Archive for January, 2014

Hypothetical Free-Agent Teams

With just a couple weeks until MLB camps begin with pitchers and catchers reporting, most of the big-name free agents have found new homes and are looking to settle in and produce for their new team. However, there are still a few stragglers that are looking for the right opportunity for their services. Some players *cough* Drew, Cruz and Morales *cough* are finding it difficult to land a spot due to their limited markets. Likewise, most starting pitchers needed to wait out the Masahiro Tanaka saga before teams decided to move on.

While the pickings are slim when it comes to some positions, I wondered what a team complied fully of the remaining free agents would look like, and how they would stack up against the rest of the league if they formed a new team. For this example, they will be called the Free Agent Stragglers. Now, there were some guidelines when putting this team together. First of all, all WAR projections are taken from Oliver simply because the Oliver system projects all batters to receive 600 PA and sort of evens the playing field that way.

Obviously there are some flaws to this, most notably bench players who will not reach that mark, but, I digress. Also, personal opinion is left out. Players listed at each position are simply the highest projected WAR player left at that position at it stands right now, defense and other considerations be damned. Lastly, for this illustration, I made the hypothetical team an AL team simply to give to an extra spot in the lineup. Finally, to be eligible, there has to be an Oliver projection for that player. Basically, this just affected Suk-Min Yoon and Yenier Bello.

At any rate, here are the hypothetical Free Agent Stragglers:


Catcher: Kelly Shoppach (1.3 WAR)

First Base: Kendrys Morales (1.5 WAR)

Second Base: Elliot Johnson (0.1 WAR)

Third Base: Justin Turner (0.9 WAR)

Shortstop: Stephen Drew (1.7 WAR)

Left Field: Juan Pierre (0.9 WAR)

Center Field: Andres Torres (0.8 WAR)

Right Field: Nelson Cruz (2.6 WAR)

Designated Hitter: Lance Berkman (0.8 WAR)

Starting Lineup WAR: 10.6


Bench: Michael Young (0.5 WAR)

Bench: Dewayne Wise (0.6 WAR)

Bench: Jeff Baker (0.4 WAR)

Bench: Yorvit Torrealba (0 WAR)

Bench WAR: 1.5/3 = 0.5 WAR

 *WAR was divided by three to try and compensate for the fact that bench players will not see the projected playing time that Oliver gives.


Starting Pitcher: A.J. Burnett (2.3 WAR)

Starting Pitcher: Ubaldo Jimenez (1.8 WAR)

Starting Pitcher: Paul Maholm (1.3 WAR)

Starting Pitcher: Jason Hammel (1.2 WAR)

Starting Pitcher: Erik Bedard (1.1 WAR)

Starting Rotation WAR: 7.7


Closer: Fernando Rodney (0.7 WAR)

Setup: Matt Belisle (1.0 WAR)

Relief Pitcher: Rafael Betancourt (0.5 WAR)

Relief Pitcher: Francisco Rodriguez (0.4 WAR)

Relief Pitcher: Andrew Bailey (0.2 WAR)

Left Handed Relief Pitcher: Mike Gonzalez (0.0 WAR)

Long Relief / Alt Starter: Chris Capuano (1.0 WAR/3 = 0.3 WAR)

*Capuano’s 1.0 WAR is clearly for him being a SP. I divided it by three and rounded down to account for spot starts and actual bullpen work.

Bullpen WAR: 3.1



So, what does this tell us? According to the FanGraphs team Depth Charts, the Free Agent Stragglers would be better than exactly one team: Miami Marlins. The Marlins are currently projected at a team WAR of 20.9; 1.0 less WAR than this team. The next lowest team, that Chicago White Sox, have 4.3 WAR on the Stragglers. Now, as stated earlier, this is an imperfect list. The projections are made differently and the team charts take into consideration team depth and actual predicted playing time. Nonetheless, it still puts it into perspective a bit.

To look at it another way, Mike Trout’s 10.4 WAR 2013 would only be 0.2 worse than the team’s full lineup. Throw Kershaw into this rotation and he would have made up for 6.5 WAR (2.2 less than the team’s rotation).

Yes, I realize that Lance Berkman is set to announce his retirement. However, it is my assumption that this is the great opportunity that he was looking for and he signs on with the Free Agent Stragglers to become their full time DH. Moving on.

There were some puzzling omissions with this as well, the main person being Ervin Santana. While Steamers gives Santana a projection of 2.6 WAR, Oliver likes Ervin for only 0.6 WAR. After looking into it further, aside from the names listed above for the team, Oliver projections has six additional starting pitchers slated to give their team more than Santana can. That list includes Tommy Hanson (1.0), Jeff Niemann (0.9), Roy Oswalt (0.9), Bronson Arroyo (0.8), Johan Santana (0.8) and Jake Westbrook (0.7). Let that sink in for a moment.

Now, you cannot just have one team enter the league. Let’s take the hypothetical one step further. What if a team was formed just as free agency started? What would the team look like if the top players signed with the team from the beginning? How good could that team be? Only stipulations other than the ones listed above are that they had to have actually gone to free agency i.e. signed on or after November 5th, and they cannot be listed on the above team. I’ll call them the Free Agent Sluggers. Let’s take a look, shall we?


Catcher: Brian McCann (4.1 WAR)

First Base: James Loney (1.8 WAR)

Second Base: Robinson Cano (4.2 WAR)

Third Base: Juan Uribe (2.1 WAR)

Shortstop: Johnny Peralta (2.6 WAR)

Left Field: Marlon Byrd (3.3 WAR)

Center Field: Jacoby Ellsbury (3.8 WAR)

Right Field: Shin-Soo Choo (5.4 WAR)

Designated Hitter: Carlos Beltran (2.4 WAR)

*Like Yoon and Bello, a projection was not available for Jose Abreu.

Starting Lineup WAR: 29.7


Bench: Curtis Granderson (2.0 WAR)

Bench: Omar Infante (2.8 WAR)

Bench: Kevin Youkilis (1.9 WAR)

Bench: Dioner Navarro (3.6 WAR)

Bench WAR: 10.3/3 = 3.4 WAR

*Divided by three per Bench WAR note above.


Starting Pitcher: Masahiro Tanaka (6.4 WAR)

Starting Pitcher: Hiroki Kuroda (2.8 WAR)

Starting Pitcher: Ricky Nolasco (2.6 WAR)

Starting Pitcher: Matt Garza (1.9 WAR)

Starting Pitcher: Bartolo Colon (1.7 WAR)

Starting Rotation WAR: 15.4


Closer: Joe Nathan (0.8 WAR)

Setup: Jesse Crain (0.8 WAR)

Relief Pitcher: Edward Mujica (0.5 WAR)

Relief Pitcher: LaTroy Hawkins (0.4 WAR)

Relief Pitcher: Joaquin Benoit (0.4 WAR)

Left Handed Relief Pitcher: Eric O’Flaherty (0.3 WAR)

Long Relief / Alt Starter: Scott Feldman (1.7 WAR/3 = 0.6 WAR)

*Feldman’s WAR adjusted for new role

**Ryan Webb, John Axford and Matt Thronton all have a projection of 0.4 WAR. Hawkins and Benoit received the spots due to having a higher actual WAR last season.

