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The second of a three-part series.

One particular area of concern in my attempt to develop a new, more accurate formula for MORP is how to price wins above replacement level for superstars, players who add several wins above replacement level. The current alternative to MORP, found at FanGraphs.com, lists a player’s value using its win statistic, WAR. They do this by approximating a price of how many \$/WAR teams pay on average on the free-agent market and multiplying it linearly by WAR to find that value. While I have a number of concerns about that methodology, this particular choice seems worth exploring.

As it currently stands, MORP is not linear with respect to WARP. In other words, if you take a player with 4.0 WARP, like Jason Bay, his MORP is more than twice as high as a player with 2.0 WARP, like Johnny Damon. This made some sense at the time the study was done, since WARP previously used a much lower replacement level. Thus, players who produced a WARP below 3.0 using the old replacement level were all probably paid close to the major-league minimum salary, as they were probably all pretty close to replacement level. For players between 3.0 and 6.0 WARP using the old replacement level, teams would start paying more for wins as WARP increased, since these players were actually above replacement level.

However, with a higher replacement level, this makes less sense as an assumption and is worth testing. Nate Silver‘s original formula for MORP logically had salary at the league minimum-when a player’s WARP was 0.0-as we see in blue below, but it also showed salary accelerating as WARP increases. If we imagine that the red points are sample data points of salary and WARP for individual free agents, it makes sense to graph it, with the curved shape we see below. Trying to draw a straight line through these points would not look like it accurately reflected the relationship. Instead, the blue parabola best fits the data:

However, Clay Davenport recently shifted replacement level upward to better reflect the players available at the league-minimum salary. Now, let’s see what happens to the same exact distribution when we shift replacement level upward and lower all those WARP levels by two wins.

If we continue the natural assumption that zero wins above replacement is worth the league-minimum salary, suddenly, the best fit is a straight line. To properly estimate whether the relationship between wins and the dollar value of a player’s wins is linear, we need to dig back into some theory and see what kind of assumptions would make that true and whether they hold in this case.

In a brief e-mail exchange with Silver on the topic, Nate said that one reason that it may still be worth keeping MORP as a non-linear estimator is that we are not estimating what teams should pay for wins but what they do pay for wins. We are stuck with the reality that we cannot determine how many extra fans are put in the seats by adding a player with a certain win value, and we are therefore stuck with using the inferred price of free agents that teams have shown us.

However, we are trying to approximate how much teams pay for that production. If we wanted to simply approximate how much a free agent would sign for, even if he was not necessarily worth the money, we would include a term in the equation to give the player extra MORP for high RBI totals. After all, some GMs certainly place a premium on this and the player will earn more as a result. A formula that simply adds extra dollars to the MORP value when a player has more RBI is hardly the production valuation that we are looking for from MORP.

Think of the implications: If we want to use MORP to evaluate signings, we cannot simply say, “Jason Bay got a great deal. Look at all those RBI that brought his MORP up! Clearly Omar Minaya overpays for RBI, just like Baseball Prospectus told him to!” After all, Bay’s placement in the potent 2009 Red Sox lineup led to a lot of RBI that we do not want to pretend is part of his value, since he would not have gotten the same total had he remained with the Pirates.

Similarly, we are also not going to include a dummy variable in the equation for “Was this a veteran relief pitcher signed by Ed Wade?” that adds a certain number of dollars to MORP when the answer is “yes.” We are figuring out what teams pay for production, so we should be using their WARP total as the measure of output. Similarly, we should not implement a system that adds extra \$/WARP for higher WARP unless there is an actual basis for doing so in economic theory.

If baseball free agents were in a typical, perfectly competitive market like those you see in the first chapter of your introductory economics textbooks, the price per win would have to be linear. Basic economic theory of perfectly competitive markets would say that anything other than the same price for all wins would create arbitrage opportunities where teams could perpetually trade their way to the top of the league. This makes sense in something like a stock market. Say the dollar price of two shares of Microsoft was more than twice the dollar price of one share of Microsoft. People would simply buy up all the single shares of Microsoft, and then sell them in packets of two at a profit. The end result is that the demand for single Microsoft shares would go up, driving that price up, and the supply of pairs of Microsoft shares would go up, driving that price down.

