2017:

He didn’t locate this slider very well, but even when left up in the zone, the pitch is objectively good enough that it can still usually generate whiffs.

New Japanese pitcher Kazuhisa Makita is also on board with the Padres, who was signed from the Saitama Seibu Lions of NPB. A submariner who releases the baseball six inches off the dirt, Makita is arguably the most interesting reliever in the Major Leagues this year. His fastball has topped out around 81 mph this spring, and he also throws a curveball that has been clocked as slowly as 52 mph, and usually sits 56-59 mph.

It is unprecedented for a pitcher to throw at such a lower velocity than is traditional in the Major Leagues, though his 2.83 career ERA in the NPB suggests he is a very capable pitcher. His pitches and pitching style are so unique, that watching them gives one a better understanding of his pitching than words could ever describe.

He’s especially adept at painting the outside corner:

It’s certainly a very different arm angle, and he looks to have pretty good command of his pitches.

Makita seems to often throw his fastball on the outside corner more than anywhere else, based on his pitching style in his appearances this spring.

Though Makita is legitimately unafraid of throwing his pitches to any part of the plate, notably pitching up in the zone at times as he does here:

It will be especially interesting to see if Makita generates a ton of pop-ups from hitters in front of, and under his often 81 mph Fastball in 2018.

What is even more fun, is Makita’s curveball, because of how slow it is. It has been described as “Bugs Bunny” and “Eephus Curve” among other names thus far. Thus far though, the pitch has played as well as any other pitchers’ Curveball.

Here is his curveball:

As far as how his stuff will translate to success in the Major Leagues, the Padres have been liberal in allowing Makita to pitch his own style. Backup catcher A.J. Ellis made echoed this sentiment nicely: “we just want to let that style translate here as opposed to making him fit into what we think he should be.” Makita is unlike any pitcher the League has seen in years, so it is encouraging that the team will give him the independence to continue to attack hitters as uniquely as he did in Japan.

Amid all the power relievers looking to often whiz the ball past hitters with velocity, Makita has the chance to finesse his way to success in the big leagues. In an era in which hitters continue to counter power pitching with higher launch angles, and fly-ball swings, Makita’s pitches that rise on hitters will require legitimate adjustments from them. He probably won’t strike out a lot of hitters, though he figures to be a guy who will generate a lot of weak contact.

There is no standard for this kind of a pitcher in the modern era throwing at such a low velocity, and maybe he just won’t throw hard enough to ever be very good. However, if his approach to pitching is successful, the Padres will have found a truly rare kind of dominant reliever.

Another member of the bullpen is Kirby Yates, who almost struck out 14 batters per nine innings last season. His 13.98 K/9 was 5th best among qualified Major League relievers, behind guys including Kenley Jansen, Dellin Betances, and Craig Kimbrel. Yates upped his Split-Change usage to 14.2% in August, and 25.6% in September, which helped him to a 14.6% K/9 rate in those months. He gave up 17 hits during that time, yet not a single one of them was on a changeup, according to Baseball Savant. His split-change had a 22% whiff rate last season, easily being the best swing-and-miss pitch in his repertoire. Here is the split-change in action this spring:

He also throws a high spin-rate fastball often up in the zone, which from his shorter arm slot was hard for hitters to make solid contact on last season. Yates ranked third in swinging strike rate, at 17.4% –  Among relievers who threw at least 50 innings last season, behind only Craig Kimbrel, and Kenley Jansen. With the increase in split-change usage, Yates could potentially take the next step as a reliever, and become even better than he was last season. Thus far, the results have been promising from a guy who was claimed off waivers from the Angels in 2017.

The three pitchers explored above, may not be likely to have the success they are sort of touted to have, as this article indicates. Especially in the case of Makita and Yates, people are not expecting them to be as good or comparable to Chapman, Robertson, and Betances. They probably aren’t going to be a three-headed monster, as the Padres hope.