Bullpen WAR: 3.8



This number crushes the top team projection of 46.7 for the Boston Red Sox. That is all with the weak spots still at the corner infield positions. Now, again, there are some flaws to this, but this is just to have some fun. These two teams really show how weak the free agent market was for most infield positions; especially if you take out the top player. Many of the secondary options are much less appealing.

There were a few surprises with this team as well. First of all, Oliver LOVES Tanaka. There seems to be a bit of a crush for him. Tanaka’s projection would have been the second-best WAR by a pitcher each of the last two seasons (tied for second with AL Cy Young winner Max Scherzer). Also, I was a bit surprised to see Balfour at only 0.2 WAR, and therefore not making the team. He has yet to have a full season below 0.4. The last big surprise was Mike Napoli not being able to make the team, even as a bench player. While Steamer’s projection of 2.0 WAR would have given him the starting first base gig for the Sluggers, Oliver knocks him down to 1.7 WAR, barely missing the cut.

The 2013 Free Agent pool certainly had talent. It would be exciting to see what would happen if a team like this actually came together, but alas, it will never happen. All we can do is sit back and watch as the last few dominoes fall as teams try and fill their final needs with the players that are still available.

Warning! Beware of Nelson Cruz

Lately I’ve been hearing some rumors connecting the Tigers to free agent outfielder Nelson Cruz. I understand how fans have been hungry for another power bat since Prince Fielder was traded, but Nelson Cruz is not the guy you want. It’s not because of the whole PED suspension last year, or even the fact that he single-handedly dismantled the Tigers in the 2011 ALCS. No, it’s simply because he is not that valuable of an all around baseball player.

I don’t particularly enjoy writing pieces where I talk about a player’s shortcomings. At the end of the day, these guys are major leaguers and I’m still a kid who’s a fringe high school bench player who doesn’t know whether he’s a natural right-handed or left-handed hitter (I’m really bad at both). But due to the recent clamoring for Cruz, I figured it was my duty to all my readers to expose the truth about him.

The Good

Nelson Cruz is a solid power hitter. Despite having a shortened season due to a 50 game suspension, Cruz still managed to hit 27 HR in 109 games. With a respectable ISO of .240 in 2013, and a career ISO of .228, Nelson can still manage to hit for very good extra base power. His wOBA in 2013 was .359 and is .353 over the course of his career, both being good. Bottom line, he’s a good power hitter, but I never said that I’m debating that aspect of his game.

The Bad

Nelson Cruz does not have very good plate discipline. Assuming that we’re talking about the guy that’s supposedly going to be “protecting” Miguel Cabrera in the batting lineup, plate discipline does play a huge factor in this discussion. We don’t want a guy who’s a free swinger batting after a walk to the best hitter in the game who also happens to be really slow on the base paths. Last season, Cruz swung at 30.8% of pitches that were outside the strike zone (O-Swing%), which is really bad. He only made contact with 73.1% of the pitches that he swung at (Contact%), which is also bad. His BB/K was also bad, clocking in at 0.32. Bad. What have we learned so far? Basically, Nelson Cruz is an all or nothing hitter, which some fans really don’t mind. In the case that he’d be hitting behind Miguel Cabrera, I’d tend to shy away from a hitter like Cruz.

The Ugly

To an extent, all the bad I mentioned could be forgiven if Nelson Cruz wasn’t such a terrible defensive outfielder. Move him to DH you say? The Tigers have Victor Martinez and Miguel Cabrera who will both rotate time at 1B/DH, so there is no room whatsoever for another DH. Cruz would have to play everyday in RF or LF. He is 34 years old and 240lbs. His ability to chase down balls in open space is clearly declining. Sticking him in the outfield with Torii Hunter, who looked lost in the outfield for most of 2013, would be a horrible idea for a team that used the offseason to vastly improve their infield defense. The stat that I like to use for defense is UZR, but because of Nelson’s shortened season though, I’m going to use UZR/150. Last year, Cruz’s UZR/150 was -6.5, which is way below average. Considering he’s posted a negative UZR for the last three seasons, you can see that he is not very good at defense and is clearly not getting any better. It’s also worth mentioning that the Tigers would have to give up their 2014 first-round draft pick to the Texas Rangers considering Cruz turned down their qualifying offer of $14 million.

Total Value

In 2013, Cruz was worth 1.5 Wins Above Replacement. Andy Dirks 2013 WAR: 1.7. Obviously WAR is not the end-all-be-all statistic, but it does give a pretty good idea of what a player is worth when you replace him with someone who is league average at his position. In this case, the WAR of each player is practically identical, which means over the course of a season they will somehow be worth the same amount of wins to their team. Cruz will probably cost around $7-9 million in 2014, whereas Andy Dirks is already under contract for only $1.625 million. Assuming Cruz signs for $8 million and has the same WAR as 2013, the Tigers would be paying $5.33 million per win for him. Andy Dirks with his current contract and WAR? $956,000 per win. I know this might be some moneyballin’ right here, but if the goal of baseball is to buy wins, wouldn’t you rather have the wins at a cheaper cost?


When all aspects of the game are taken into account, you see that Nelson Cruz is a below-average baseball player with a plus power tool. The Tigers have Miguel Cabrera, Victor Martinez, Ian Kinsler, Austin Jackson, and Torii Hunter (and sometimes Alex Avila too) who will all contribute their fair share of runs this upcoming season. Not only do they not need a one-dimensional power hitter, he just doesn’t make sense for the makeup of their lineup which now features a solid balance of on-base average, power, and speed. Mix that with the huge liability that he is on defense, and you get a player that I don’t want to play for the Detroit Tigers.


For more information from me on the Detroit Tigers, visit

The Draft Pick Compensation Paradox

Last week I looked at the 2014 free agent class and how some of the big contracts of the offseason stacked up against our idea of fair market value. Afterwards, I tried to use this model to predict contracts for Ubaldo Jimenez and Ervin Santana, but came across the problem of factoring in the draft pick compensation, which I left out of my initial article simply because of its complexity. Draft pick value is highly variable, and it gets more difficult to assign costs when a team surrenders multiple draft picks. Regardless, I wanted to take a closer look  because of the impact it will have on the top remaining free agents.