Of course, strawman economists, who consider it their job to think really hard about the first chapter of the econ textbook, are always wrong. That first chapter is really supposed to be a baseline from which we can see what would happen as we change each assumption. In the case of baseball free agents, there are two main reasons why the baseline’s assumptions don’t apply. First, these markets aren’t thick enough that teams can sign and trade players so easily and quickly swap out players for others like investors can do with shares of Microsoft. There are only so many teams, and there are limits to making this kind of move in general. Second, you can’t employ 60 Garret Andersons on a team and suddenly become the best team in baseball. There are only 25 roster spots, and only so many players can realistically get enough playing time to realize their true value. Somebody needs to be playing above average for the team to make the playoffs.

The first issue of “thick enough” markets does not matter as much here. As the Mets could have simply signed Jon Garland and Johnny Damon, both two-win players, rather than just Jason Bay, one four-win player, it does not make sense to say that the MORP of a four-win player is any more than the combined MORP of a pair of two-win players. Since the money it would take to get four wins of production is better estimated through the price of two two-win players if there are spots for both, the price of four wins should be the combined price of Damon and Garland. Of course, that assumes that the Mets have spots in their rotation and lineup for both.

The issue of there being spots for both is curious. In the initial background study toward the general project of developing MORP, I decided to look at how many roster spots teams could realistically upgrade from a replacement player. I looked through each team’s roster at the beginning of the 2009-10 offseason and attempted to determine how many places a team would have been left with expected replacement-level talent without making a trade or free-agent signing.

The concept of what a replacement player means is hazy, but there certainly does seem to be a talent level that is common among teams who replace players. I used something roughly equal to that definition to do this analysis. This definition, for clarity, involves about 20 runs below average over a full season for position players with positional adjustments considered. For starting pitchers, it involves approximately a 5.50 FRA in a neutral league. For relief pitchers, it is approximately a 4.50 FRA in a neutral league. FRA, or Fair Run Average, estimates what a pitcher’s Run Average would have been if he had neutral performance on inherited/bequeathed runners. These are only ballpark figures, as I only have a few projection systems to work with, but these levels do make sense as there seems to be about three to six players who would have been slotted as starters at each position with no off-season moves. All of them were about 20 runs below replacement level and more than half of teams had a fifth starter who could be expected to put up a FRA near 5.50. Among relief pitchers, it’s tough. Although the average team employs six or seven relievers, not all of them get high-leverage innings. Looking through how teams have historically used relievers, a good estimate is that each team uses about four relievers in high-leverage situations regularly over the course of the season. Therefore, if a team had three relievers projected to have FRAs below 4.50, I considered that one opening in the bullpen where a new reliever could be signed and get high-leverage innings.

The analysis is relatively straightforward after that. In final part of the series on Friday, I’ll check how many spots the average team had, with special emphasis on teams who typically spend on free agents and therefore set the market. With these definitions and the understanding developed above, I’ll look through each position on the diamond (and DH in the American League) as of the beginning of November, and the top five projected starters and top four relievers at this time. If most teams have a few replacement-level openings at the beginning of the offseason, then we will know it is OK to go forward with a linear relationship between dollar value and WARP.

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sunpar
1/20
Could you clarify this statement: "but there certainly does seem to be a talent level that is common among teams who replace players"

Specifically, are we talking about stuff like the Florida Marlins in 2009 replacing the outgoing Mike Jacobs at 1B by shifting Jorge Cantu over to 1B, and employing Emilio Bonifacio at 3B? So then Bonifacio's production would be in this talent level bucket?

(I suppose since Bonifacio in 127 games accumulated -19 runs below average, he'd be the perfect example).

swartzm
1/20
Sunpar, thanks for your clarifying question. Although Bonifacio probably is replacement level, that wasn't quite what I meant. I actually meant literally players being replaced. In Friday's article, you might see what I mean a little clearer, but some examples would be that the Phillies had Greg Dobbs as the next-best option to making a move at 3B by staying in the organization but chose to replace him with Placido Polanco, the Red Sox had Jed Lowrie in the organization as the next-best option to signing Marco Scutaro at SS who they chose to replace him with instead, the Rays had Dioner Navarro as the next-best option to trading for Kelly Shoppach at C, etc. Friday's article will definitely show you more about what I meant. Thanks for clarifying.
sunpar
1/21
That seems to pretty much the definition I had in mind, though Bonifacio was a bad example since he was traded for.