Brad Hand is legitimately talented and should be recognized the way the members of the Yankees trio are. The point is that the other two pitchers have shown flashes of brilliance, in the case of Makita because of his unique style of pitching. Yates got hitters to swing and whiff at a level nearly as high as Craig Kimbrel, and Kenley Jansen.

Being a smaller market team, the Padres have to be more careful with their money than a team like the Yankees, who signed Robertson and Chapman to hefty free agent deals. Quietly San Diego might have found their own funky three-headed monster to anchor the late innings of their games this season. They’ve acquired and signed the aforementioned three relievers for a combined total of $7,145,833 in 2018 – The Yankees trio, in contrast, is due $38,100,000 in 2018 salaries according to Spotrac.

The team will never have the financial might of the Yankees, but they have shown a creative way to build a bullpen, that will be interesting to watch this season. Reliever performance is volatile, and the sentiment that these guys are nothing more than flashes in the pan is perfectly legitimate. What they have is a chance to be excellent relievers, and that chance is worth examining.

All Data used in the article was taken from MLB.com, Baseball Savant, Spotrac, and Brooks Baseball.

The tools hadn’t quite come together for Eddie Rosario until last year. Through his first two seasons, he had a penchant to swing often and at anything. While his power still made appearances, his overall line was diminished by his lack of selectivity at the plate, which resulted in far too many Ks compared to his bottom-of-the-barrel walk rate. In 2017, hitting coach James Rowson made note of Rosario’s focus on becoming an “all-around hitter,” and evidently, that had him heading in the right direction.

Part of becoming that kind of all-around hitter had to be closing the gap between his BB% and K%. After posting very poor BB% of 3.2% and 3.4% in his first couple seasons, Rosario made the jump to 5.9% last year and coupled that with a hefty decrease in Ks as well — from around 25% to 18.0%. And this was hardly a fluke. Rosario has swung less and less over his three seasons in the majors, and that decrease in Swing% has been due almost entirely to a decrease in O-Swing%.

He’s seen fewer first-pitch strikes whether by chance, by choice, or by pitchers respecting his talent a bit more, but regardless, what is most notable is his precipitous drop in O-Swing% and SwStr% with a steady Z-Swing%. Together, these stats suggest that Rosario made a distinct effort to recognize and lay off pitches he can’t do much with. While he has somewhat of a reputation for being a bad-ball hitter, Rosario seemed more committed to finding “his pitch” to swing at in 2017. Career highs in nearly every offensive category you can think of seem to set Rosario up for another fine year, but the sustainability of this progress relies on him leaving his old tendencies in the past.

With his new approach, Rosario was able to put his sneaky raw power on display. Per Baseball Savant, his xwOBA on all types of batted balls were more or less in line with his career norms. Only his flyball wOBA (.560) outpaced its xwOBA (.411) by a good margin. It’s fair to assume this means there is some regression baked in here, but in reviewing more than a handful of highlights, I noticed something particularly interesting.

In 2017, Rosario seemed to handle pitches up in the zone far better than he ever had previously. Clip after clip showed Rosario slamming up-and-away pitches to left field and handling pretty much anything else elevated. Referencing the gameday zones shown below, we can see just how well Rosario has hit elevated pitches over the years.

Given that we’re interested in how sustainable Rosario’s uptick in power is, let’s take a look at his flyball xwOBA in zones 1, 2, 3, 11, and 12.

Combining these zones, we can see the overall increase in xwOBA, and for good measure, I’ll lump his line drives from those zones in as well.

Whether the scope of this analysis is too narrow is up to the reader, but at the very least, the preceding data confirms my suspicions. The jump in xwOBA is a translation of exit velocity increases and more optimal launch angles, indicating that Rosario put much better swings on elevated pitches last year, and he was rightfully rewarded with by far the best power numbers of his career.

Checking out some Swing% heatmaps, we could infer why he had so much success on high-balls last year. The following heat maps are in order from 2015 to 2017.