Let’s assume that each team places a dollar value on their first unprotected draft pick ($X). In a vacuum, if a team evaluates a player’s performance as being worth a certain amount of money ($Y) over Z number of years without any draft pick compensation, then they should only be willing to pay $(X-Y) if they will be forced to surrender a draft pick. For example, if the Orioles think that Ubaldo Jimenez would be worth $60M over 4 years, but value their first round pick at $10M, then they should only be willing to pay him $50M for those same four years. Of course this isn’t really fair to the player, but those are the rules.

So, how much do teams value their draft picks at? There’s no way to know for sure, but some research has already been done on the matter. Andrew Ball at Beyond the Box Score explored this question last summer, assigning a dollar value to certain tiers of draft picks. For our purposes, the important ones are the 8-15 draft picks (worth an average of $15.2M of net value) and 16-30 (worth $7.17M). This sounds like it’s in the right ballpark, but seemed a little bit low to me. Sky Andrecheck calculated average WAR by draft pick back in 2009, and found that the 10th overall pick was worth an average of 6.2 WAR, while the 30th pick was worth 3.6 WAR, numbers slightly higher than the more recent study. We also have to account for the fact that a team will pay around 30-35% of a player’s market value while under team control, and that they have to pay an average of $2M to sign a player drafted in the mid-to-late first round.

Taking all of this into account, I’d estimate that the net value of an unprotected first round draft pick can range anywhere from $10-25 Million dollars. This may sound a little bit high, but with the cost of a win at $6-7M, even a player who produces only 0.5WAR per season and costs a total of $10M for those six years of team control can provide $10M of savings. Since the teams signing high-priced free agents are usually pretty good and therefore have a lower draft pick, we’re probably looking at $10-15M in most cases. (Early second round picks might be closer to $8M.)

While this is great in theory, how have the attached draft picks affected the signings so far this offseason? In the table below, I included a more standard model — $6.5M per win with 5% inflation and standard aging (from Jeff Zimmerman’s contract calculator) — along with a modified version of my previous model. I didn’t want to mess with the aging curves so I used the same as Zimmerman (-.5 WAR/year until age-32 season, -.7 WAR/year after), I bumped inflation up to 6%, and I didn’t want to push a win past $7M so instead I gave a slight boost to the players’ WAR projections (just 0.2 WAR). I think it’s fair to assume that the team with the highest bid also expects the player to perform slightly better than projected.

The first two columns show the player and their total salary (assuming no options are vested or picked up by the team). The next three columns represent the “Standard” projection, followed by my “Modified” projection. The top six players were extended qualifying offers, so the signing team had to surrender a draft pick. The bottom eight players had no such compensation attached.

Player Salary Standard: Wins/Salary Standard: Projected WAR Standard: Net Wins Modified: Wins/Salary Modified: Projected WAR Modified: Net Wins
Robinson Cano $240 29.94 24.60 -5.34 26.75 26.35 -0.40
Jacoby Ellsbury $153 20.34 15.15 -5.19 18.38 16.55 -1.83
Shin-Soo Choo $130 17.13 11.50 -5.63 15.45 12.70 -2.75
Brian McCann $85 11.89 11.65 -0.24 10.84 12.65 1.81
Curtis Granderson $60 8.57 4.60 -3.97 7.85 5.40 -2.45
Carlos Beltran $45 6.60 3.30 -3.30 6.07 3.90 -2.17
Draft Pick: Total $713 94.46 70.80 -23.66 85.34 77.55 -7.79
Jhonny Peralta $53 7.66 6.80 -0.86 7.02 7.60 0.58
Matt Garza $50 7.16 8.00 0.84 6.56 8.80 2.24
Ricky Nolasco $49 7.01 5.00 -2.01 6.42 5.80 -0.62
Omar Infante $32 4.92 3.60 -1.32 4.15 4.20 0.05
Scott Feldman $30 4.80 4.60 -0.20 4.08 5.20 1.12
Carlos Ruiz $26 4.13 6.30 2.17 3.50 6.90 3.40
James Loney $21 3.32 1.80 -1.52 2.82 2.40 -0.42
Jarrod Saltalamacchia $21 3.32 3.75 0.43 2.82 4.35 1.53
No Draft Pick: Total $282 42.31 39.85 -2.46 37.37 45.25 7.88

Regardless of which model you use, the conclusion is the same: so far this offseason, players who have cost the signing teams a draft pick have actually made more than the models predict. Much more. On average, these six players have been overpaid by about $9 million, while players with no draft pick compensation attached have actually been underpaid by an average of $7 million. This is the complete opposite of what we would expect if teams are acting rationally when it comes to the cost of their draft picks. When forced to pay what is essentially a $10M fee, these teams not only didn’t penalize the player, but actually paid them more. This could mean one of a few things:

Teams are willing to pay a premium for “elite” talent. The six players with free agent compensation attached include the only four free agents projected to be worth at least 3 WAR in 2014, along with the two next-best available outfielders. While Dave Cameron has long espoused the idea that the cost of a win is linear and there is no “bonus” for elite players, the fact that these six players haven’t been penalized for the attached draft pick tells us that teams may be willing to pay more to land the big guns. This could have to do with elite players (and their agents) being unwilling to take a discount because of the attached draft pick and there being at least one team who will cave and give the big contract, essentially ignoring the additional cost. This brings us to the second possibility:

Teams are not acting rationally with their draft picks. No prospect is a sure thing, so it could be easy for a team to talk itself into giving up a hypothetical player who may never make the majors in order to get a stud on their roster for the upcoming season. There are a lot of other factors here, notably the fact that signing team is usually at a high-leverage spot in the win curve and doesn’t know where they will be when the draftee they are giving up would be ready to contribute. Texas, for example, has a few players locked up long term, but also has some key pieces (Darvish and Beltre) who could be gone in a few years. Positional needs also certainly play a role here, but even when a team is willing to spend big money to improve in the short term, it’s tough to argue that they couldn’t have allocated their money better by upgrading at several other positions for the same cost (as Dave Cameron argued earlier this week). The Rangers, for example, could have kept David Murphy (2 years, $12M), signed Chris Young (1/$7M) for outfield depth, improved behind the plate with Jarrod Saltalamacchia (3/$21M), and bolstered their rotation with Matt Garza (4/$50M) instead of signing Choo, saving $40M and a first-round draft pick. The last possibility is that…

Something is wrong with the model. The other difference between the six players with a draft pick attached and the remaining eight is the length of the contract (an average of 6 years vs 3.5 years). If the teams signing these contracts expect the cost of a win to increase faster than the 5-6% inflation rate we project, then the middle and later years of this contract look a little bit better, but not by much. The only way to make the draft-pick contracts look better is if the players age much more gracefully than the average player, a pretty big risk to take on a $100 Million investment. The model also doesn’t account for any impact the signings may have on ticket sales. Five of the six big contracts came from big-market teams with lucrative TV deals, and teams may be willing to pay a premium to invigorate their fanbase with the addition of an elite player that might not be accomplished by signing a few mid-tier free agents who might add the same total value to the team. While I can’t speak to the economics, we all know that at the end of the day, the most important thing for the fans is to win.

