The Cubs won the 2016 World Series. Though that hopefully isn’t news to anyone, it is still interesting for a variety of reasons. Notably, it was the Cubs’ first World Championship since 1908. I have nothing new or interesting to add to the conversation about the Cubs’ accomplishment. The reason I want to talk about the Cubs now is because not only are they World Champions, they were also clearly the best team in the MLB this year.

Most fans recognize that those two statements are saying vastly different things. The Cubs won more games in 2016 than any other team, had the greatest run differential and had the highest team WAR total, so it is fairly safe to say that they were, in fact, the best team in 2016. But in 21 seasons from 1995-2015 (wild-card era) the team with the best regular-season record (or tied) has only won the World Series four times: the Red Sox in 2007 and 2013 and the Yankees in 1998 and 2009. That’s a 19% success rate. Also since 1995 only three teams that have led the major leagues in team WAR have won the World Series: again the 2007 Red Sox and 2009 Yankees, and also the 2010 Giants. That’s 14%. So that raises the question: is this a problem? Should the World Series champion more frequently be the best regular-season team? Should MLB change things to fix this problem?

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With the offseason in full swing, there are a number of contenders looking to fill their vacancies at catcher. After surveying the market, the most common names featured have been Brian McCann and an injured Wilson Ramos. After that, you hear rumblings of the Athletics dangling Stephen Vogt and another exercise in how teams value pitch-framing with Jason Castro. There is a player, however, I feel is being overlooked and could provide value to a contender. Alex Avila isn’t the sexiest name on the free-agent market but could be a sleeper candidate for a team willing to roll the dice.

When combing through the free-agent leaderboards, I discovered a couple of interesting data points that show how Avila could break through with the bat. First, I calculated “Good Contact %” by adding together Medium and Hard Contact %. Alex Avila was the leader at 91.3%. Other notable players on this list include Justin Turner, fifth at 87.9%, and the recently-signed Kendrys Morales, seventh at 87.2%.

So we have a 29-year-old left-handed-hitting catcher who makes good contact and plays the toughest position on the defensive spectrum. So why isn’t there more chatter about Alex Avila? The two biggest culprits lying in the stat line would be his groundball and strikeout tendencies. In 2016, Avila ran a 52% groundball rate and a 37% strikeout rate. Even then, Avila still managed to produce a 104 wRC+ which, given the low bar for catchers, is excellent. Diving into Statcast, we find that Avila had an average exit velocity of 92 MPH, which groups him in the same bucket as J.D. Martinez and Chris Davis. The disclaimer here is Martinez and Davis had over 300 batted balls and Avila had fewer than 100.

This is where there may be hidden value waiting to be unlocked. Avila has an average launch angle of 7.5 degrees, which is suboptimal for a slow-footed catcher. Given his exit velocity, if he could increase his average launch angle into the 15-30 degree range he could exponentially improve his offensive production. If he shifted his approach to drive balls in the air to his pull side, he could unlock additional power and maximize the contact he does make. Last season, Avila ran a pull percentage of 38%. Given his left-handedness and groundball tendencies, he is easily shiftable, which depresses the value of his bat. Avila only managed to hit seven homers last year, but with an offseason to work on a change in approach, I firmly believe he could unlock additional power.

Avila would definitely benefit from being the strong side of a catching platoon. If I am Dan Duquette and the Baltimore Orioles, I am moving to sign Avila to be the strong side of a catching platoon in hopes he could undergo a Trumbo-esque transformation by maximizing contact in a hitter-friendly environment. At present, Steamer projects Avila for 1.2 WAR in 2017, which on the open market should garner a commitment of just under $10 million on a one-year deal. If nothing changes, Avila can still be a serviceable option in a platoon, but if these changes were to take hold, we could be looking at the steal of the offseason.

The National League Cy Young Award race is looking like it is going to be closer than the 2016 presidential election. Kyle Hendricks has the sparkling ERA and solid peripherals while Max Scherzer has the sexy strikeouts and the innings pitched of a workhorse. Jon Lester, meanwhile, was the ace of the Cubs and got the first start over Hendricks in the playoffs despite having slightly worse numbers because of his reputation as a big-game pitcher. All three candidates are deserving and have a legitimate chance to win the election; let’s just hope the 30 voters all show up.

With starters getting the hook quicker and quicker over the past few years, pitching is increasingly becoming a race to the bullpen rather than a one-pitcher marathon. In light of this, we’re going to compare these pitchers through their first five innings pitched each start. This will show how the pitchers pitched while they were at their peaks in each game rather than while they were tired or overworked from being left in too long. In theory, this should give a statistical boost to Max Scherzer because his manager Dusty Baker is notorious for leaving starters in too long (see 2003 Cubs pitchers). Scherzer and Lester should also get a slight edge because Hendricks was given a pretty short leash this year. He has not had to pitch under excessive conditions as often as Scherzer or Lester have.

Through innings 1-5 this year, the edge actually ends up going to Kyle Hendricks with the lower FIP, HR/9, wOBA, and a sparkling 1.68 ERA. Although Scherzer has that ugly 1.12 HR/9, it is mainly due to the high number of fly balls given up. The 47.2% of automatic outs via pop-outs and strikeouts should allow him to continue as one of the best pitchers in the NL for a couple more years. Lester hangs in with solid numbers across the board, although his FIP and xFIP are the highest of the group.

After the fifth inning this year, Hendricks really hit a wall, supporting a 3.87 FIP and 4.17 xFIP. Scherzer takes a small hit overall but still pitches at a Cy Young level late in the game. Lester continues to pitch solidly as well, although the 2.26 ERA is suspiciously low considering his 3.63 FIP in the late innings. Hendricks’ poor performances after the fifth inning help explain why Joe Madden decided to go with Lester in Game 7 of the World Series in the fifth inning against the Indians rather than Hendricks. Although the playoffs do not count towards Cy Young voting, the fact that Maddon brought in Lester on short rest because he did not trust Hendricks in the biggest game of the year shows how cautious Maddon has been with his ERA-title winner in late-game situations this year.

Another thing to consider is that Lester and Scherzer are considered the “aces” of the staff. They know going into each game that they are expected to pitch to the seventh, eighth, or ninth inning. They have to pace themselves while Hendricks has the luxury to empty his tank through five and allow the bullpen to close out the contest. Or, since each pitcher threw under 60 innings after the fifth, this may be like the presidential polls and is just too small of a sample size to matter.