I would still technically consider Bonifacio to be "free available talent", as he was acquired for a 29-year-old Jon Rauch and later a throw-in along with prospects for Willingham and Olsen-- the prospects being the "real" part of the deal. But I understand why you can't include guys like him in that bucket.
swartzm
1/21
Well, Bonifacio is probably replacement level for 2010 even if his upside is higher. He certainly is the same quality of player as I was thinking of, but unless other players of his caliber were replaced on other teams, we wouldn't have counted him. I think it may be clearer Friday, but please ask questions if it's not.
sunpar
1/21
Heh, the more I think about what I was saying, the more I'm realizing how misleading my thinking is. So feel free to ignore at this point; I understand what you're saying.
metty5
1/20
Matt, I liked that piece a lot. I would suggest that if you "are not estimating what teams should pay for wins but what they do pay for wins" that you should create MORP2 that calculates what teams should pay.
cjones06
1/20
I'm a bit confused by the end of this, but it sounds like you're checking how many teams have replacement-level players as defined by the average production of players that are replaced. Won't that number be very close to the number of players that are replaced, i.e., the number of free agent signings each year?

Regardless, it's hard to see exactly what it would prove if each team had 3 or 4 replacement-level starters heading into the offseason. This still means that a team cannot sign 6 low-WARP players for the same production as 3 better players; there is still a scarcity for higher quality players and they will demand a higher price. The only question is HOW non-linear this relationship is. Your graphs seem to imply that the answer is NOT VERY MUCH (presumably because the scarcity seems to provide extra contract security instead of a salary premium).

Still, i think we can look at the theoretical value of this scarcity a little more directly, in contrast to: "We are stuck with the reality that we cannot determine how many extra fans are put in the seats by adding a player with a certain win value, and we are therefore stuck with using the inferred price of free agents that teams have shown us."

In some ways, the increased value of better players can be measured by how far along the win curve their teams are, on average. That is, while marginal revenue is fairly linear in wins for the average team, valuable players make it easier to be further up on the curve, so that marginal wins are higher. By averaging the marginal revenue 4 win players provide (as measured by finding the difference between expected revenue at the actual number of wins - expected revenue for wins less the player's contribution), you'll get a better idea of what this advantage is (which should be greater than 4* the average marginal revenue that 1 win players provide; there's also one extra complication that needs to be taken into account-- the incentive to spend more money on your team when marginal revenue is greater --but this could be corrected for by using salary as a percentage of team payroll and then translating to an average payroll or some other fix). This would leave a similar scatter-plot of MRs and salaries which you could check for linearity.

Hope that was somewhat clear / made sense to anyone but me. I just wouldn't give up on attempting to use MR just because we don't have direct measurements.
swartzm
1/20
@archilochusColubris: The number of replacement level players will outstrip the number of free agents signed, you'll see on Friday. A lot of teams don't sign or trade to improve on replacement level production-- and end up getting it as a result. Think about how many teams have 5th starters with ERA's well into the 5s. The idea is that as we get a sense of who is replaced, we get a sense of what replacement level is.

The example you gave of 6 low-WARP players vs. 3 high-WARP players actually will illustrate the point of exactly how low and high WARP of free agents are. There are only a small handful of free agents that will get you more than 4.0 WARP reliably, while you can certainly see an abundance of guys in the 1.5-2.0 range. I guess it's possible that a team could try to sign 3 guys with 4.0+ WARP, but that's really rare and not common enough to affect the market price, mainly because you'd really need two bidders to push up the price. Maybe the Yankees signed Sabathia, Pettitte, Burnett, and Teixeira last year, but that's a rare year even for them, and they probably not have people competing with them to sign several of them rather than individual teams competing to sign one or two of them (e.g. the Red Sox were not probably also trying to sign three of these guys, probably just Teix and a pitcher at most).

The scarcity is reflected in the already higher price-- it's just that the scarcity comes in linearly.

The important distinction to be made with how far along their teams are along the win curve, on average, is an important one. The average team does not sign free agents-- the team that values the player the most does. Thus, teams that sign free agents are the ones that are likely to be the most competitive. For them, the marginal value of a win is already high since most of them are already in the 85-95 win range.

