ZiPS ROS Projections as Estimates of True Talent

Player projections are a great tool. They give us good, objective estimates for a player's talent going forward, which makes them useful for addressing a number of questions. For example, should your team go after Player A or Player B to play shortstop next year, and how much improvement does each expect to provide over Player C, who is already signed? How much should the team offer each if they decide to pursue them? Who is a better option to start between two players competing for a job? Did that trade your team just make make sense, and did you get an improvement in expected performance over what you had? How does the talent on my team compare to that of other teams in the division?

You can even use projections for important questions, like, who should I draft first overall in my fantasy league (I guarantee you will avoid such pitfalls as the infamous Beltran-over-Pujols,-et-al debacle, circa 2005--sorry, Uncle Jeff)?

That's all well and good for looking at the coming season, when you don't know anything about anyone's season yet, and your best guess is probably going to be heavily informed by each player's projections. However, the major problem with projections at this point in the season is that most of them are an off-season affair. They are most widely used for projecting the coming season, after all, and they can take a lot of time and computer resources to update to work mid-season and keep running over and over throughout the year.

Each player's current season performance definitely tells us a lot about how we should estimate his talent going forward, so this presents a problem with relying primarily on pre-season projections in some cases. As a result, you are more limited if you want to find projections that incorporate the current season's data to answer questions that require current estimates of talent to answer; say, for example, how does that trade my team just recently made look, or how does my team shape up for the playoffs, and how do they compare to their likely opponents, or should we give a serious look to this September call-up who's been on fire?

Fortunately, there are at least a couple freely available projections that provide in-season updates. The ones I know of are CHONE (published at Baseball Projection) and ZiPS (published at FanGraphs as ROS--rest of season--projections). Both can be good options for estimating a player's current talent level without ignoring information from his performance this season.

Because ZiPS is updated daily (as opposed to the updates every month or so that CHONE provides) and because it is now published at and frequently used by writers for the prominent stat website FanGraphs, it has become a favourite for a lot of fans for estimating current offensive talent for players. While it is great that such a tool is available and that it is used in an attempt to form objective, informed opinions, there is a serious caveat with using the current ZiPS projections on FanGraphs as true talent estimates this late in the season.

To illustrate, consider Ryan Ludwick's ZiPS ROS wOBA projection. Right now, it is .375. Before the season started, ZiPS had Ludwick pegged for a .372 wOBA. He has since aged a bit, posted a .334 figure for the year, and moved to a worse park for hitters. How did his projection go up? What is even more confusing, if you track the projections from day to day, is that yesterday, his wOBA projection was at .390 or so. The day before, it was at .385. And, if you really want to wake up in Wonderland, check the ROS projections during the last week or so of the season, when you have 8 dozen guys projected for the same .250 (or whatever it ends up being) wOBA. What is going on?

The issue is that the ZiPS ROS projections on FanGraphs are not, in fact, an estimate of the player's true talent going forward. Rather, the projection gives its best estimate, in whole numbers, for the player's number of singles, doubles, triples, homers, walks, and HBP for the rest of the season, and then FanGraphs figures out what the player's wOBA would be over the rest of the season if he hit each of those figures on the nose. For Ludwick, that means his .375 wOBA projection is not his projected talent level, but the wOBA for the following projected line:

appr. wOBA
Ludwick 8 3 0 3 4 1 55

But remember that each of those components is rounded to the nearest whole number. His projected singles total could be anything from 7.5-8.5. Rounding to the nearest whole number eliminates precision, and when you have a wOBA figure that needs to go to 3 decimal places, that loss of precision can affect the projected wOBA. To see just how much difference this can make, let's pretend all of Ludwick's actual projected components are really .5 lower than the rounded off whole number (the lowest his actual projected wOBA could be), and then pretend they are all really .5 higher (the highest his actual projected wOBA could be), and see how much that affects his projected wOBA:

1B 2B 3B HR BB HBP PA appr. wOBA
7.5 2.5 0 2.5 3.5 0.5 55 0.324
8.5 3.5 0.5 3.5 4.5 1.5 55 0.440

As you can see, given Ludwick's projections over 55 PA, his actual projected wOBA could theoretically be anywhere from .324 to .440. That is a huge range. Of course, to be close to the extremes of the range, every component would have to be rounded in the same direction by a large amount, so it is more likely to be close to .375 than to .324 or .440.

How much more likely? To answer that, we have to know something about the distribution of possible true projected wOBAs for Ludwick, given that FanGraphs is displaying a .375 projection over 55 PA. We can do that by finding the standard deviation of the difference between actual projected wOBA and the rounded wOBA projections displayed on FanGraphs for hitters with 55 projected PA.