Before we decide who should ultimately serve the one-year term as the National League Cy Young Award winner, we should look at one more thing. The Cubs defense. Yes, Hendricks has a great GB% and is fantastic at limiting contact, as his adjusted contact score is 75 (Lester and Scherzer are 88 and 92 respectively). However, Hendricks and Lester had one of the best defenses to ever be assembled behind them doing work on all the balls in play. The Cubs as a team allowed a .255 BABIP, which is .042 points better than average and .033 points better than the Nationals. Their FIP-ERA gap is 0.62 while the Nationals are right around league average with an FIP 0.06 higher than the team ERA. So, while Hendricks and Lester both had a hell of a season with 2.13 and 2.44 ERAs respectively, the top-notch defense the Cubs deployed behind them deserves a lot of the credit.

If I had to pick who I thought deserves the Cy Young award, I would pick Scherzer, followed closely by Hendricks. Through the first five innings of games, his FIP is comparable to Hendricks’, so it comes down to whether I would take the longevity of Scherzer, or the contact management of Hendricks. While the 75 adjusted contact score is fantastic, he doesn’t quite get to the 1.07 gap in FIP-ERA without fantastic fielders and a little luck behind him. Scherzer threw the most innings in the NL this year and was the undeniable ace of the Nationals’ staff. The two Cubs pitchers may lose the Cy Young race, but they will be just fine with the hardware that they already earned this year.

The case for never letting pitchers bat in the NL has just gotten a whole lot better. I now estimate that if a NL team were to always pinch-hit for their pitchers they would expect to pick up a whopping 7.2 wins per year. And that, my friends, is a game-changer.

In my initial post two weeks ago I laid out a strategy in which a National League manager pinch-hits for his pitchers every time their turns come up in the batting order. I called it the “Pitchers Never Bat” strategy. The manager would keep a pitching staff of 11 “relievers” and no “starters.” The major benefit of doing this, I estimated, would be an improvement in the team’s offense.

I addressed what I considered the two major “components” of the analysis and estimated that the impact of this strategy was worth an extra 3.6 wins per year if the team was the only team in the National League to implement it. I also identified four other components of the analysis that could possibly add to, or take away from, my initial estimate of 3.6 wins per year.

In this follow-up post I will do two things. First, I will make some improvements by estimating the impact of two of the four components that I previously left unaddressed. And second, I will address some concerns raised by some members of the FanGraphs community via their thoughtful comments on my initial post.

Here is where I left off at the end of my original post:

Estimated Change in Wins Per Year by Component –

Component #1:   +3.6

Change in Runs due to pinch hitters batting for all pitchers

Component #2:   +0.0

Change in Runs Allowed due to using pitching staff in a new way

Component #3: Not Evaluated

Change in Runs Allowed due to added flexibility in selecting pitchers based on how they are warming up prior to or during a game

Component #4: Not evaluated

Change in Runs Allowed due to opponents’ inability to “stack the lineup” to take advantage of the starting pitchers “handedness” (i.e., lefty or righty)

Component #5: Not evaluated

Change due to reducing size of pitching staff by 1-2 men

Component #6: Not evaluated

Change in Runs Allowed due to the “times through the order” effect

TOTAL:                +3.6 Wins per Year

IMPROVEMENTS

So now, let’s make some improvements to the prior analysis. Here, I’m going to add estimates for the impacts of Components #4 and #6:

Component #4 – Handedness

In my “Pitchers Never Bat” strategy, the starting pitcher leaves the game when his turn in the batting order comes up, as a pinch-hitter takes his place. In this approach the starting pitcher will typically throw 1-3 innings, averaging two innings per start. Compare this to the conventional starting pitcher who will throw six innings, on average. If the opposing manager were to “stack” (or “tilt”) his batting order to have more lefties (LHB) to face a righty starting pitcher (RHB), or more RHB to face a LHP, as they do now, the value of his tilt would only be in effect for two innings, not six. The manager of the team using the “Pitchers Never Bat” strategy would most likely bring in the next two relievers with the opposite hand of his starter. Example: A lefty starter goes two innings, and is replaced by two consecutive right-handed relievers who would pitch two innings each.

After reviewing league averages for wOBAs for each of the four “handedness combinations” (i.e., LHP/LHB, LHP/RHB, RHP/LHB, and PHP/RHB) as well as how much managers “tilt” their line-ups to take advantage of the starting pitcher’s hand, I estimate that the opponent would lose his current handedness advantage for, on average, four PAs per game, with each of these PAs reducing his batters’ expected wOBA by 18 points for these PAs. Over 162 games, that amounts to 648 PAs per year. Using the rule of thumb that a decrease of 20 wOBA points decreases team run production by 10 runs per every 600 PAs, I estimate that the opponents will lose 9.8 runs/year (that is 18/20 * 10 * 648/600). And since every 10 runs is worth a win, on average, that’s a positive impact to the team implementing the “Pitchers Never Bat” strategy of about 1.0 wins/year (= 9.8/10).

But, since opponents will quickly catch on to the new strategy that they are facing, they should immediately stop trying to “stack” or “tilt” their line-ups. If the opposing manager puts up a line-up that is set up with absolutely no regard to lefty or righty pitching, he can reduce the negative impact to his offense by about 25%, down to a loss of 7.3 runs/year, or a loss of 0.7 wins/year. Since I assume that the opponents will take this less damaging approach, I will use +0.7 wins/year as a conservative estimate for Component #4.

Component #6 – Times Through the Order

Times Through the Order (TTO) refers to differences in pitcher performance due to how many times pitchers have faced the opposing lineup. I recently read an excellent piece on this topic by Mitchel Lichtman, published on Baseball Prospectus on 11/5/13, entitled “Everything You Always Wanted to Know About the Times Through the Order Penalty.” I will draw on one of his many key findings to estimate the impact of TTO on the “Pitchers Never Bat” strategy.

Lichtman presents data (drawn from 2000-2012) which shows that starting pitchers are, on average, at their best the first time through the line-up, are worse the second time through, and even worse the third time through. Using “wOBA against” statistics (adjusted appropriately for batter quality), he shows that pitchers suffer a decay of about 10 points in wOBA against when going from the first TTO to the second TTO, and then decay another 10 points when going from the second TTO to the third TTO. He also estimated the wOBA against statistic for the second TTO is equal to the pitchers’ overall wOBA against. So, in other words, starting pitchers are about 10 points better than average for the first TTO, about average for the second TTO, and about 10 points worse than average for the third TTO.

In the “Pitchers Never Bat” strategy, starters will occasionally work into the beginning of the second TTO, so I’ll assume that 80% of the batters they face will be in the starter’s first TTO, and 20% will be in the second TTO. This means that their wOBA against should be about eight points better (=10 points * 80%) than they would see if they were used in the conventional six-plus inning approach. This advantage will be repeated again by the relievers who replace the starter and pitch through the sixth inning, or until the time that the starter would typically be pulled when using a conventional pitching staff. Think of it this way – instead of a starter throwing a wOBA against of .320 for the first six innings, you get a starter plus two relievers each throwing a wOBA against of .312 for the first six innings. And this benefit is strictly due to the TTO effect.