For your MR measurement, the problem is that we do not have counterfactuals. In other words, even ideally we could only know what the Phillies' revenue was last year given that they won 93 games-- we do not know what their revenue would have been had they not signed Ibanez and won, say, 89 games. Any attempt to solve this empirically would be muddled by the fact that the Phillies clearly thought 89-73 was unpalatable compared to 93-69, so even if we had the revenue of other teams who went 89-73 or even the Phillies in previous years where they won 89 games, those numbers likely understate the difference between 89-73 and 93-69 because in instances where the team won 89 games, they likely didn't have as huge a gap (and didn't want to spend the money), and in instances where a team won 93 games, they likely had a larger gap.

In reality, assuming the very rich individuals and companies who own baseball teams have at least a decent sense of their marginal revenue, we can use the Axiom of Revealed Preference to impute a decent approximation of marginal revenues.

Let me know if I left anything out, and thanks for giving such an incredible amount of thought to this. It's a very challenging job to redo MORP, and I encourage thoughtful comments like these to help guide me along and challenge my assumptions (and change them where necessary!).

@JDSussman: I would say that this is estimating what teams should pay for wins, conditional on the fact that the market is producing the correct price on average. For instance, if Omar Minaya overestimates the win-value of Jason Bay and overpays but Jack Zduriencik sneaks in at gets Chone Figgins at low \$/WARP, that would not be an issue in the model as they would cancel out. Where the issue would lie is if winning actually doesn't add much to revenue but Steinbrenner just lets Cashman spend to a certain budget because he can afford it-- rather than because he can make money allowing him to do so competently-- then MORP won't know that this is happening. It assumes that, on average, teams are paying for wins at their marginal benefit.
cjones06
1/21
Ah good point; it is pretty much impossible to account for the fact that each team is estimating MR by evaluating their pre-season chances of making the playoffs, which is certainly dependent on competition and therefore not the same for every x-win team. Annoying!

And thanks for the clarification on your approach. I get what you're doing now, though i'm still a tad confused on the logic behind the last sentence of your article. Well-- can't wait for your article on Friday when perhaps things will clear up a bit!
bsolow
1/21
Hey Matt -- there was actually a discussion of this between myself and Tango 1-2 days ago here: http://www.insidethebook.com/ee/index.php/site/comments/revising_morp/#comments.

I'm quite interested to see the next part of this series, because I think there's some confusion between the salaries being linear and the value of players being linear. With the appropriate replacement level and assuming 0 WAR players get paid the minimum you probably will get a linear relationship in observed salaries. However, I think there's an issue with market thickness that you haven't addressed (do certain teams have monopsony power over top free agents?) that may make observed salaries appear more linear. Furthermore, it may be the case that so few of the GMs or agents take into account lineup constraints when negotiating contracts that the value isn't accurately priced -- really smart guys like Tango didn't think about it either. Finally, I really do wonder about the shadow price of the lineup constraint. Take a team full of guys who are +1 win above replacement -- one +5.5 win player and one +0.5 win player are more valuable than two +3 win players because of who they're displacing to the tune of 0.25-0.50 wins each time you make this decision (full examples in the comments that I linked to above). So long as you're a team with significant depth of above-replacement players (i.e. with a great farm system or an unlimited budget), there should always be an extra return to concentrating talent.

Colin noted in those comments, rightly so, that I'm ignoring any aspects of risk hedging. That's absolutely right, and a series of articles on optimal roster/lineup construction would be a fan-freaking-tastic project for BP to tackle.

Last note -- I think it's worth deciding, and being clear about, what exactly you want the new MORP to represent. Is it the going rate of a win above replacement? Is it an estimate of marginal revenue product? Bid shading in a sealed bid first price auction would suggest that those are not the same thing. Similarly, if you viewed this market as a Nash bargaining game due to monopsony power (although I prefer your auction interpretation), it's not clear why players should be earning their entire marginal revenue product.
swartzm
1/21
I read through that discussion between you and Tango the other day, but decided to hold off on commenting until I published all three articles. I guess the short of it is that I think that you were right about the kind of tests that need to be run and he was right that it'll come out linear even if he didn't have the right reasoning down. Basically, Friday you'll see just how many replacement level players in key roster spots (i.e. lineup + rotation + top four bullpen guys) are lined up as of early November. It's a lot, even for good teams. So, while I agree that there is absolutely an economic argument for a premium due to concentrating talent, there are just too many ways to do it that signing a superstar isn't necessary. Think of the best free agents signed this year-- Jason Bay and Matt Holliday-- and look at how many holes were in each roster as of November.