While this is an interesting phenomenon, it doesn’t help us predict the kind of contracts the remaining free agents will get. As we saw with Kyle Lohse last year, while teams may be willing to look past the loss of a draft pick for an elite player, they might not if player in question is closer to league-average. While the free agents with a draft pick attached have actually signed for significantly more than market value, I wouldn’t expect to see this trend continue this offseason. With most of the contenders’ rosters pretty much ready for the season, they’ll only sign that extra piece if the price is right, including the loss of the draft pick. When it comes to players like Nelson Cruz and Kendrys Morales who may only generate $20M of value (2-3 WAR) over the next two years, the $10+ Million valuation of a draft pick explains why the market for them has been so slow. While things worked out fine last year for all of the free agents who turned down their qualifying offer, we could see a couple players really suffer this year, which may make agents — and teams — think twice about the qualifying offer next offseason.

Another Look at Tom Glavine’s Generous Strike Zone

Jeff Sullivan recently suggested that despite his reputation Tom Glavine did not pitch to a significantly more generous strike zone. Sullivan points out Glavine did not get significantly more called strikes than other pitchers, even during the peak of his career. Sullivan’s analysis piqued my interest and made me wonder if Glavine’s reputation for getting a wider strike zone helped him succeed in ways beyond called strikes.

Glavine’s reputation alone likely influenced a batter’s behavior at the plate, encouraging batters who were behind the count to swing at questionable pitches. Batters believed if they did not swing these pitches would be called strikes for Glavine (when a batter swings at a pitch out of the zone when the batter is ahead of the count that has more to do with a pitchers stuff than the batter giving the pitcher an expanded zone). So, what would we expect from a pitcher who is getting batters to expand the strike zone? You would expect batters to make poor contact, yielding a lower BABIP. The batter would most likely swing at pitches outside the zone when the batter is behind the count.

Based on this reasoning, I hypothesize that Tom Glavine will see a greater reduction in quality of contact when he gets ahead of the count than a league-average pitcher. I’m going to look at the time span from 1991 to 2002 because that was the time span Jeff looked at and because I like palindromes.

To measure quality of contact I will be looking at BACON (batting average on contact). BACON is slightly different than BABIP because BACON includes home runs. If batters are expanding the strike zone when Glavine is ahead in the count we should see the quality of contact decrease. To measure the decrease in quality of contact, I will look at the ratio of BACON when Glavine is ahead to BACON to when Glavine is behind (the lower the number the greater improvement the pitcher experiences by getting ahead in the count). I will refer to this measure as EXP (a lower EXP shows a greater decrease in quality of contact, an EXP above 100 shows an increase in quality of contact).  The graph below compares Glavine’s EXP to the league average EXP for each season during the 11-year span.

 The league-average EXP is consistent year to year, hovering around 91, which suggests batters expand the strike zone for most pitchers when batters are behind in the count. Glavine’s EXP is not always better than the league-average EXP. In ‘94 and ‘96 Glavine was actually worse when ahead in the count than when he was behind.  This is to be expected because BACON takes a while to stabilize. Looking at Glavine’s data for a single season is subject to a fair amount of random noise because you have a relatively small sample of data. One season for Glavine gives us about 170 fair balls with Glavine ahead and 280 fair balls with Glavine behind. However, over a larger sample BACON stabilizes. At around 2,000 fair balls (more than in a single season for Glavine) BACON stabilizes. For example, when looking at the league-average EXP for a full year BACON is stable — with 3,500 fair balls with the pitcher ahead of the count and 4,600 fair balls with pitcher behind the count.

To make sure we are not just attributing skill to some random variation we need to look at a larger sample for Glavine. Over the 11 year span form 1991-2002 Glavine induced weaker contact (lower BACON) than the league average both when he was ahead of the count and behind the count. This is not surprising as we would expect a good pitcher to be better than average ahead and behind the count.  What’s interesting is Glavine has better than league-average EXP  (87 vs. 92) which suggests Glavine is better at expanding the strike zone than league-average pitchers. This comes with the caveat that while we have 3,056 fair balls when Glavine is behind the count, we only have 1,853 fair balls when Glavine is ahead — just shy of the 2000 at which the measure should stabilize.  Even so, the difference between Glavine’s EXP and the league-average EXP is very convincing.

Glavine (1991-2002)

MLB ave (1991-2002)

Ahead Behind EXP Ahead Behind EXP







To stabilize BACON, I increased the sample by looking at all the balls put in play. I compared balls put in play when the pitcher had two strikes to balls put in play when the pitcher had fewer than two strikes, which led to EXP2: the ratio of BACON when a pitcher has two strikes, to when he has fewer than two strikes. The table bellow shows a comparison of the quality of contact in two strike counts to non-two strike counts.

Glavine (1991-2002)

MLB ave (1991-2002)

2 Strikes Not 2 Strikes EXP2 2 Strikes Not 2 Strikes EXP2







Even with this larger sample size Glavine’s BACON is still lower than the league average in respective counts. More importantly, his EXP2 is still better than league average (although higher than his EXP).  Pitchers in general try to induce weaker contact when they are ahead of the count, but the data shows Glavine is doing something special to induce even weaker contact.

Is Glavine getting batters to give him a wider strike zone? We cannot definitively say what is causing this pattern in the data, but we are seeing the type of numbers we would expect to see if the batter was giving him a wider strike zone.


All splits number are from Baseball-Reference.

The Curious Case of Jason Castro

As we look for candidates to regress in 2014, a popular choice is Houston catcher Jason Castro for it seems the Astros backstop has two targets on his back: a high strikeout rate last year of 26.5% and a high BABIP of .351. Steamer and Oliver both project a steep drop in BABIP that will drag his batting average from a solid .276 to the .250s. As Brett Talley wrote, Castro screams regression.

Or does he?

Talley points to Castro’s strikeout rate that has been topped only 61 times in the past decade, and only four times the player matched or bettered a batting average of .276. But that measure may miss the mark. No one is suggesting Castro’s strikeout rate will worsen. When it comes to batting average, the critical question, then, is whether he can come close to maintaining a high BABIP.

On that question the evidence is more promising. In the last decade, only 38 of 1,509 batters have had an infield-fly rate lower than Castro’s 1.8%. Only 47 had a line-drive rate higher than Castro’s 25.2%. Taken together, those two select groups actually have 10 matches — players who managed both a lower infield-fly rate and higher line-drive rate. Here they are along with their BABIP, batting average and strikeout rate:

Player, year, BABIP, Avg., K-rate

Joe Mauer, 2013, .383, .324, 17.5%

Joey Votto, 2011, .349, .309, 12.9%

Howie Kendrick, 2011, .349, .297, 17.3%

Matt Carpenter, 2013, .359, .318, 13.7%

Michael Young, 2007, .366, .315, 15.5%

Joey Votto, 2013, .360, .305, 19%

Adam Kennedy, 2006, .313, .273, 14.3%

Bobby Abreu, 2006, .366, .297, 20.1%

Michael Young, 2011, .367, .338, 11.3%

Chris Johnson, 2012, .354, .281, 25%


What might we gather from this evidence?