Improving your wOBA against statistic by eight points for the first six innings of every game means that these pitchers will face about 4,374 batters per year (= 27 PA per game X 162 games.)  Again, using the rule of thumb of 20 woBA points equates to 10 runs per 600 PA, I estimate the impact of this improvement to be a decrease in Runs Allowed of 29.2 runs per year (=8/20 * 10 * 4,374/600.) And using the rule of thumb that 10 runs per year equates to one additional win per year, I can finally estimate that the positive impact of the TTO effect to be 2.9 additional wins per year (=29.2/10).

Now, let’s revisit where we stand with our six components:

Estimated Change in Wins Per Year by Component –

Component #1:   +3.6

Change in Runs due to pinch hitters batting for all pitchers

Component #2:   +0.0

Change in Runs Allowed due to using pitching staff in a new way

Component #3: Not Evaluated

Change in Runs Allowed due to added flexibility in selecting pitchers based on how they are warming up prior to or during a game

Component #4:   +0.7

Change in Runs Allowed due to opponents’ inability to “stack the lineup” to take advantage of the starting pitchers “handedness” (i.e., lefty or righty)

Component #5: Not evaluated

Change due to reducing size of pitching staff by 1-2 men

Component #6:   +2.9

Change in Runs Allowed due to the “times through the order” effect

TOTAL:                 +7.2 Wins per Year

CONCERNS FROM COMMENTERS

Commenters to my original post raised no objections with my estimated value of +3.6 wins per year due to Component #1, which is the expected change in runs due to pinch-hitters batting for all pitchers. Their two primary concerns were regarding Component #2, which is the change in runs allowed due to using the pitching staff in a new way. Commenters were concerned that my proposed staff of 11 pitchers, averaging 130 innings pitched (IP) per year each, would not be able to handle that large a workload, and therefore the pitchers’ performances would be worse than they would be as part of a traditional pitching staff.

On the issue of workload I see it as follows: Say half of the new staff comes from current relievers who are used to throwing 50-80 IP per year. The new strategy would ask them to average 100-130 IP per year. And let’s say that the other half of the new staff comes from current starters who are used to throwing 160-200 IP per year. The new strategy would ask them to throw 130-160 IP year. So, yes, one would expect that the old relievers would probably pitch worse if they were asked to throw an extra 50 IP per year. But, by similar logic, the old starters would be expected to pitch better if they were asked to reduce their workload by 30 or 40 IP per year. Do these two effects offset each other? Does one dominate the other? I don’t know. Even if Component #2 resulted in a negative net effect, how big could it be? Could it be large enough to outweigh the +7.2 wins estimated from Components #1, #4, and #6? I don’t think so.

And what if, instead, the GM hired 11 guys for the staff that were all starters previously? Would that lead to a net gain to the staff’s performance due to reduced workloads per person? Potentially. Also, note that the impact we are talking about here is solely due to workload and has nothing to do with Handedness (Component #4) or Times Through the Order (Component #6).

For those still concerned that an average of 130 IP for each of 11 pitchers is still a big negative, here are three ways to reduce the average workload:

First, due to call-ups from the minors, visits to the DL, and expanded rosters in September, team workloads are actually shared by far more than the current 12-13 pitchers on the roster at any one point in time. In 2016 the median number of pitchers used by NL teams was 27. If you ranked each team’s staffs at year-end by IP, and then added up the IP thrown by their top 12, you’d find the top 12 typically account for about 80% of their team’s total IP. So you could safely reduce my 130 IP per person that I required for the “Pitchers Never Bat” strategy by 10% to adjust for that. That brings the average workload required down to 117 IP (= 130 * 90%).

Second, some commenters suggested I keep a 12-man staff, not 11 as I proposed. Doing this would decrease the average workload per pitcher by another 8%, or about 9 IP. That would bring down the average workload from 117 IP to 108 IP. (Of course, this would require that the number of position players be reduced by one, and there would be some negative impact because of that.)

Third, as I mentioned in my first post, a team could keep an ace starter that is allowed to bat for himself. He would be used exactly as an ace is used now, pitching 6+ innings every fifth day. In this variation, the “Pitchers Never Bat” strategy would only be used on the four days that the ace is resting. So, here the ace would pitch about 180 innings, reducing the workload for each of the other pitchers by another six innings per year, bringing their average workload down to about 102 IP. (By the way, I roughly estimate that the ace would need to have an expected WHIP of 1.05 or lower to justify allowing him to bat. At a WHIP of 1.05, the added benefit of letting him pitch 6+ innings would just offset the benefits from Components #1, 2, 4, and 6.)

So, to recap, with all three of these changes incorporated, the staff would consist of an ace throwing 180 IP, plus 11 others averaging about 102 IP, and another 15 or so pitchers that come and go throughout the season to support the 12 “primary” guys by sucking up the remaining 20% of the entire team’s IP. This should alleviate the concerns about pitcher workload.

I’m still not totally comfortable quantifying the impact of Component #2 yet, but I’m going to go out on a limb and say that if the staff was developed from 11 guys who were previously starters throwing 180 IP, the smaller workload should improve their average performance. My hunch is that the impact might be slightly positive, whereas the commenters thought it was negative. At this point I’m still going to leave the impact of Component #2 at 0.0, or no change, pending further evaluation.

CONCLUSION

By adding estimates for the impacts of “Handedness” (Component #4) and “Times Through the Order” (Component #6) my total estimated value of the “Pitchers Never Bat” strategy has jumped dramatically from +3.6 wins (in my initial post) to +7.2 wins per year. If this were to hold up, this would be an astounding gain to any NL team that implemented the strategy. At the going rate of $8 million per year that teams currently pay per win, this equates to about $58 million per year. I look forward to hearing your comments regarding this analysis.

Oh, and by the way, if any NL team would like to discuss additional analysis and/or implementation of this strategy please feel free to contact me at howardsrubin@gmail.com.

A WAR Carol

Winter has come, baseball season is over, and Ebenezer finishes his analysis and goes home to his cold bed and DVD of Game 4 of the 2004 ALCS since there are no longer any current games to watch.

The Ghost of Pitcher Wins appears and informs him that he will be visited by the Ghosts of Relievers Past, Present, and Future, who will explain to him the errors of his ways.

Mike Marshall appears. “In 1974 I pitched 208.1 innings in relief during the regular season and 12 more in the post season. I accumulated 4.4 WAR. It would have been about 2 wins higher, but I was penalized for being a relief pitcher. It seems that giving my manager over 200 innings of good pitching becomes less valuable if I do it out of the bullpen when and where he needs it rather than as a starter on a schedule. I’m not alone — in MLB history there have been 393 pitcher seasons with over 100 regular season innings and no starts. I don’t even hold the record for most relief innings in a season. Why must I suffer for being a reliever when I carried a starter’s load?”