I do think that current estimates of replacement level-- 40 to 50 wins for a whole team-- look a little low unless you count displaced talent. Specifically, the first example I'll give Friday is the Phillies and Greg Dobbs. He's not quite 20 runs below average even if he had to hit off lefties, but the effective pinch-hitting changes by making the Phillies use a worse PH vs. RHP make it about 20 runs below average. So I think displacing people is part of the story.

Also, remember that calling up talent from the farm costs service time, so I don't know if that's really a preferable solution in many cases.

With respect to what MORP is trying to represent, it's a good question. I'm basically assuming that teams are setting marginal revenue to marginal cost on average, but that there is some noise in the estimates of win values of players. I would say that marginal revenue is really equal to marginal wins x marginal dollars per win. Further, I'm assuming that marginal dollars per win is probably negligibly different between the top few teams but that marginal wins is really where there is more variance. From there, I'm basically assuming a first price sealed bid auction. Due to the winner's curse and the fact that it's a first price auction, I assume teams probably due shade their bids down some but that those are negligible differences. Really, I think that on average, a model of (\$/WARP constant)*(WARP) pretty much explains the market and can give you MORP but that teams can do things like the Phillies did with Polanco (check my earlier article on this if you haven't seen it) by adjusting the replacement level of the (N+1)th team where there are N free agents. But in general, I do think that the model as is explains it pretty well.

I'm not sure I like monopsony because I think of the 30 teams as being the labor demand side rather than 1 MLB, so that would put it at an oligopsony, and while I do think that the draft is an example of implicit collusion of the repeated prisoner's dilemma ilk, I'm not sure that the free agent market does that mostly because teams from different divisions bid, and so I'm pretty sure they bid based on the expected marginal revenue (conditional on winning, winner's curse thing).

Thinking more about it, I do see the possibility that there is still some fraction of marginal revenue product that the players do not capture in expectation, but I think in that case MORP still answers the question "What do teams pay for this number of wins on the free agent market on average?" so I think it's a valuable tool even without looking at actual marginal revenue.

I definitely liked your discussion with Tango, though. I think you saw something he missed, but I think the results make it such that it doesn't matter.
bsolow
1/21
I certainly agree that MORP is a useful statistic - the answer to the question "What is the average price of a win's worth of talent?" is valuable. I also think, though, that while monopsony may be overstating the case, for top tier free agents there probably is a lot of demand-side market power. With rare exceptions, top tier free agents are going to sign with the highest marginal revenue clubs. Then, constrain the set of available matches to teams with an opening at that specific position (or the ability to shift a player to make an opening). It's likely that this looks like a market with one or two dominant buyers and a competitive fringe with a significantly lower marginal revenue. After the players and the dominant firm are matched, it's just a question of how they split the excess marginal revenue through some kind of Nash bargaining game. However, if you're assuming that differences in marginal revenue are negligible, market power isn't relevant except in extreme cases.
swartzm
1/21
This is a very good point. I guess the concentration of the Red Sox and Yankees in the AL East does cause that kind of issue. I guess that would affect the market, but given that the Cardinals signed Matt Holliday and the Mets signed Jason Bay, and neither are top 2-3 revenue clubs, I suspect that maybe the marginal revenue isn't as distinct among top teams even if total revenue is (certainly they must be highly correlated though). There's also another aspect that I'm not approaching here that you remind me of, which is externalities-- I mean, the Yankees and Red Sox really exert externalities on each other's playoff probability when they sign free agents and in those cases the marginal revenue might get higher because of what it does to the competition too.

There are definitely a lot of complicated issues here, but I think that the main one is the roster construction issue of number of openings and probably these results are enough to ensure it's safe to use a linear \$/WARP framework.
cjones06
1/21
By the way, Ben perfectly articulates the reason why imputed team value shouldn't be linear in player value by noting that this disregards the shadow price of lineup (or roster) constraints. Concentrating value is valuable in and of itself and therefore we would imagine greater player value should earn a premium over a linear pay structure.