Obviously, Rosario was quite the free swinger in 2015, but he quickly shied away from the outside part of the plate the following year. Perhaps focusing on the inside edge more wasn’t quite the remedy he was after, yet it seemed to represent a step in the right direction. He was more patient on outside pitches, and that trend expanded into greater selectivity more so than passivity in 2017 where he opened up those middle-away zones a little and became even more reluctant to offer at up-and-outside pitches.

Clearly, something was up with the way Rosario approached his at-bats. And with this newfound approach, he made more contact on both outside and elevated pitches.

Following the logic that if he can find “his pitch,” he can make more frequent, quality contact, it seems that better judgment around the edges of the zone over the past two years has started to transform Rosario’s approach from purely aggressive to selective aggressive. We know he has the power to muscle the ball around a bit, and we know his bat-to-ball skill is great too; his success is largely just a matter of swinging at the right pitches instead of swinging at everything. Rosario wanted to be more of all-around hitter, and that’s exactly what he did.

A slow start to spring training (only 7 games and 20 PA so far) might have him showing some rust early on this season, but if he can maintain his approach, Rosario can sustain his above-average offensive performance in 2018. Actually, he must maintain this approach to remain productive. With large steps forward in BB%, K%, and HR/FB% namely, he demonstrated a clear departure from his earlier days, but if he regresses in those areas, he could dip below 100 wRC+ again.

In fact, if we take his 2017 BB% from 5.9% down to 4.5%, his K% from 18.0% up to 21.2% (league average), and his HR/FB from 16.4% down to 13.8% (league average), we get the following 2017 output for Rosario:

Veritable skills don’t evaporate overnight, and you don’t massively improve your plate discipline stats by accident so I wouldn’t expect to see such a steep decline in production from Rosario in 2018, but it’s important to note that those modified rate stats would still represent career-bests for him. This “What If?” stat line simply highlights how important maintaining his 2017 approach will be for him this year. There is plenty potential for Rosario to post another .800+ OPS season as a selective, high-ball hitter, but his track record suggests the bottom could fall out if pitchers can effectively force him out of this new comfort zone.

At the beginning of February, Travis Sawchik wrote a piece about the viability of a team consisting entirely of unsigned free agents. I enjoyed the exercise as it underscored the extent to which players had been waiting to sign deals. Even that late in the year it was easy to field a competitive team, albeit an expensive one. Free agency is always considered to be more expensive than a homegrown team, hence the reason small market teams have to trade free agency bound players and retool, so it was no surprise that to create a decent team, the payroll had to be exorbitant. If you assume one WAR is worth $8-9 million dollars, then you would predict a 40 WAR team to cost over $300 million dollars in payroll. Sawchik’s team ended up costing $245 million dollars for the first year and was projected for 37.1 wins above replacement. While this was good for only $6.6 million dollars per WAR, it would still be the most expensive team in baseball and have to fight to stay in the wild-card race.

At the time I thought this was a good reminder of why the offseason was so slow; it just didn’t make sense for teams to meet players contract demands when it was so inefficient. In the following weeks though, players started signing at a faster rate, and again and again, I was taken aback by how little they were receiving. The $4 million dollar contract for Neil Walker was the most surprising of all for me. With seven straight seasons of at least 2 WAR and no qualifying offer, it seemed obvious to me that he deserved considerably more this. If you were to plug one year of Neil Walker into the surplus value calculators that Dave Cameron used to commonly employ, it estimates that Walker has $16 million in value for 2018, this is nowhere near what he ended up receiving.

Because of this, I decided to do a different spin on Sawchik’s team building exercise, using the contracts players actually signed, as opposed to projected contracts. Here is the team I came up with:

Team of Signed Free Agents

As you can see, the result of this team is much more successful than the team using projected contracts. I managed to stay under the luxury tax threshold ($197 million minus $13 million projected for player benefits) while creating a team that would be eighth in major league baseball in projected WAR just ahead of the Cardinals and behind the Nationals. Think about that, a team with no prospects, no homegrown players, and no assets to trade from could create a competitive baseball team from scratch through one year of free agency. And the team isn’t completely sacrificing its future either, as only four of the contracts are for more than three years. I can’t stress enough how surprising this is.