Next is the Ghost of Relievers Present. Tony Watson appears. “In 2016 I went 67.2 innings as a lefty with a large platoon split (.049 difference in wOBA between lefties and righties). But because I wasn’t totally hopeless against righties I faced well over twice as many righties as lefties (195 to 77) and ended the season with –0.1 WAR. Had I been a worse pitcher so Clint Hurdle used me less I’d have had a positive WAR. Would any manager have actually preferred a LOOGY who faced fewer batters and was inferior against both righties and lefties? Why am I penalized for being too good to be used only as a LOOGY?”

Next comes a group of six — it’s the Ghost of Relievers Future, and they say, “In the distant future a team attempts starting by committee. They have nine pitchers who typically go 18 batters each on a three-day rotation so as to avoid the third time through the order penalty. We come in in the middle of a game, at an unpredictable time, and do the same job for the same length of time as the starters. Occasionally we’re asked to cover additional outs if an earlier pitcher melts down or is injured so we enter early and go long. The starters have a lower replacement level than we do despite having the easier job with greater certainty about both when they will enter and leave a game. How is this fair?”

They fade from view, and The Ghost of Pitcher Wins reappears and says, “Seriously; the reason relievers have a higher replacement level is because their usage is different than that of a starter in ways that affect their value. But different relievers can have drastically different usage, and that also affects their value. Fix this, Ebenezer, or in the long run WAR for relievers will suffer my fate and be superseded by a better tool for reliever evaluation.”

Why the Problem Exists

Why does the replacement level differ between starters and relievers? That’s easy — replacement level is different because it’s easier to find a reliever with a given xFIP, wOBA, RA/9, ERA, or pretty much any other rate stat than it is to find a starter that good. Starters improve when sent to the bullpen; relief is an easier job, so it has a higher replacement level.

But if that were all there was to it then pretty much everyone would do nothing but have bullpen games. Relievers are better and the goal is to win games. So why employ starters at all, much less pay them lots of money?

I’m going to assume that a team has seven roster spots for relievers and five for starters. I’m going to exclude September and October from this analysis as the limit to a 25-man roster doesn’t apply in those months.

In 2016, prior to September, a starter roster spot averaged 151.8 innings (decimal fraction rather than outs obviously). A reliever roster spot averaged 60.8 innings. A team averaged 1184.6 innings.

With those utilization numbers a team would need 20 roster spots of typical relief pitching to get to September. This is not viable. A reliever is less valuable than a starter because eating innings has real value. Getting lots of outs has value beyond simple run prevention, because the team not only needs to prevent runs per at-bat for one or two lefties a game, but someone also needs to get through a large number of innings, and most relievers provide far less of this value than a starter.

The problems with reliever WAR in the fable above all come from the fact that we’re using reliever or starter status as a proxy for the ability to eat innings and changing replacement level to reflect this, rather than giving an explicit adjustment for being able to eat innings as a thing of value in its own right and otherwise evaluating pitcher results on a common basis.

Not all starters are equally good at eating innings, not all relievers are equally bad at it, and the ability to eat innings per roster spot used on the pitching staff has value.

When Steve Carlton went 346.1 innings of 11.1 WAR ball in ’72, he not only pitched quite well on the batters he faced, but he also gave his managers a lot of added flexibility by eating far more than his share of the innings. This is a source of substantial value not captured in the current methods. When Mike Marshall ate over 208 innings in relief that was again a source of substantial value not captured in the current methods. Marshall is in fact penalized on the assumption that he is failing to do exactly the thing that he clearly did.

Approach

One problem with what I’ve been saying is that the value added depends on innings/roster spot over time, and I don’t have good information about roster usage. Even if I did have good information about exactly how long each pitcher spent on a roster, I don’t want to give a pitcher a negative WAR for being called up and never used. For that matter I also don’t want to have to change the formula in September when roster spots drop in value.

I’m going to use appearances as a proxy for roster-spot usage. Appearances are readily available and this doesn’t penalize a pitcher just for sitting on the bench. Outs/appearance gives an indication of how good a pitcher is at eating innings, or at least of how good his manager thinks he is. Once a pitcher is in, he typically stays in until the manager has a reason to take him out or the game ends. Closers put in only at the end see such short appearances because the manager doesn’t want to use him for longer appearances.

Note that this is all extremely preliminary; I’m mostly hoping someone else will come up with a better solution than I have below.

Cut to the Chase

I had a bunch of stuff typed up, and reading it puts me to sleep.

I ended up convincing myself that I wasn’t going to do better than a simple linear approach. I’m using outs/appearance as a proxy for efficiency at eating innings; I split this into two terms.

The proposed replacement formula for pitcher WAR is:

WAR = (Runs above League Average)/(R/W) + (C₁ × total outs recorded) – (C₂ × total appearances)

That’s familiar enough — the first term is wins above (or below) average, the C₁ × total outs recorded term is simply adding in a replacement level, the C₂ × total appearances is a penalty to represent eating a roster spot.

What I’m actually doing is reducing the replacement level and adding a small penalty based on number of appearances. Unless you think there is something magical about being the “starter,” the different replacement levels for starters and replacements already add such a penalty. They simply do so in an ad-hoc way by adjusting the replacement level and assuming that relievers are the ones with short appearances.

The elephant in the room is that relievers and starters record different numbers of appearances over the same amount of time and I’m using appearances as a proxy for roster usage. This is where the math I removed comes in. On June 17, 1915, George Washington “Zip” Zabel came in for 18 1/3 innings in relief in a single game. I don’t think he needed less rest than a starter. Outs/appearance is being used as a stand-in for the ability to eat innings, and rest requirements would also be reasonably modeled as a term dependent on Outs/appearance. I don’t need a separate term for the things already being accounted for.

Let’s run the numbers for 2016. I’m going to assume that the total WAR given to starters and relievers in each league is at least approximately correct, and that all I’m doing is redistributing that WAR slightly.

I don’t have league-specific runs/win handy; 9.778 is the combined value, so I’ll use that. I also don’t have a good way to correct for the fact that some fraction of reliever WAR is due to leverage concerns and won’t apply to the average values I’m using here.

155.3 = outs/27×(4.22−4.34)/.92/9.778 + 41,450×C₁ −2,428×C₂

58.8 = outs/27×(4.22−3.94)/.92/9.778 + 23,383×C₁ −7,301×C₂

And if follows that for the AL the value of C₁ is 0.004906 and C₂ is 0.01135.

The AL C₁ value gives a replacement level of 0.1345 below league average, or replacement of 0.3655, slightly less than the .38 currently used for starters. Then the AL C₂ value penalizes a pitcher an 88^th of a win for each time he comes into a game.