That said, this is a theoretical point, leaving the magnitude of the effect uncertain. If the shadow price of the roster constraint (and playing time constraints) is zero, then there would be no effect. If it's close, the effect would be negligible (which i believe is Tango's position here). It appears that Matt is presenting data here that back this up.

I've got to admit, that's pretty counter-intuitive to me, given all the hand-wringing and whatnot over getting enough arms in the bullpen, but if it's so, it's so.
bsolow
1/21
I agree with you and Matt that it's likely to have a pretty small effect in observed salaries. I think that it could appear that way, though, due to the presence of other non-linearities that push the other way such as risk-hedging. But, if you're interested in figuring out the going rate for talent, it doesn't matter what the non-linearities are if they balance each other out. Which brings me back to thinking that optimal roster construction would be a good thing to figure out.
swartzm
1/21
I agree that optimal roster discussion is probably a good task, though it's probably still in its infancy. Have a look at recent Eric Seidman articles. He and I have had a few discussions recently about certain free agents and risk, and I really like what he's been able to do in applying his ideas to Pineiro and Garland, and other free agents. Basically-- risk isn't always bad in baseball. The average team wants risk. It's only teams who are very good who want to lower the standard deviation of their win total distribution. Let's say the Mets expect to win 83 games next year. They want the standard deviation of their win total to be higher, because it entails a higher chance of reaching the playoffs. Similarly, the Cardinals are almost a shoe-in and probably could expected 92 wins, say, in a weak division. They want their standard deviation as low as possible. Thus, Seidman explains that the Cardinals would be a better match for Garland and the Mets would have been a better match for Pineiro (though he signed with the Angels, which makes sense for the same reason).
cwyers
1/21
In this case, we're talking downside risk, typically from season-ending injuries. In the case of an average ballplayer, you should see an almost bimodal shape, as you have some variation around a 2ish WARP, and then you should have a little peak again around zero for times when a player missed most of the season. That's the sort of risk that you hedge against by having two 3 win players rather than one 6 win player.
cwyers
1/21
I think there are a lot of problems currently with figuring a ballplayer's marginal revenues, not least of which the fact that we don't actually know team revenues. We have the Forbes estimates, but we don't really know the extent to which those are true. (We do have other financial disclosures, like the Blue Ribbon panel, but we don't know the extent to which that is true. Probably our best source of financial info on teams is the audit of the Brewers from a few years ago, but even then some rather key aspects were left outside of the scope of the audit.)

I think given the uncertainty there, it's better to do a "free market returns" approach to valuing players, rather than to do an MRP analysis and assert that teams are incorrectly valuing players. (This hasn't stopped me from trying to do an MRP-style salary value estimate before, I should note.)
nosybrian
1/21
Matt: interesting article, but I have a question.

If the effect of your predictor variable (say X) is specificied as a quadratic function (b0 + b1(X1) + b2(X^2), you do allow for the possible curvilinearity (parabolic) but without necessarily imposing empirically.

This is true because if in fact the empirical relationship turns out to be strictly linear, then the coefficient b2 would be small and not statistically significant. In that case the linear coefficient (b1) would capture the effect of X on salary.

I agree with Nate that it may be preferable to use the quadratic function as a theoretically more compelling function in this case that would not in fact cause any serious distortion in your MORP estimates if it turns out empirically to be a linear relationship. The cost in degrees in freedom is also negligible.

My analogy is to the price that I paid per meal as a function of the number of stars that a restaurant gets in the Michelin guide. My experience in that case told me that while I might pay \$50 for a meal in a 1-star restaurant, and \$100 in a 2-star restaurant, it would cost me \$200 in a three-star restaurant. The marginal pric of the additional star was a nonlinear function. (This based on a "45 days in Europe" tour some years ago. Your costs may be different!).
swartzm
1/21
I am not up to checking the regression yet, but based on my results in this article and the next, the point is that what teams are paying for is wins. The analogy with stars of restaurants is not the same because you can't go to a one-star restaurant and a two-star restaurant and feel as satisfied as you would going to one three-star restaurant.