(1) All but one of the players topped .276.

(2) The skills involved seem somewhat repeatable: Votto and Young each appear twice and as a group they generally in their careers combined a high LD rate, low IFFB rate and a high BABIP.

(3) We wouldn’t expect a player who whiffs a quarter of the time to have a batting average as high as someone who strikes out half as much while putting up similar LD and IFFB rates. Castro is unlikely to approach the median average of this group of .307.

(4) Castro doesn’t need to approach the median average to avoid significant regression. He is more likely to hit closer to last year’s mark than he is to hit in the .250s.

Do Closers Need to Throw Hard?

I recently wrote about teams no longer paying a premium to land closers with 9th inning experience, instead choosing to spend less and acquire very good relievers with little 9th inning experience.  It seems teams have moved away from the conventional thinking that a closer must have experience or a special mentality in order to succeed as a closer. This made me wonder whether the view that a closer must have to throw hard was still alive. It is important to note that throwing harder certainly gives the pitcher an advantage, but it is also very possible to succeed without being among the hardest throwers. In order to look at this, I looked at all Relief Pitchers with at least 10 saves from 2010-2013 and separated them into two groups based on their average fastball velocity (aFV), based on P/Fx. The aFV for the entire group of 93 pitchers was 93.0. I chose 93 as the divider between High Velocity (HVelo) closers and Low Velocity (LVelo) closers.

Looking at the breakdown of the two groups, the HVelo group included 53 relief pitchers and the LVelo group included 40 relief pitchers. The difference of 13 pitchers between the groups should not affect the results too much, as the sample is big enough to negate this discrepancy. However, the difference does say something about closers during this period, as there were many more hard-throwing closers than low-velocity closers. Looking into the numbers between these two groups for this four-year period, it is clear that the HVelo pitchers were more effective. They averaged 15 more saves over that period and outperformed the LVelo pitchers in every statistic, except BB/9 and BABIP. LVelo pitchers walking fewer batters per nine innings is not surprising, as they usually have better command in order to compensate for fewer strikeouts. HVelo closers were also better at fulfilling their role, as they had a 81.7% conversion rate, while LVelo closers converted just 77.5% of their opportunities. If you look at this four-year window it is clear that the harder-throwing closers have been more successful and there have also been many more hard throwers used in the 9th inning than LVelo relievers.

However, if we take a look at just the final year of this four-year period, we see something different. Looking only at 2013 and relief pitchers that had at least 10 saves, I broke the pitchers into two groups using the same criteria as before: HVelo is all pitchers with aFV higher than 93 mph and LVelo is all pitchers with aFV below 93 mph. This is the same cutoff as for the four-year period because the mean is relatively unchanged, at 92.8. Unlike from 2010-2013, these two groups were essentially even: of the 37 qualified pitchers, 19 were in the HVelo group and 18 were in the LVelo group. This alone shows that teams are more comfortable using effective relievers in the 9th inning, even if they do not light up the radar gun.

Just using more LVelo pitchers does not actually prove they are as effective or better than HVelo relievers, but it does show teams may be moving away from the conventional belief that closers must throw hard. When I looked at the numbers of these two groups, I saw evidence that the LVelo group was certainly as effective, if not more effective, than the HVelo group. The HVelo group saved just one game more on average; however, their save percentage was 87%, compared to the 88.7% of the LVelo group. Just as before, the LVelo outperformed the HVelo group in BB/9 and BABIP, but they also had a better average ERA than the HVelo group. While the HVelo pitchers had a much higher K/9 (10.7 vs. 8.4) and a better HR/9, the LVelo group did a better job at preventing runs and also a slightly better job at converting their save opportunities.

Certainly, looking at just one season is not a very large sample, but I believe last season was the beginning of a trend. The role of the closer has evolved quite a bit in recent years and many long-held beliefs are being dispelled. I believe teams have realized that a pitcher does not have to be the hardest thrower in the bullpen, instead he just needs to be the most effective. In 2013, both teams that reached the World Series turned to closers without previous experience and who were both among the LVelo group. The Cardinals chose to give Edward Mujica the closer’s role, instead of turning to young flamethrower, Trevor Rosenthal. Mujica turned in a fantastic season with 37 saves and a 2.78 ERA. The Red Sox also entrusted their 9th inning duties to a member of the LVelo group, Koji Uehara. Uehara took over as closer after both of the Red Sox’s other options suffered season-ending injuries, but Uehara still totaled 21 saves and a 1.09 ERA. Both these closers overcame common beliefs that closers need experience in the 9th inning to succeed and must also throw hard.

* I would have liked to look at a larger sample than 2010-2013, but I did not feel comfortable using Pitchf/x data older than 2010. Since its inception in 2006, Pitchf/x has vastly improved and become much more accurate.  

* This post has also been posted on my personal blog,

What the Red Sox are Getting in Grady Sizemore

The Red Sox have made news, signing Grady Sizemore to a Major League contract worth $750k ($6 million if all incentives are factored in).  This got me thinking about what happened to Sizemore.  He made the game of baseball seem simple with his defensive prowess, his above average power, and his lightning speed.  Then one day, his aging body realized that the kind of aggressive player that he had been would no longer work and it started giving in to the high strain that he put it under.  He had a hernia surgery as well as several knee and back surgeries between 2010 and 2013 which seemed to end his baseball career.  Then out of the blue he was picked up by the Red Sox in a deal that has high potential for both sides; the Red Sox could get a great player for cheap and Sizemore could resurrect his career.  This deal could end poorly for Sizemore, who could finally realize that his career is over either from injury or performance reasons while the Red Sox will view it as a failed experiment that doesn’t hurt them financially now or in the long term.

The signing of Grady Sizemore is an indication that they are ready to give Jacoby Ellsbury’s former job over to Jackie Bradley Jr., but it also shows that they are prepared with a backup plan in case that doesn’t pan out.  Some would say that Sizemore is hardly a backup plan as he could very well end up injured, which is absolutely true, and that an outfield of Gomes LF, Victorino CF, and Nava RF would happen in the event of Bradley turning out to be a dud.  But with Sizemore comes a tremendous amount of upside.  Five years ago he was a 30-30 player and a gold glover in the outfield.  He was healthy, he was starting to walk more and strike out less, and then everything stopped for him.  He was forced to undergo elbow surgery in 2009, an injury that had plagued him all season long, and from that point on if it wasn’t one problem then it was another.  Left knee surgery, right knee contusion, hernia surgery, back surgery, and then a right knee surgery came all in a span of three years which can leave a player asking whether or not their career is over.