The same calculation for the NL comes out with a C₁ of 0.004856 and C₂ of 0.009520; or replacement of 0.3689, and a penalty of one 105^th of a win per appearance.

Call it a replacement level of 1 win less than average per 200 outs recorded and a penalty of 1 win per 100 appearances and you’d be close enough for a first cut.

I strongly suspect that more detailed analysis with better starting numbers and taking leverage effects into account would work better, but the basic method will give long relievers some credit for what they’re doing, and give exceptionally long or short starters a small amount of credit for their ability (or inability) to eat innings also.

Now that the World Series is over and the offseason upon us, our view of baseball begins to shift. For the last six months we have been laser-focused on the outcomes on the field. Now we begin to focus on the process of team-building and the chase to taste October Glory.

This exercise is an attempt to figure out how close teams may be and what they need to add in in the offseason to reach the playoffs. To do this, I looked at the latest FanGraphs depth charts, and the WAR landscape looks something like this:

Team 2017 Projected WAR

Cubs 50.1
Dodgers 48.7
Nationals 45.3
Indians 43.2
Red Sox 42.5
Giants 41.1
Astros 40.2
Cardinals 39.1
Angels 38.3
Mets 37.5
Mariners 37.2
Yankees 36.9
Pirates 36.6
Tigers 34.2
Rays 33.8
Rangers 33.5
Blue Jays 32.5
Marlins 32
Orioles 31.9
White Sox 31.1
Royals 30.7
Athletics 30.7
Diamondbacks 30.3
Rockies 27.7
Twins 27.7
Reds 26.5
Phillies 26.1
Padres 23
Braves 22.9
Brewers 21.6

To the surprise of no one, the Cubs lead in projected WAR due to the excellent core in place, with the Dodgers and Nationals taking second and third, respectively. The Indians and Red Sox rank fourth and fifth on this list and represent the top of the American League.

Now, to get a feel for what it is likely going to take to make the playoffs in 2017, I approximated how much team WAR will be needed to make the 2017 playoffs by averaging the WARs of playoff qualifiers going back to 2012 and came up with this:

AL WAR Target: 42.0
NL WAR Target: 44.6

American League teams, when assessing whether they are a realistic playoff contender, should project for a team WAR of 42, and National League teams thinking the same should project for closer to 45. Next, I took the projected WAR from each team and subtracted it from the respective league’s WAR target to determine how close teams may or may not be:

Team Target WAR +/-

Cubs 5.5
Dodgers 4.1
Indians 1.2
Nationals 0.7
Red Sox 0.5
Astros -1.8
Giants -3.5
Angels -3.7
Mariners -4.8
Yankees -5.1
Cardinals -5.5
Mets -7.1
Tigers -7.8
Pirates -8.0
Rays -8.2
Rangers -8.5
Blue Jays -9.5
Orioles -10.1
White Sox -10.9
Royals -11.3
Athletics -11.3
Marlins -12.6
Diamondbacks -14.3
Twins -14.3
Rockies -16.9
Reds -18.1
Phillies -18.5
Padres -21.6
Braves -21.7
Brewers -23.0

We see that only five teams exceed the arbitrary threshold of projecting above an average playoff contender. For a team like the Astros and Giants the decision to go for it is obvious. The Giants and Astros have payroll available and solid player development. Interestingly enough, the Angels are closer than one might initially think, but that has more to do with Mike Trout than the cast around him.

Moving toward the middle of the graph is where things begin to get intriguing. With the cost of 1 WAR on the open market approximately $8 million and the trade market expected to be active and expensive, teams need to be realistic with how much they are willing to spend, in cash or prospects, in order to reach the projected WAR threshold. Fringe contenders like the Pirates, Blue Jays and White Sox need to look in the mirror and recognize the uphill battle they have. The Blue Jays are losing key pieces to free agency and they could potentially cripple their flexibility with ill-advised moves. The Pirates are staring up at the Cubs dynasty in the making and you wonder if it is time to shop Andrew McCutchen and other short-term pieces. Lastly, the White Sox have Chris Sale, Jose Quintana, Todd Frazier and other quality pieces around the diamond. Given the AL Central, the Sox could blow it up and return to contention sooner rather than later, with the Royals and Tigers’ windows closing and the Indians representing the class of the division.

As we know, it rarely plays out this cleanly on the field, but from a pure projections standpoint, this serves as a gauge to where teams currently are. Some teams have very easy decisions and the choice to contend or rebuild is obvious. For other teams, the decision is less clear, and failure to capitalize could leave them stirring in mediocrity. The Cubs and Indians will fortify their rosters to chase down another pennant. For teams like the Pirates and White Sox, it just might be time to hit the red button.

It’s safe to say 2016 was a disappointing year for Jose Bautista. After posting three consecutive seasons with a WAR greater than 4, Bautista posted his lowest mark since 2008. The Toronto Blue Jays were ousted in the American League Championship Series for the second consecutive year and have looming decisions on how to go forward. Bautista is a polarizing figure in the baseball world and is a free agent in a relatively weak class. The big question teams will be asking is whether Bautista’s 2016 was more indicative of further decline or if there is a chance he rebounds. The 36-year-old will be looking for his last big payday.

Bautista’s defensive game continued to deteriorate. After posting a -12.5 UZR/150 in 2015, Bautista had a -9.3 UZR/150 this past season. Moreover, he finished second to J.D. Martinez for the right field Iron Glove. The main takeaway here is that Bautista is no longer good defensively and we shouldn’t expect him to get better. Unless a team wants him playing in the outfield, his future likely rests at first base or in the DH role. That’s not say a team cannot be playoff contenders with a poor right fielder. The aforementioned J.D. Martinez and Mark Trumbo were both below-average fielders this past season and both teams were in the thick of the playoff race. Moreover, being a good base-runner has never been part of Bautista’s game. Which brings us to his offensive value.

Jose Bautista will be paid on the basis of his bat. With his bad defence and sub-par base-running, teams will be lining up for Bautista due to the offensive numbers he has put up since his breakout in September of 2009. Since 2010, only three players have had a higher wRC+, and nobody has more home runs. On the surface, Bautista’s 34-point drop in wOBA and 26-point drop in wRC+ show a declining bat. Factor in his age, and things aren’t looking so rosy. Digging deeper, it is possible this was somewhat of an anomaly and Bautista will have a better offensive season in 2017. This is what makes Jose Bautista the winter’s most intriguing free agent.

Jose Bautista Walk and Strikeout Rate

Bautista’s walk rate remained elite. The Dominican slugger is one of the more selective hitters in the league, having the tenth-lowest swing percentage since 2014. The strikeouts rose, becoming much closer to the league-average 20.6% strikeout rate. Since 2014, Bautista has the 65^th-best swinging strike rate at 7.3%, tied with notable players such as Adrian Beltre and Joey Votto. Bautista’s swinging strike rate in 2016 was 7.2%. This suggests his strikeout rate has more to do with an increase in called strikes than swinging strikes.