If b2 turned out to be significant, then that would indicate a market inefficiency or something missing like arbitration compensation or replacement level too low, etc. But if adjusting for arbitration and proper replacement level, I still find b2 is statistically significantly positive, then that means something is wrong with the market that can be exploited.
gregorybfoley
1/21
Couldn't a significant b2 value also be explained by a nonlinear market for wins?
swartzm
1/21
It could also be explained by teams who sign stars overvaluing their worth. The difference is this test I've run where I checked how many openings teams have. If teams who sign superstars had several replacement level players who they neglected to replace, then they shouldn't be nonlinear. The point is that if the market with respect to WARP is nonlinear but shouldn't be, then we can't make the market value of those wins can no more than we can consider RBI to be worth more. If there was a way to replace a 4-win slugger with a 4-win player who has fewer RBI at a cheaper price, the cheaper price is the market value of 4-win players. If teams that sign 4-win players can be eschewed in favor of pairs of 2-0 win players at a cheaper combined price, then the cheaper combined price represents the price of 4 wins as well.
nosybrian
1/21
I think it could.

What Matt is calling a market inefficiency could also be understood in some other way. For one, a buyer (GM) is, after all, only making a forecast of the player's performance. would conjecture that the greater the GM's forecast on the wins produced by a given player, the greater the tendency to let hope come into play. Given that any forecast has a probability distribution around it, when you move into acquiring a star player you may tend to envision next year's performance as coming at the high end of that distribution (perhaps by picking out the player's "best" performances in recent years rather than making a more conservative PECOTA-like projection).

If you want to call such an "optimistic" projection inefficient, that's fine. But it still can lead empirically to "fairly valuing" slightly above replacement players and overvaluing the better players.

Also keep in mind that roster spots are also scarce (limit to 25), and there are transaction and maintenance costs for players (health care, uniforms and equipment, travel, etc.); so if you can get the same number of wins from one player as you get from two, then your "costs" per win may be reduced by hiring one 4-win player rather than two 2-win players. There can also be efficiencies when you get a "utility" 2-win player rathern than two one-win one-position players.
nosybrian
1/21
BTW/ what is the average maintenance cost of a player over a season? How much is spent on travel and lodging, meals, equipment and uniforms, medical care, training, and other administrative overhead including insurance?
swartzm
1/21
It could be that optimism plays a role, but that would still mean those GMs are overvaluing wins. That said, I think it's more likely the somebody thinks a pitcher who has a 4.50 career ERA can be spun into a pitcher with a 3.50 ERA with the right pitching coach than it is for a team to think a pitcher who has a 3.50 career ERA can be spun into a pitcher with a 2.50 ERA. Same idea-- a GM seems less likely to think a .325 hitter could be turned into a .365 hitter than he is turn a .285 hitter into a .325 hitter.

I like the transaction cost idea a lot, but I think short of health care costs, it's really hard to see other stuff playing a huge role (i.e. you get 25 uniforms and 25 plane tickets regardless of whether a schlub is wearing the uniform in the airplane seat or not). Health, maybe, but I don't know-- how much does Dr. Andrews charge?
nosybrian
1/21
I know it's probably a minor point, but I'm just saying that if you can get the same otal tactual value (wins) for less overhead (indirect) cost while keeping another roster spot open by hiring one 4-win player rather than 2 2-win players you might get more wins/\$ that way (when your \$ represents both direct costs (salary and fringe benefits) and indirect costs (healthcare, training, travel, equipment, administration, legal, insurance, etc.).
swartzm
1/21
Oh, it's a very good point, but just make sure to separate indirect costs that vary by player and indirect costs that are the same for all players because you 25 plane tickets, 25 uniforms, 25 sets of bats, etc., regardless. I definitely appreciate the comment.
rawagman
1/21
Matt, I think you're giving some valuable information here. Even though I have never attended an economics class, I still think I get it.
I may have missed it somewhere in your explanation, but to be certain - I take it you assume that when a team makes a decision to sign a free agent, it is not just in the need to displace a replacement level player, but more specifically to replace a replacement level player at the position of the new signee.
swartzm
1/21
I'm pretty sure you get it based on this, but I'm not quite sure about the distinction between those two things. The point is to replace a player, typically one who is a replacement level at the same position (or at least by shifting players around the diamond and bumping someone replacement level out). Sure, some times it won't be a replacement level player but teams with the worst alternatives are typically the ones most inclined to sign free agents.