The question that should also be brought to the attention about Sizemore is what his plate discipline will be like.  Sizemore’s BB/K reached its peak in 2008 with a .75 BB/K, dropped to .65 in 2009, and then plummeted to .245 in the combined 104 games in 2010 and 2011.  For most of his career, it seemed that Sizemore was above average at walking and avoiding strikeouts as his career BB/K was .53, .05 above the Major League average during that time period of .48.  Now did the drop come about as a result of the injuries that he suffered from 2009 to 2011 or did they just come as a result of him losing his ability?  The interesting thing about his BB/K having such a drastic change is that his swing percent rarely changed.  His career Swing% is 43.4% which is fairly decent considering that between 2004 and 2011, the average swing rate among players was 47.6%.  Sizemore also made contact with the baseball at an 81.1% rate over the course of his career with the contact rate dropping barely below that number in the three shortest years of his career (2004, 2010-2011).  Those were also the only years that his swinging strike percent exceeded 10%.  Perhaps what this shows is that pitchers weren’t afraid to attack him and he wound up taking a lot of called strikes.

The other facets of his game that must be viewed at with a lot of importance are his power and speed.  I truly believe that if Sizemore can stay healthy, then we will see a resurgence of his power.  His power numbers have always been impressive, with a career ISO of .204 and career SLG of .473.  Even in 2011 when he was limited to 71 games and was coming off of microfracture surgery in his left knee, he produced an ISO of .198.  I don’t think power will be an issue for him.  The other major part of his game that will likely never return is the speed.  In those 71 games of 2011, he stole 0 bases after averaging 19 swiped bases per season and stealing at least 22 bases in 4 of his 7 seasons prior to 2011.  With the second knee surgery having occurred in 2012, my guess is that little to no speed will be found from him in 2014.

As with everything in baseball, there are the intangibles that must come into consideration when discussing the future of Grady Sizemore.  For starters, he has not set foot onto a baseball field in 2 years.  It is a possibility that he will be incredibly rusty and might struggle to perform again at the big league level.  For some players, that would be less of a concern but for a player who last played baseball in his twenties and who is now playing in his thirties (granted, it was his late twenties and it will be his early thirties), it could pose a greater challenge.  It’s possible that he could shake all rust in Spring Training and come out in April and prove all the doubters wrong although it is impossible to know for sure.

The most optimistic yet realistic scenario for Sizemore is that he comes back to the majors, is solid defensively, and puts up great power numbers for the Red Sox.  My guess is that from the knee and back surgeries, his base stealing days are over and he will not be able to cover as much ground in the outfield that someone else might.  If I was Red Sox management, I would not give him the role of backup center fielder until I knew for sure the kind of speed that he has left.  I would task Shane Victorino with that as he has remained healthy and still has the speed to cover that ground.  Victorino would play center and when he does then Sizemore would be in left field and Gomes/Nava would be in right field.  If Bradley fits in with the Red Sox plan, then Sizemore just becomes a spot starter/platoon player in left, center, and right field only to give people a break when they need it.  So to answer the question that the title of this article poses: the Red Sox are getting a wild card, a player with the potential to be a power bat off the bench or even in the everyday lineup or a player that has played his last days in the bigs.

Comparing Kershaw and Tanaka’s Opt-Out Clauses

This post is going to examine the value of the opt-out clause in both the Clayton Kershaw and Masahiro Tanaka contracts. I think this is interesting because the Yankees gave Tanaka an opt-out one year earlier, and gave that option to a commodity with a much more uncertain value.  As we will see, the opt-out clause for Tanaka is going to be a lot more costly to the Yankees than the clause was for Kershaw and the Dodgers.

Let’s start with the projections for each player. ZIPS and STEAMER don’t have anything for Tanaka, but we can make a guess based on the contract he was given that he’s at least expected to be worth a lot of wins over the next several years.  Since he’s the same age, it seems approximately fair to start with 5 wins, and reduce in the same pattern that Kershaw got.  I’ll use the values from Dave Cameron’s excellent article the other day for Clayton Kershaw, and I’ll also take the $/WAR from his projected inflation.  Excess value is the value of that player’s WAR, minus salary.

Tanaka Kershaw
AGE WAR $/WAR Salary Excess Value AGE WAR $/WAR Salary Excess Value
25 5.0 6.0 22 8.0 25 5.5 6 30 3.0
26 5.0 6.3 22 9.5 26 5.5 6.3 30 4.7
27 4.5 6.6 22 7.7 27 5 6.6 30 3.0
28 4.5 6.9 22 9.1 28 5 6.9 30 4.5
29 4.5 7.3 22 10.9 29 5 7.3 30 6.5
30 4.0 7.7 22 8.8 30 4.5 7.7 30 4.7
31 4.0 8.0 22 10.0 31 4.5 8 30 6.0

The key here is not going to be the expected value — it’s going to be the possible variation. Kershaw is expected to get 5.5 wins next year because of the ever-present risk of injury — there are probably Dodgers fans going nuts over that projection because they know that a healthy Kershaw, pitching like he can, is going to be worth closer to 7 wins.  There are certainly scenarios where he manages that, but also scenarios where he tears his rotator cuff and is worthless.  While there is a continuum of possibilities, let’s break the world into two scenarios for each pitcher, an up and a down. The only requirement is that the weighted average of each scenario has to average out to their projections.  I’ve made up some basic numbers here, and you might think they’re reasonable, you might think they’re not, but the point of this article is to illustrate how one extra year and some extra volatility can affect the value of an opt-out clause.

In each scenario, I make the downside a mirror image of the upside. For Tanaka, because he is an unproven commodity, I’ve added 2 WAR to the upside, and subtracted 2 for the downside. For Kershaw, I’ve just added/subtracted 1 for each. I gave each scenario a 50-50 chance of happening.