Instead of showing that free agency is completely inefficient for teams, this shows how easy it would be for a team to be projected for a playoff spot in the year’s offseason. Adding even a couple homegrown players, which every team has would boost this team into the ranks of other division leaders. So why is this the case? How was an entire team of free agents created for $4.2 million dollars per projected WAR? What happened to the accepted value of $8-9 million dollars per WAR?

I found both of these questions kind of perplexing since I could not find a good reason why the price of a win had dropped so quickly, but I decided to compare some of the most surprising contracts with similar players who were traded, and what the return was. All of the following free agents received considerably less than expected salaries based on their projected WAR and the following traded players were traded this offseason and have played a similar position and projection to the selected free agents.

Selection of Signed Free Agents

Selection of Traded Players

While these are only specific examples, all three comparisons, between Longoria and Moustakas or Fraizer, between Gordon and Gomez, and between Walker and Solarte, show a higher value placed on traded players than on free agent ones. Even with Longoria’s $68 million owed, he still returned three prospects in a trade. The Rays did take on Denard Span’s contract, but this salary dump was made up for by Arroyo alone, who is worth $20.2 million according to the Updated Version of MLB Prospect Surplus Values. Despite this, Moustakas received a tenth of the guaranteed money, and Frazier, who didn’t have a qualifying offer, a quarter of Longoria’s contract. So while Longoria had surplus value in a trade to the Giants, Frazier, and Moustakas, whose projections are very close to Longoria’s, couldn’t get anything close to his contract.

Similar situations occur with the other two comparisons. Dee Gordon was worth two prospects in surplus value, but Carlos Gomez, who is only projected to be a half-win worse, couldn’t even get 15% of Gordon’s guaranteed money. Also, the Blue Jays traded two prospects for Solarte this winter, even though he is making slightly more money than Neil Walker, and is projected to be only half as valuable. These both seem to be huge gaps between the value on the trade market, and value on the free agent market.

Then there is Jonathan Lucroy. While there were no significant catcher trades this offseason, comparing Lucroy’s Fangraphs projection to his contract is absurd.He has the fourth highest projected WAR for catchers in all of baseball, meaning that 27 teams could have upgraded by signing him, and yet he received $6.5 million. Granted, this projection seems high, but it’s easy to forget that two years ago he was a 4.6 win player. It seems to me that he would be worth much more than $6.5 million.

It is hard to know what all of this means. Do our WAR models overestimate mid-level talent? Do teams have projections very different from what is in the public sphere? Does it really have a lot to do with what teams think they can do with a player as opposed to their present value as was brought in a recent piece by Jeff Sullivan? Was the $8-9 million per win phase really just a contract bubble that has burst? While it is true that the gap in value between trade candidates and free agents is what you would expect if there were to be collusion from general managers, I think there is little other evidence of that, but it is still confusing why some player values seem to have dropped so quickly when compared to previous markets. I feel like I have brought up more questions than I have answered, but one thing is clear to me. If the trends from this offseason continue, looking to free agency for mid-level players will be much more efficient than it once was for teams. It seems unlikely that contracts for these types of players stay this low, however, since as any economics textbook can tell you, demand drives the price up. I would guess that plenty of teams will once again realize the value of Neil Walker for $4 million a year in the coming weeks, months and years ahead.

In July of 2013, Jose Altuve agreed to a four-year contract extension with two club options for the 2018 and 2019 seasons that guaranteed $12.5 million and a $750,000 signing bonus. Now that the Astros have picked up the club option at $6 million for the 2018 season and will pick up the club option at $6.5 million for the 2019 season, the deal will end up totaling 6 years for $25.075 million (this figure includes $75,000 accrued in incentives). What is important to note about this extension is that the deal bought out all three of Altuve’s arbitration eligible years (2015-2017) at $2.5, $3.5, and $4.5 million respectively and through the club options, controls his first two years of free agency.