It’s been said that when a player can no longer catch up to a fastball, the end is nigh. The swing is slower, leading to more swinging strikeouts and an increase in weak contact.

FB SwStr%: League and Bautista

Bautista’s been below league average at swinging and missing on fastballs throughout his career. He saw an uptick in 2016, but it was still better that most. Moreover, among players to see at least 1000 pitches, Bautista ranked 11^th in the league in average fastball exit velocity on line drives and fly balls, at 97.8 MPH against. Overall, Bautista can still hit the fastball.

In a similar method as shown here by Andrew Perpetua, I took a look to see if Bautista was getting lucky or unlucky.

View post on imgur.com

As you can see, Bautista’s slugging was fairly close to its expected value. Bautista’s lowest slugging percentage over the past five years was .498. There is a big difference in batting average, likely due to the big difference between expected BABIP and actual BABIP. To look into this disparity further, I looked at Alex Chamberlain’s expected BABIP formula. Using that formula, the xBABIP was .287, a lot closer to Bautista’s batting average. Bautista has been a career .260 BABIP hitter. Some of that is due to him popping out a lot and a lack of speed. Lastly, by taking a look at xISO, Bautista also underperformed by both metrics. Through Chamberlain’s formula, Bautista’s expected Isolated Power would be .265, and under the work of Andrew Dominijanni, his expected ISO would be .257. Bautista’s .217 ISO was his lowest mark since 2009. It is likely that Bautista was a tad unlucky in regards to outcomes. The story told by the multiple variants of xBABIP, xISO, and xAVG all point toward a better fortune for the Dominican slugger.

Another potential concerning issue with Bautista was the drop in contact on pitches outside the zone. With a career 64.7% O-Contact percentage, this number dropped to 60.4%, the lowest since 2009. You can see the difference between 2012-2015 and his 2016 contact percentages in various parts of the zone below.

Bautista Contact% 2012-2015

Bautista Contact% 2016

While his zone contact rate looks consistent, his contact made outside the zone away from Bautista decreased. To compensate for this, Bautista swung slightly less on pitches outside the strike zone. If he continues to struggle to make contact on pitches outside, then Bautista will continue to take more chances on borderline calls. The overall contact rate remained solid and he continued to pull the ball at the same rate, showing that Bautista still has good bat speed.

Another riveting aspect of Jose Bautista is that over his career, he hasn’t had a platoon split. Against right-handers, the six-time All-Star has a career 131 wRC+, and against southpaws he owns a 135 wRC+. The current Steamer Projections peg Bautista to be worth 2.9 Wins Above Replacement, with a 128 wRC+.

Jose Bautista showed some signs of decline. He made less contact on outside pitches, and he saw a decrease in offensive stats such as wRC+ and Isolated Power. The three-time Silver Slugger however continued to show strong plate discipline, and continued to hit the ball hard, using the same approach he has over the past few years. Furthermore, many expected stats point toward Bautista being somewhat unlucky with balls in play. With a wRC+ of 122, it is clear he can still hit and a rebound in offensive numbers isn’t out of the question. With the sub-par season he had, he could very well be one of the better value sluggers in the market. ­It will be a fascinating offseason for the Dominican slugger.

A popular theme this preseason was parity.  Truth be told, it’s been quite popular since the 2014 preseason projections forecast the smallest disparity between the best and worst teams at least going back to 2005.  Since then, the term has been so worn out that BuzzFeed included it on their end-of-the-year list of “words that need to be stricken from the Saber community” (source needed).

While the AL was the main driver of parity-related conversation, it might be worth mentioning that the results show that the AL was more lopsided than it was in 2015 while the NL’s gap was more compressed compared to the previous season despite the existence of the Chicago Cubs World Champion Chicago Cubs.  It’s not that that’s incredible — projection systems are conservative and variables such as sequencing and luck are still unpredictable.  Reflections of these points can be seen in Texas’ record in one-run games, or the Phillies and Braves performing better than they expected, or the Twins performing more like the Phillies and Braves were expected to.

It’s possibly reasonable to think that, as front offices skew more towards advanced analytics, the trend of increased parity will continue.  Of course that’s too simple of a statement as revenue sharing and luxury-tax measures have played their part in balancing out the competitive environment as well.  But as front offices progress it’s more likely that the true-talent level at the major-league level will span a smaller range, fewer and fewer at-bats will go to poor players, and the top players should be more evenly distributed throughout the league, speaking in terms of true talent.

This article, however, is not really about anything based in analytics or reality and I don’t know how to segue from my intro into delivering to you what I set out to do any better than asking you to assume some truly ridiculous prerequisites:

1. MLB and the owners of all the teams only care about the viewer’s experience
2. Unpredictable variables have become somewhat predictable. This includes some luck, breakouts, injuries, and rapid declines or dips based on smaller injuries.  This does not mean, however, that Runs and RBIs are predictable; it just works out perfectly by FanGraphs WAR
3. The public is unaware of the predictability of baseball and there is an Illuminati-type presence in baseball headed by a board of trustees that includes, ironically, but obviously, Joe Morgan
4. Payrolls are dictated by the outcomes that MLB knows will happen and are strictly performance-based – by FanGraphs WAR
5. Rosters are reconstructed every single year
6. Reconstructing rosters has no effect on luck or sequencing or ballpark effects (maybe all ballparks have the same dimensions)
7. The DH is in both leagues but is only reserved for a portion of games throughout the year; teams are required to allocate at least 140 PA to pitchers
8. Dave Stewart somehow managed to mess up his last season as the Diamondbacks GM (They just happened to be the last team I constructed and there wasn’t enough WAR left to make them as good as the other teams — the Cubs got dinged by this, too.)

What I did was export all the data I felt was relevant from the leaderboards and build 30 rosters based on the average number of Plate Appearances, Games Started, Innings Pitched, and WAR.  The numbers for the league break down like this:

Offense

PA (Non Pitchers): 179,218 (5,974.93/team)

WAR (Non Pitchers): 572 (19.07/team)

PA (Pitchers): 5,366 (178.87/team)

WAR (Pitchers): -2.6 (-0.09/team)

Pitching

GS: 4856 (161.87/team)

IP: 43306.3 (1443.54/team)

WAR: 429.5 (14.32/team)

The only other things I wanted to be consistent with reality were the distribution of plate appearances by position and accounting for the IP by position players.  The first caveat doesn’t work out perfectly, but you’re not going to find a team that received 1,500 PA from their catchers and only 900 from all three outfield positions combined.  The second one, however, I believe I perfected.