The actual projected total for each component, before rounding, can be anywhere from .5 less to .5 more than the rounded total. We have no idea where in that range it falls. If Ludwick is projected for 8 singles over 55 PA, it is probably close to equally likely that his true projected rate of singles per PA is 7.5 as it is 8.5, with everything in between being pretty much equally likely. This is a uniform distribution. The standard deviation for this distribution is .5/sqrt(3)=.289. That means the standard deviation for the difference between Ludwick's projected 1B total without rounding and his projected 1B total rounded to the nearest whole number is .289 singles. This describes the error in the rounded total FanGraphs displays.

Since the possible error for every component has the same uniform distribution from -.5 to .5 (except triples, since the rounded estimate of 0 can't have been rounded up, but we'll ignore that for now), the standard deviation for the error of each component is the same .289. Next, we need to know what that means in terms of affecting wOBA. The formula for wOBA is:

(0.72xNIBB + 0.75xHBP + 0.90x1B + 0.92xRBOE + 1.24x2B + 1.56x3B + 1.95xHR) / PA

That means each walk (non-intentional walk, but ZiPS doesn't differentiate, so we'll just use BB) is worth .72 in the numerator of wOBA, each HBP is worth .75, etc. The standard deviation for the error in walk total is .289, so the standard deviation of the effect of that error on the numerator of wOBA is .72*.289 (in other words, the value of each walk times the number of walks). The same process goes for each component. The following table shows the standard deviation and variance for the value of each component to the numerator:

error Val StD Val Var Val
1B 0.289 0.9 0.260 0.068
2B 0.289 1.24 0.358 0.128
3B 0.289 1.56 0.450 0.203
HR 0.289 1.95 0.563 0.317
BB 0.289 0.72 0.208 0.043
HBP 0.289 0.75 0.217 0.047
0.897 0.805

The combined row shows the total variance and standard deviation for the combined rounding errors. This is simply the sum of the individual variances, with the standard deviation being the square root of that. This is what we are interested in.

.897 is not the standard deviation of wOBA itself, just the numerator. To get the standard deviation for the rounding error of wOBA, we have to divide by the numerator, which, as the above formula shows, is just PA. Ludwick is projected for 55 PA, so divide .897 by 55:

.897/55 = .016

For players projected for 55 remaining PA on FanGraphs, the standard deviation of the difference between their actual projected wOBAs and the rounded off projections which is displayed is .016. If Ludwick's actual projected wOBA is .359, that would put the rounding error in his displayed projection at one standard deviation, which would be a pretty typical observation. Of course, we don't know what anyone's actual projected wOBA is or whether the displayed figure is rounded high or low, just how imprecise the displayed figure is. In some cases, like Ludwick's, we can make a reasonable guess that the projection is rounded in a certain direction based on what we know about how projections work (i.e., a 31-32 year old with a down year probably isn't raising his projection), but all we can do is make reasonable estimates and acknowledge the limitations the imprecision imposes.

What does this mean about the value of ZiPS ROS projections? It depends on how precise you need to be. The precision drops quickly near the end of the year, but earlier in the year, they can work as good estimates of current talent. To determine how much rounding error you can expect in a projection, just divide .897 by the projected PA total for the rest of the season, and that will give you the standard deviation of the error. For example, with 200 PA projected for the ROS, the SD of the error is .897/200=.004, which is a lot more reasonable. At 20 PA, you get .045, at which point you basically can't estimate the difference between anyone with much certainty.

As a result, extrapolating the projections over longer periods of time becomes problematic. For example, if you want to compare players for next season, or to measure the magnitude of the difference between them on a full season scale (i.e., Player A is projected to be worth 30 more runs a year on offense than Player B), you are going to be multiplying the large error in wOBA over a large number of PA. Basically, you can't use them to get an idea of large-scale value.

What they are good for, however, is getting a good guess at expected production over the handful of remaining PAs this season. For example, if you want to scour your fantasy league waiver wire and see what everyone is likely to give you over the rest of the season, or if you want to evaluate a fantasy trade proposal, or whatever, then ZiPS ROS projections are great. The key to using them is, do you need a precise measure of value, and do you need to extrapolate over a large number of PAs? Anything where you are looking for true talent going forward beyond just what to expect over a handful of remaining PAs, or to discuss value in terms of a full season, you'd want to shy away from ZiPS ROS projections more and more the later in the year you get. For applications where you don't care about precision or how the projection extrapolates beyond the remaining 50 or 20 or however many PAs, and you don't need to be able to necessarily pick up differences between players with much certainty, then ZiPS ROS projections are fine.


Post a Comment

Note: Only a member of this blog may post a comment.