GOOD Tanaka-50% GOOD Kershaw-50%
AGE WAR $/WAR Salary Excess Value AGE WAR $/WAR Salary Excess Value
25 7.0 6.0 22 20.0 25 6.5 6 30 9.0
26 7.0 6.3 22 22.1 26 6.5 6.3 30 11.0
27 6.5 6.6 22 20.9 27 6 6.6 30 9.6
28 6.5 6.9 22 22.9 28 6 6.9 30 11.4
29 6.5 7.3 22 25.5 29 6 7.3 30 13.8
30 6.0 7.7 22 24.2 30 5.5 7.7 30 12.4
31 6.0 8.0 22 26.0 31 5.5 8 30 14.0


BAD Tanaka-50% BAD Kershaw-50%
AGE WAR $/WAR Salary Excess Value AGE WAR $/WAR Salary Excess Value
25 3.0 6.0 22 -4.0 25 4.5 6 30 -3.0
26 3.0 6.3 22 -3.1 26 4.5 6.3 30 -1.7
27 2.5 6.6 22 -5.5 27 4 6.6 30 -3.6
28 2.5 6.9 22 -4.8 28 4 6.9 30 -2.4
29 2.5 7.3 22 -3.8 29 4 7.3 30 -0.8
30 2.0 7.7 22 -6.6 30 3.5 7.7 30 -3.1
31 2.0 8.0 22 -6.0 31 3.5 8 30 -2.0

Let’s think about what happens in each scenario when it comes time to exercise the opt-out clause.  Shockingly, GOOD Kershaw and GOOD Tanaka each exercise the clause. We can see this reflected in the positive “excess value” column of each chart — age 29 for Tanaka and age 30 for Kershaw. They could get more on the free market, so they will. BAD Kershaw and BAD Tanaka both stick with their contracts, because they’re being paid more than market value.  Let’s re-do the charts from the teams’ perspectives, reflecting the opt-out clauses now:

GOOD Tanaka-50% GOOD Kershaw-50%
AGE WAR $/WAR Salary Excess Value AGE WAR $/WAR Salary Excess Value
25 7.0 6.0 22 20.0 25 6.5 6 30 9.0
26 7.0 6.3 22 22.1 26 6.5 6.3 30 11.0
27 6.5 6.6 22 20.9 27 6 6.6 30 9.6
28 6.5 6.9 22 22.9 28 6 6.9 30 11.4
29 0.0 7.3 0 0.0 29 6 7.3 30 13.8
30 0.0 7.7 0 0.0 30 0 7.7 0 0.0
31 0.0 8.0 0 0.0 31 0 8 0 0.0


BAD Tanaka-50% BAD Kershaw-50%
AGE WAR $/WAR Salary Excess Value AGE WAR $/WAR Salary Excess Value
25 3.0 6.0 22 -4.0 25 4.5 6 30 -3.0
26 3.0 6.3 22 -3.1 26 4.5 6.3 30 -1.7
27 2.5 6.6 22 -5.5 27 4 6.6 30 -3.6
28 2.5 6.9 22 -4.8 28 4 6.9 30 -2.4
29 2.5 7.3 22 -3.8 29 4 7.3 30 -0.8
30 2.0 7.7 22 -6.6 30 3.5 7.7 30 -3.1
31 2.0 8.0 22 -6.0 31 3.5 8 30 -2.0

Now let’s take the expected value of these two scenarios, which is in this case a simple average:

Expected Value Tanaka Expected Value Kershaw
AGE WAR $/WAR Salary Excess Value AGE WAR $/WAR Salary Excess Value
25 5.0 6.0 22 8.0 25 5.5 6 30 3.0
26 5.0 6.3 22 9.5 26 5.5 6.3 30 4.7
27 4.5 6.6 22 7.7 27 5 6.6 30 3.0
28 4.5 6.9 22 9.1 28 5 6.9 30 4.5
29 1.3 7.3 11 -1.9 29 5 7.3 30 6.5
30 1.0 7.7 11 -3.3 30 1.75 7.7 15 -1.5
31 1.0 8.0 11 -3.0 31 1.75 8 15 -1.0

We can see that in both cases, the post-option years of the contract become negative propositions for the teams — in fact, they would have to be, by how we’ve implicitly stated the conditions under which the players opt out: if the player were expected to provide positive value to his team, he would opt out.

So how much is the option worth? Ignoring the $20 million posting fee, the Tanaka contract, sans opt-out, was expected to produce $63.9M in excess value for the Yankees. With the option, the expected excess value drops down to $26.1M.  That’s a drop of $37.8M. This could be thought of as the extra money Tanaka puts into his pocket from years 5 onward, if he comes into the league and becomes Justin Verlander.  Kershaw, on the other hand, would be expected to generate $32.3M for the Dodgers, without the opt-out. Now his contract is only worth $19.1M to them. That’s a reduction in value, but because we’ve made him less uncertain, and because the option occurs after year 5, not year 4, the reduction is only $13.2M.  So the extra year and the double variability make Tanaka’s option worth $24.6M more than Kershaw’s.

Again, this depends largely on the choices I’ve made for the range of possible outcomes, and I’ve kind of picked Tanaka’s projection out of thin air (since the excess value of the contract with the opt-out is only $6.1M, considering the $20M posting fee, I would argue that I’m not that far off). I could have made more possible outcomes, or maybe even defined a probability distribution function and integrated over that, if I knew how to do that sort of thing. The only lesson we’re going to be able to take from this is how one year and some extra variability affect the value of the opt-out clause.

Great Game Survey

Hi Baseball fans,

I’ve been working on a project with some students of mine at Middlebury College. It’s a survey that looks at the factors that make a particular baseball game great. We are trying to get as many responses as possible. We have about 260 right now. It just takes about 10 minutes and will get you thinking.

The URL is below

If the link, doesn’t work, just paste it into your browser.

If you have any questions, feel free to email Matt Kimble at Also send an email to Matt Kimble if you are interested in getting a summary of the results sometime in February.


Contract Modeling for the 2014 Free Agent Class

After Matt Garza reportedly signed with the Brewers for $52 Million over 4 years today, the initial response was that it was a steal. Baseball writer Joe Sheehan tweeted that the signing was “Grand Theft Pitcher“. Sure, a day after the Yankees spent $175 Million on a big question mark, the price for Garza looks like a bargain. Upon closer analysis, however, the deal appears to be pretty close to what we should expect given what we know about the cost of a win, inflation, and aging curves. This can be seen by using the same model that Dave Cameron writes about so frequently.

Year Salary (M) Cost of Win (M) Wins / Salary Steamer WAR
2014 $13 $6.00 2.17 2.8
2015 $13 $6.30 2.06 2.3
2016 $13 $6.62 1.97 1.8
2017 $13 $6.95 1.87 1.3
Total $52   8.07 8.20

This model assumes that in 2014, a win costs $6 million dollars, and that the cost of a win will increase by 5% each year. Steamer projects Garza for 2.8 WAR in 2014, and I subtracted 0.5 WAR each year to account for age-related decline. As with the Kershaw contract, the model pretty much nails the cost for four years of Garza. The deal appears to be slightly team-friendly, with the Brewers getting 0.13 wins of value over the course of the contract. Put in money terms, they saved about $800K for Garza’s expected production. His health concerns (he has totaled 259 innings in the past two seasons) mean extra risk for the team, making it tough for me to get really excited about the contract. According to the model, the Brewers pretty much paid market value for Matt Garza.