I'm glad you were able to follow without taking econ. I always strive to explain the econ well enough that it makes sense as common sense rather than just empty theory :-)
Darsox64
1/21
Something that I think Silver was hitting on and is not being captured in the analysis is the economic idea of the subjective theory of value. What is observable on the market is not what people should do but what they actually do. Perhaps there exists an objective way to measure how to achieve a certain number of wins or a certain probability of reaching the playoffs or a certain probability of winning the World series, but there exists NO way to scientifically measure the difference in importance between achieving any of those ends. The only way to perceive how owners and GMs behave in response to those different subjective ends is to allow for other functional forms and accept whichever functional form best fits the data. To do otherwise is to assume some objective trade-off between the desirability of winning a game (as in going from 70 to 71 wins) against getting into the playoffs (the increase in probability by winning 88 and 89 wins). These trade-offs are in every sense implicit in valuing a star player's wins differently than a marginal player's.

I don't think this analysis is economic given the subjective theory of value, which very much is econ 101.
swartzm
1/21
No offense, but I don't think you know what you're talking about when you say "I don't think this analysis is economic." I'm a PhD economist, so I'm pretty sure it's economic and I'm pretty sure that counts. If you don't agree with economic theory as it applies to this problem, then say that, but try to avoid telling me I'm not using economic analysis.

I'm also confident that in the past decade of work at Baseball Prospectus, including much of the pioneering work by Silver, there is little ability to control the probability of success once you reach the playoffs with notable exceptions like the Secret Sauce formula that you can find on the stat pages. Of course, teams put different subjective weights on these different outcomes, but regardless, that would not really change the fact that signing a superstar and signing several average players are both viable choices even for teams who have higher aspirations is still an option. I'll say that again for clarity-- the whole point of this article is that achieving the 100th win or the 60th win, teams who sign superstars will generally have the ability to add those win by filling in several average players as well. There are very few situations where a team has almost no replacement level players in important roles.

As far as your 71st win versus 89th win tradeoff, I addressed that in the last article, this one, and again in the comments-- the point is that the vast majority of teams who sign free agents are the ones with the highest value for a win. The reason is that those teams generally value the win more. You can figure that out from their behavior, which is both intuitively obvious and basic economic logic. No one is questioning Silver's marginal value of a win-- which isn't a subjective argument either, but an objective one with noise mixed in-- but rather approaching how the market works given that. Since teams who sign free agents are generally competitive and generally set the market, there is no conflict in those thoughts, what I'm saying, and economic theory.
rawagman
1/21
Matt - I wanted to ask about your comment that, "the point is that the vast majority of teams who sign free agents are the ones with the highest value for a win". Would it be fairer to say that "the vast majority of teams who sign *high end* free agents are the ones with the highest value for a win."?

I say that as a Jays fan with no real hope for this season - but some reasonable hope for subsequent seasons. Either way, even the Jays sign some guys - a bunch of MiLB contracts, John Buck, various MI waiver claims, re-upping John MacDonald... Even the Pirates signed Ryan Church
swartzm
1/22
I would agree that some low end free agents are more likely to go to other teams. This is for a couple reasons. One is that "replacement level" isn't always true in practice and teams with particularly bad alternatives that are worse than replacement are more likely to sign a mediocre player. Basically, let's say that we have a guy who is worth 0.5 wins and the market prices him around \$3MM. For a team with a bad alternative who is actually going to produce -2.0 wins, that's a pretty good deal. Of course, if there is a replacement level player worth 0.0 wins, that's a better option so you'll probably observe that more often. That's part of the reason you see a whole host of minor league deals. The other issue is that for bad teams especially, there is an indirect cost of calling up a bad player because you use up his service time. If you have a guy you expect to be worth 3 wins a year starting next year but is only worth 0.5 wins now, why call him up now? You can get 2.5 wins extra from his 6 cost-controlled years by signing a replacement level player instead. The benefit of blocking a developing player who would theoretically be above replacement now but is likely to be further above replacement in the future is valuable.
jdtk99
1/21
Matt, I very much enjoyed the give and take in the comments. This reminds me of into physics where we were told to imagine an object had all of it's mass at a point in space. Half the class objected because this was not true. Half the class rejoiced because it made the math much easier.