After I had built the 30 rosters I realized they were only distinguished by a roster number, so in order to assign each roster a team, I simply took an alphabetical list of the team names and went down one by one with a random number generator and matched that team and random number to the roster with the corresponding number.

Here’s a link!

Who was on your favorite team?  Considering the public doesn’t know about the basically flawless projection systems, how did your team do compared to how you thought they would do? How much would this affect the way you watch the game?  How much would this affect your team loyalty?  Would you enjoy this?  Is this the dumbest exercise you’ve ever seen?  Is Joe Morgan a genius for complaining about the lack of dynasties while he secretly pulled strings to get all teams to be perfectly balanced, competitively, thereby creating a socialist baseball regime?

I’ll do this again when the 2017 rosters and projections are set so we can follow up on “equal” roster construction.

In “Hardball Retrospective: Evaluating Scouting and Development Outcomes for the Modern-Era Franchises”, I placed every ballplayer in the modern era (from 1901-present) on their original team. I calculated revised standings for every season based entirely on the performance of each team’s “original” players. I discuss every team’s “original” players and seasons at length along with organizational performance with respect to the Amateur Draft (or First-Year Player Draft), amateur free agent signings and other methods of player acquisition.  Season standings, WAR and Win Shares totals for the “original” teams are compared against the “actual” team results to assess each franchise’s scouting, development and general management skills.

Expanding on my research for the book, the following series of articles will reveal the teams with the biggest single-season difference in the WAR and Win Shares for the “Original” vs. “Actual” rosters for every Major League organization. “Hardball Retrospective” is available in digital format on Amazon, Barnes and Noble, GooglePlay, iTunes and KoboBooks. The paperback edition is available on Amazon, Barnes and Noble and CreateSpace. Supplemental Statistics, Charts and Graphs along with a discussion forum are offered at TuataraSoftware.com.

Don Daglow (Intellivision World Series Major League Baseball, Earl Weaver Baseball, Tony LaRussa Baseball) contributed the foreword for Hardball Retrospective. The foreword and preview of my book are accessible here.

Terminology

OWAR – Wins Above Replacement for players on “original” teams

OWS – Win Shares for players on “original” teams

OPW% – Pythagorean Won-Loss record for the “original” teams

AWAR – Wins Above Replacement for players on “actual” teams

AWS – Win Shares for players on “actual” teams

APW% – Pythagorean Won-Loss record for the “actual” teams

Assessment

The 1921 Detroit Tigers 

OWAR: 49.3     OWS: 289     OPW%: .553     (85-69)

AWAR: 40.4      AWS: 212     APW%: .464     (71-82)

WARdiff: 8.9                        WSdiff: 77  

The “Original” 1921 Tigers paced the Junior Circuit in OWAR and OWS. Detroit finished third in the American League, ten games in arrears to the Red Sox. Harry “Slug” Heilmann (.394/19/139) collected his first batting title, smashed 43 two-baggers and topped the leader boards with 237 safeties. Ty Cobb (.389/12/101) continued to mash opposition offerings. “The Georgia Peach” tallied 197 base knocks, 124 runs, 37 doubles and 16 triples while recording an OBP of .452 and a .596 SLG. Baby Doll Jacobson (.352/5/90) contributed 211 base hits, 38 doubles and 14 triples to Detroit’s powerful lineup. Ray “Rabbit” Powell (.306/12/74) legged out 18 three-base hits to lead the League and scored 114 runs. Powell and outfield mate Bobby Veach (.338/16/128) established personal-bests in almost every major offensive category. Lu Blue supplied a .308 BA with 103 runs scored and 33 two-baggers in his inaugural campaign while fellow first-sacker Wally Pipp (.296/8/103) drilled 35 doubles.

Ty Cobb placed runner-up to Willie Mays among center fielders in the “The New Bill James Historical Baseball Abstract” top 100 player rankings. “Original” Tigers teammates registered in the “NBJHBA” top 100 ratings include Harry Heilmann (16^th-RF), Bobby Veach (33^rd-LF), Carl Mays (38^th-P), Donie Bush (51^st-SS), Lu Blue (77^th-1B), George H. Burns (79^th-1B), Wally Pipp (83^rd-1B) and Baby Doll Jacobson (85^th-CF).

“Actuals” backstop Johnny Bassler rated forty-seventh.

  Original 1921 Tigers                                Actual 1921 Tigers

Carl “Sub” Mays (27-9, 3.05) topped the American League in victories, games (49), saves (7) and innings pitched (336.2). Clarence Mitchell fashioned a 2.89 ERA and notched 11 wins while splitting time among the bullpen and starting rotation. Dutch H. Leonard contributed a 3.75 ERA with an 11-13 record for the “Actuals”.

  Original 1921 Tigers                                Actual 1921 Tigers 

Notable Transactions

Carl Mays 

Before 1914 Season: Returned to Providence (International) by the Detroit Tigers after expiration of minor league working agreement.

Before 1914 Season: Obtained by the Boston Red Sox from Providence (International) as part of a minor league working agreement.

July 30, 1919: the Boston Red Sox sent Carl Mays to the New York Yankees to complete an earlier deal made on July 29, 1919. July 29, 1919: The Boston Red Sox sent a player to be named later to the New York Yankees for Bob McGraw, Allen Russell and $40,000. 

Baby Doll Jacobson 

Before 1915 Season: Purchased by the Detroit Tigers from Chattanooga (Southern Association).

August 18, 1915: Traded by the Detroit Tigers with $15,000 to the St. Louis Browns for Bill James. 

Ray Powell 

July 10, 1917: Purchased with Wally Rehg by the Boston Braves from Providence (International).

Clarence Mitchell

October 16, 1917: Selected off waivers by the Brooklyn Robins from the Cincinnati Reds.

Wally Pipp

August, 1912: Purchased by the Detroit Tigers from Kalamazoo (Southern Michigan). (Date given is approximate. Exact date is uncertain.)

February 4, 1915: Purchased with Hugh High by the New York Yankees from the Detroit Tigers.

Honorable Mention

The 2003 Detroit Tigers 

OWAR: 14.8     OWS: 195     OPW%: .400     (65-97)

AWAR: 7.1       AWS: 129      APW%: .265    (43-119)

WARdiff: 7.7                        WSdiff: 66

The “Original” 2003 Tigers finished last in the AL Central, 17 games behind the White Sox. However the “Actuals” finished 47 games off the pace with a ghastly 43-119 record.

Juan Encarnacion (.270/19/94) established career-highs in RBI and doubles (37). Frank Catalanotto contributed a .299 BA with 34 two-base knocks. Robert Fick registered a personal-best with 80 ribbies and Dave R. Roberts pilfered 40 bags. The bullpen featured John Smoltz (1.12, 45 SV) and Francisco Cordero (2.94, 15 SV).