In 2013, Altuve was following a 2012 All-Star campaign where he slashed .290/.340/.740. However, at the time the deal was signed on July 13, 2013, Altuve had seemed to regress slightly hitting .280/.317/.671 through 86 games. Following the 2013 season, Altuve’s stock soared, culminating in an MVP 2017 when he led the majors with an 8.3 WAR.

(Image from sportingnews.com)

Looking back on this contract, the deal obviously resulted in a large team surplus; however, contracts like this have had mixed results in the past (think Allen Craig) so I must stress that the point of this article is not to bash Altuve for signing the deal or laud Jeff Luhnow and the Astros for getting this deal done when they did. The point of this article is, if we hold Altuve’s past performance constant, had Altuve not signed this extension and instead had gone the more traditional route of going through three years of arbitration then hitting free agency, how much could he have expected to make along the way? Although I could see this article going in many different directions, such as trying to assess the level of risk Altuve signed away in July of 2013 or, in a similar way, trying to quantify the amount of the risk the Astros took on by signing the deal (this risk is definitely magnified due to the fact they started the 2013 season with a payroll of just $22 million), I believe knowing what transpired over the last 6 years, calculating the surplus on this deal is that most interesting way to proceed.

For the purpose of this article, I am assuming that Altuve worked on one-year contracts through the 2017 season when he would have hit free agency. I am also assuming that during each arbitration year, any of the three possible arbitration outcomes (player victory, team victory, or prior settlement before a hearing) could have occurred. To assist in keeping track of the many numbers presented in the remainder of this article, I have prepared the following table:

2013/2014 Offseason

Since Altuve would have been under team control, 2014 is the easiest season to estimate surplus and was clearly the most player-friendly year for Altuve. During 2014, Altuve’s salary jumped from the $510,000 he most likely would have received under team control to a $1.25 million base salary plus a $750,000 signing bonus and $25,000 in incentives. Hence, during the 2014 season, Altuve saw approximately $1.515 million dollars in surplus on this deal. For a player under team control, this number is pretty much unheard of, however, after 2014 is where the deal’s problems started.

2014/2015 Offseason

The 2014 season was clearly a breakout campaign for Altuve who hit .341/.377/.830 with 56 stolen bases and 225 hits. Since we are talking about his first arbitration-eligible offseason, it is important to keep in mind that Altuve’s .341 batting average and 225 hits both led the league. These more traditional statistics may not impress the sabermetrically savvy readers of FanGraphs, but the truth of the matter is that arbitration salaries are still very much reliant on these traditional metrics.

In the 2014/2015 offseason the largest contracts awarded to hitters who were arbitration eligible for the first time were Chris Carter ($4.175 million), Trevor Plouffe ($4.8 million), and Dayan Viciedo ($4.4 million; however, Viciedo was released at the end of Spring Training of 2015). None of these players are great comps for Altuve who only hit 7 home runs in 2014; however, they clearly set the market for top first-time arbitration eligible hitters. While someone like Carter may have hit 37 home runs and used this traditional measure of player value to push his deal up, Altuve did smack 47 doubles during the 2014 campaign and actually had an OPS that was 31 points higher than Carter’s (.830 vs. .799). I think a fair claim to make from this is that both sides would have seen tremendous value from Altuve and my estimate of a $5.0 million salary for a first-time arbitration eligible player is fair. This gives the Astros $2.475 million in surplus on the 2015 contract for Altuve who in reality received $2.5 million and $25,000 in awarded incentives. This changes the tide and brings the total surplus of the contract through 2015 at $960,000 in favor of the Astros.