But despite the numbers in front of me (and you), the contract does feel like a bargain. Why is this the case? This brought me to the greater point of this article, which was to try to find out the real market value for the 2014 free agent class. To do this, I applied the same model explained above to the 14 major contracts that have been signed this offseason by MLB free agents. These contracts are all include at least 3 years and $20M guaranteed, and total nearly $1 Billion. This leaves out relievers (which never quite fit into the model), injury-prone bounce-back candidates like Josh Johnson, and of course Masahiro Tanaka (since he’s extremely difficult to project). Ten of the fourteen players are between the ages of 29 and 31. For 2014 WAR, I used an average of Steamer and ZiPS (where available), and in the few instances where there was a team option or buy-out, I included the cost of the buy-out in the final year of the contract, as players in their mid-30s are rarely worth the cost of the option year. Lastly, rather than projecting the money a player should have earned, I simply calculated the WAR that a player is being paid to be worth (Wins / Salary) and compared it to their projected WAR for the duration of the contract. Without further ado, the table:

Player Salary (M) Wins / Salary Projected WAR Net Wins
Robinson Cano $240 32.43 31.00 -1.43
Jacoby Ellsbury $153 22.03 17.15 -4.88
Shin-Soo Choo $130 18.55 9.80 -8.75
Brian McCann $85 12.88 12.25 -0.63
Curtis Granderson $60 9.28 5.80 -3.48
Jhonny Peralta $53 8.29 8.00 -0.29
Matt Garza $52 8.07 8.20 0.13
Ricky Nolasco $49 7.59 5.60 -1.99
Carlos Beltran $45 6.58 4.05 -3.25
Omar Infante $32 4.92 4.60 -0.32
Scott Feldman $30 4.80 4.80 0.00
Carlos Ruiz $26 4.13 6.90 2.77
James Loney $21 3.32 1.80 -1.52
Jarrod Saltalamacchia $21 3.32 3.75 0.43
Total $997 146.20 123.70 -23.22

While your first instinct may be to declare most of these contracts huge overpays, the fact of the matter is that if everything appears to be an overpay, we need to adjust our baseline. According to the model, teams have paid for 146 wins, but are only projected to get back 124. What could account for the difference between the model and reality? On one hand, we have to consider the fact that every team values a win slightly differently. The Yankees have a huge incentive to put together a competitive team or they risk alienating an impatient fanbase. A win is worth more to a team on the brink of contention than a team sitting at the bottom of its division. This could be driving much of the variation, but is impossible to fully account for.

This leaves us with four factors that could cause the discrepancy between the model and the market that we can adjust for. First is the initial evaluations of the players. For instance, Shin-Soo Choo is coming off of a 5.2 WAR season, but is projected for just 2.9 WAR by Steamer. If we pencil Choo in as a 3.5 WAR player in 2014 (Oliver has him at 5.4), then he is set to produce 14 WAR during his 7-year contract, and be worth “only” -4.55 wins relative to his contract. The second is player aging. Taking off half a win each year is a quick and relatively accurate way to calculate future WAR for players who are already around 30 years old. However, some research has suggested that elite players may peak later and/or decline slower, which could affect many of these high-priced free agents (at least for the first few years of the contract).

The third and fourth variables are the cost of a win in the present and in the future. We’re using $6 Million per win, but other research has suggested that a win may cost more like $7 Million. In addition, the model increases the cost of a win by 5% each year, and some teams might suspect that rate to be higher with all the additional money flowing into the league.

After fixing the biggest outlier of the table (by projecting Choo for 3.5 WAR in 2014), these are the adjustments that would have to be made to a single variable (with all others held constant) to give us a model that properly values this free agent class so far:

Player Evaluation: The team signing the contract expects the player to perform roughly 0.23 WAR better than the Steamer/ZiPS projects in 2014.

Player Aging: The team signing the contract expects the player to decline at roughly 0.37 WAR per season.

Present Cost of a Win: One win (+1 WAR from a player) is currently worth $6.9 Million on the open market.

Future Cost of a Win: The cost of a win is expected to increase by 11.5% each year for the life of the contracts.

As is usually the case, the truth probably lies somewhere in between, with a little bit of each. In some cases, the driving force may be different for each team and each contract. The Mets may have signed Granderson believing that he can be worth 2.6 WAR in 2014 (as opposed to 2.2 from the projection systems), while the Mariners may have agreed with Steamer and ZiPS that Robinson Cano will be worth 5.35 WAR in 2014, but might project him for a slightly slower decline.

Just for fun, I’ll take a shot at modifying the model with a few minor adjustments so that the expected wins purchased matches the expected production. For my updated model, I’ll use the following parameters: Steamer/Zips are accurate measures of current talent, the players signed will decline 0.45 WAR per season after 2014, a win currently costs $6.4 Million, and the cost of a win will rise by 6% in the foreseeable future. Here’s the adjusted table:

Player Salary (M) Wins / Salary Projected WAR Net Wins
Robinson Cano $240 29.26 33.25 3.99
Jacoby Ellsbury $153 20.10 18.20 -1.90
Shin-Soo Choo $130 16.90 15.05 -1.85
Brian McCann $85 11.86 12.75 0.89
Curtis Granderson $60 8.58 6.10 -2.48
Jhonny Peralta $53 7.68 8.30 0.62
Matt Garza $52 7.46 8.50 1.04
Ricky Nolasco $49 7.02 5.90 -1.12
Carlos Beltran $45 6.64 4.05 -2.59
Omar Infante $32 4.54 4.90 0.36
Scott Feldman $30 4.46 4.95 0.49
Carlos Ruiz $26 3.83 7.05 3.22
James Loney $21 3.08 1.95 -1.13
Jarrod Saltalamacchia $21 3.08 3.90 0.82
Total $997 134.49 134.85 0.36

Reducing the rate of decline and increasing the cost of a win helps out the longer contracts quite a bit, so Robinson Cano’s contract starts to look a lot better. However, the net benefit is largely offset by committing such a massive amount of money to a single player who could get seriously injured or decline sooner than expected. With the new model, the Garza deal looks more like a bargain (although I would still hardly call it a steal), and a few contracts that looked like a market value or a slight overpay appear to be more team-friendly than initially anticipated (McCann, Peralta, Infante, Feldman, and Saltalamacchia). Carlos Ruiz looks like a downright steal. Keep in mind that even just netting half a win translates into an extra $3 Million of value, so we’re talking about a pretty significant savings here.

In closing, Cameron’s quick-and-dirty model works quite well, but given the contracts signed so far this season, appears to require some minor adjustment. It’s impossible to know which of the factors require adjusting and how they vary from one team to another, which is what makes projecting these contracts and determining whether a contract is a bargain or an overpay so difficult. As is always the case, only time will tell, and as more free agents sign we’ll be able to see if the new model checks out and make necessary adjustments.

All projections are from Steamer and ZiPS. Contract information is from Fangraphs and Baseball-Reference.