On Deck

What Might Have Been – The “Original” 1979 Mets

References and Resources

Baseball America – Executive Database

Baseball-Reference

James, Bill. The New Bill James Historical Baseball Abstract. New York, NY.: The Free Press, 2001. Print.

James, Bill, with Jim Henzler. Win Shares. Morton Grove, Ill.: STATS, 2002. Print.

Retrosheet – Transactions Database

The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at “www.retrosheet.org”.

Seamheads – Baseball Gauge

Sean Lahman Baseball Archive

As a Yankees fan (albeit one that has only witnessed their 2009 World Series), I have never been more excited about the team’s present and future. With the MLB roster slowly filling with good, young talent, and with even more stirring circumstances in the minors, the Yankees have the potential to be another powerhouse team.

The Team

Right now, the Yankees are in the midst of a revolution. Out with the old (A-Rod and Teixeira) and in with the new (Sanchez, Judge and Austin). Despite missing out on the playoffs, they will feature a well-rounded lineup at the start of next year.

It’s safe to say that Gary Sanchez won’t enjoy quite the success he did in the last two months of this season. Actually, he won’t come close. This isn’t to say he will play poorly, it’s just that he played so well that he can’t come back to those levels. However, Sanchez will no doubt still be one of the better-hitting catchers in the MLB with average to plus defense behind the dish, so they will already be better in that position in 2017 than they were in 2016.

The Yankees infield is the most likely to change the least with only Greg Bird slotting in at first base. Didi Gregorious, Starlin Castro and Chase Headley are each under team control until at least 2018, and there isn’t anyone challenging them for their spots at the moment. At first base, though, I say it is most likely that Bird gets the spot because it is possible that Tyler Austin beats him out in spring training. Austin is more likely to be used as a quasi-utility player as he can play at first, in right field and DH.

In the outfield everything could remain the same as the end of the season with Hicks or Judge in right, Ellsbury in center and Gardner in left. It could also see some changes. Gardner and Ellsbury both have the potential to be traded over the offseason with Gardner the more likely of the two. There are options to fill those gaps if trades do happen. Mason Williams could fill in until Clint Frazier is (hopefully) ready later in the season. Hicks, Austin and Judge could also fill the holes if needed.

The Yankees pitching is the most worrisome issue. The starting pitching, that is. Masahiro Tanaka performed well in 2016, so there is no reason to think otherwise for the next year. Beyond that, though, are question marks. Nate Eovaldi will probably be a non-tender after his Tommy John surgery. Pineda had his usual ups and downs. Sabathia is still getting older. Then there are numerous options in Luis Severino, Chad Green, Luis Cessa and Bryan Mitchell. Severino will be given the longest look because of his end to the 2015 season, but it’s a toss-up from there.

The bullpen in New York is still a quality one despite trading away Aroldis Chapman and Andrew Miller. Dellin Betances is one of the best in the game, so that’s a good start. Tyler Clippard, Adam Warren and whoever misses out on the rotation gig will presumably fill in the rest with a lefty thrown in.

The Minors

Now comes the most exciting part of the Yankees. With a system that starts with four top-30 prospects despite Sanchez already graduating, the Bombers are on their way to a good future. Frazier is in AAA and still needs to put up good at-bats before he gets the call to the majors, but that time will come soon enough. Gleyber Torres and Jorge Mateo will likely start the year in AA, so they won’t be seen until 2018 most likely, especially with the likes of Gregorious and Castro blocking them. Beyond their top three guys, the Yankees still have plenty of players who could make a major-league impact once it’s their time. Simply, there is a lot to be excited about when it comes to the team’s future.

The Yankees will have the 17th overall pick in next year’s draft, so they will be in familiar position after having the 16th and 18th picks in the two previous years. Their first-round picks in recent years have both been ones that I personally like, but who wouldn’t? James Kaprielian is shining in the Arizona Fall League and Blake Rutherford looks like a steal at the 18th pick, especially after his hot start to his pro career. This year will hopefully prove to be another that produces some good picks.

The Offseason

With the Yankees pretty much set with position players, there’s no reason to add any pricey free agents. It also wouldn’t be wise to block some of their young players out to prove themselves or ones that are close to ready in the minors. Pitching is another story.

As I stated before, their starting pitching has question marks when it comes to Sabathia’s age, Pineda’s consistency and Severino bouncing back. There also aren’t many pitchers on the free-agent market that stand out. Overpaying for Rich Hill would be contradictory to what the Yankees are trying to do in becoming younger, but his dominance when healthy is something that can’t be questioned. It wouldn’t be a bad move to sign him, but it would add yet another question mark to their rotation due to his injury history. Signing him also wouldn’t help any towards getting under the luxury tax, which Steinbrenner would like to do.

The only free-agent acquisition that I would like to see is a top-notch reliever, which means one of Chapman, Kenley Jansen or Mark Melancon. Jansen is likely going back to the Dodgers and Melancon would be yet another righty for the bullpen. A reunion with Chapman would be the best move. Pairing him with Betances again would put the bullpen in great shape. It’s just that it will cost a lot.

In terms of trading, I am one that is all for trading Gardner, Ellsbury and/or Brian McCann. Ellsbury’s contract probably means he’s staying, but Gardner will be easy to move if Brian Cashman can get the right return. Some reports have said that a swap of him for a middle-of-the-rotation pitcher could work, and that would be just what the Yankees need. McCann will have high demand this offseason with multiple teams needing catchers and not enough free agents to go around. The Yankees will have to eat a good chunk of his contract to get anything of value in return, but it shouldn’t be a problem as they’d be shedding a good portion of his $17-million-per-year contract. It would also give younger players like Bird, Austin and Judge a chance to DH.

The Braves have been said to want a reunion with McCann but won’t trade Mike Foltynewicz for him. The Yankees will do well if they can eat about half of his contract and get a couple middling prospects with some upside.

With such a deep farm, the Yankees also have the ability to trade for a front-of-the-rotation starter. Landing one of the top guys on the trade market probably isn’t in their best interests, though. To get one of Chris Sale, Chris Archer or Sonny Gray will cost a good portion of what the Yankees were able to get for Chapman and Miller. Instead, they should look to trade from depth for a guy that is a step down from the others. With Torres looking like the better middle-infield prospect, trading Mateo as the headliner of a package for a starter would be a good move and won’t impact the team’s future too much.

In Summary

In an ideal scenario, the Yankees will sign one of the top relievers to pair with Betances, stand pat on other free agents and see how Cashman can work the trade market for a third straight offseason. The Yankees likely aren’t a top contender next season, but the potential is there. If things break right with Judge, Bird, Sanchez and the rotation, they could find themselves at the top of the A.L. East. Right now, though, they should look to continue development of their top-three farm system and look at 2018 as the year to really contend.