2015/2016 Offseason

In 2015 Altuve was named to his third All-Star team and continued to impress, leading the league in hits and stolen bases for the second year in a row on his way to finishing in the top ten in MVP voting and winning a Gold Glove Award at second base. During the second year of arbitration salaries tend to jump up a lot, so after backing up his 2014 campaign with an even stronger 2015 season, a fair estimate for his 2016 salary is $11 million. Now, since Altuve ended up earning $3.525 million in 2016, assuming the $11 million salary is correct, the Astros’ surplus in 2016 was $7.475 million, making the total surplus of the deal through 2016 $8.435 million in favor of the Astros.

2016/2017 Offseason

I’m sure this will come as no surprise that Altuve backed up his All-Star 2015 campaign by leading the league in batting, increasing his home run total to 24, and finishing third in 2016 MVP voting. These are exactly the type of numbers that jump out of a presentation to an arbiter and due to the precedent of great value placed on high impact position players in their third year of arbitration, it is fair to assume that the 2016/2017 market would have been high on Altuve. Further evidence of this fact can be found in the 2017/2018 market that saw Josh Donaldson set the arbitration record by reaching a 2018 salary of $23 million. In addition, Bryce Harper settled on a 2018 salary of $21.625 million in May of 2017 after coming off a massive step back in production from 2015 to 2016 that saw him hit 18 fewer home runs and his on-base percentage to drop 87 points (Harper did rebound strongly during the beginning of 2017 right before this deal was signed). For these reasons, it is safe to assume that Altuve could easily have expected a 2017 salary of $20 million, leaving $15.5 million in team surplus and totaling $23.935 million in the deal.

2017/2018 Offseason: Free Agency!

Finally, a lot has been made over the free agent market this year, but the fact of the matter is that this past offseason Altuve would have been a 27-year-old reigning AL MVP hitting free agency. If the 5 year 151 million dollar extension he signed yesterday is any indication of the deal he would have received, I think 8 years at $225 million paying $23 million in 2018 and $25 million in 2019 is a conservative estimate. Based solely off this past year’s market, people may scoff at the length and dollar value of this deal, but the comparison of what Altuve’s situation would have been to the situations of this year’s free agent class are not strong due to the fact that the three main reasons this class struggled, do not pertain to Altuve. The first reason this past year’s free agent class struggled is that teams now have a better understanding of how players age and are not offering long contracts to players hitting free agency at 29 or 30 years old anymore. The second reason is that not enough teams are trying to compete for a playoff spot in 2018 due to the many rebuilds that are taking place. Because of this fact, there were fewer teams in the market submitting bids and driving up prices. The third reason is that lower WAR players who excel at putting up big numbers in traditional statistics like home runs (i.e Mike Moustakas) are finally being more fairly valued.

Being one of top players in the league at just 27 years old Altuve would have faced none of these problems even if only one team (say Milwaukee) had competed with the reigning World Champion Houston Astros to sign Altuve. The presence of just one other team in the market would have been enough to drive up the price making the Astros not afraid to pull the trigger on this big deal.

For the purpose of this article, the only two years we are worried about are the first two years (2018-2019), which are covered under Altuve’s actual contract at $6 million and $6.5 million. Thus, the Astros will receive $17,000,000 in surplus in 2018 and $18,500,000 in surplus in 2019, totaling $59,435,000 in surplus during the length of this 6-year contract. Talk about a team friendly deal!

(Image from clickhole.com)

Lastly, a quick note on what transpired yesterday. In my opinion, Altuve signing his second extension is a double down on the risk-averse behavior he first exhibited in 2013. Had he waited the two years until his current deal expired and hit free agency at age 29, teams once again may have shown the pattern of this past offseason and may not have been willing to give a 29-year-old more than a 5-year deal. Thus, Altuve’s contract way back in 2013 may have dealt his hand yesterday and forced him to sign this contract. The 2013 team friendly deal once again works perfectly for the Astros who were able to extend Altuve for five years while getting to take him off the books by his age 34 season.

The details on player contracts were taken from spotrac.com.