## Fantasy Value Above Replacement: Part Two

*This is the second part in a published four part series. If you’re interested in reading Part Three, and the Update, click through!*

If you haven’t already, make sure to read the introduction to Fantasy Value Above Replacement from earlier this morning.

**Step Two: Adjusting for Positional Replacement Levels
**

*Theory 2: There will be more outfielders drafted than any of the other position players, and there will be more 1B drafted then any other infield positions.*

Replacement levels are taken on a positional basis. While it may seem that it is just doubling up on the positional adjustment, it is still important to do it this way. If we only standardized replacement level across positions without accounting for the number of players drafted, we could end up with very uneven numbers. There will be more outfielders drafted than any other position players, and more first baseman drafted than any other infielders. We have to reflect that in this number, and this is how we do it.

A replacement level player is defined as “a player who is available on the waiver wire in a majority (50.01%) of leagues.” This will mean that some players taken in the last couple rounds will be at (or below) replacement level, and that is just fine. When I originally created this system, I had it set for 246 players above replacement level. According to the crowdsourcing data that I collected, you guys agree that the numbers should indeed be 246, since the last 2.5 rounds of a 23 round standard draft are replacement level or below.

Because the overall replacement level doesn’t necessarily help up pinpoint the levels at each position, I did a sampling of mock drafts this offseason to help come up with the numbers. Below is a list of how many players are considered to be above replacement level at each position.

C: 12

1B: 23

2B: 18

3B: 17

SS: 16

OF: 62

SP: 62

RP: 36

The data was found using a sampling of ESPN and Yahoo mock drafts to try and prevent one site’s bias from screwing with the data.

When we set a replacement level at each position, we do so by forcing the 13th catcher (for instance) to be a replacement level player. The FVAAz number will change every year depending on the strength of the position, so we just simply adjust using the 13th catcher instead of a set number. We use the 13th catchers’ FVAAz, and add the respective value (or subtract, in some cases) to force their Fantasy Value Above Replacement to equal zero. We then use the same factor and add (or subtract) it to every other player’s FVAAz at the position.

We now have our FVARz, and once we have one for every player at every position, we can directly compare these players. Now, regardless of position, a player with a FVARz of 10 is more valuable in drafts than a player with a FVARz of 9.

*Next, we’ll look at how to convert FVARz numbers into “auction dollars,” as well as going over some semi-random notes.*

Print This Post

Hey Zach,

Cool stuff. 2 questions:

1. Is this different than what Last Player Picked does? if so, how is it different?

2. Will you guys be publishing this as a tool, in order to factor in different categories and positions?

great stuff!

1. From what I can tell, LPP compares raw numbers to an overall (not positional) average. The auction conversion formula is similar, as well, but not exactly the same.

All in all, they did a pretty good job, but I felt they did enough “wrong” to make a whole new one.

2. Not sure.

When looking at replacement values, you must pay close attention to the league setup. The number of catchers above replacement value in a 2-catcher league will be 24, while in a 1-catcher league it will be 12 (in 12-team league).

In addition, the number of 1B above replacement value also depends on the league setup. If you don’t use any kind of utility player (CI/MI/UI/Utility) in your league setup the number of 1B above replacement will be 12 (in a 12-team league). In a league where there are utility spots the number of 1B will change dynamically depending on the number of utility roster spots the 1B will qualify (e.g. CI/UI/Utility).

In our software (RotoChamp) we figure these things out based on the league setup. Eventually, we determine the optimal ‘X’ number of players (where X = starting spots per team multiplied by number of teams). In some leagues, there may be 23 1B that qualify as ‘starters’. In other leagues it may be higher or lower.

From there, we adjust each position by setting the replacement value to zero so that the replacement value of the last ‘startable’ player is the same. For some positions we must add value (Catchers, SS) and others we must subtract (1B, OF most of the time).

I’m unclear of how your system handles heterogenous league setups. How are you adjusting your replacement level in a 2-catcher league? What about a league with 5 OF versus a league with only 3?

Good post, though. Looking forward to your auction dollar conversion.

@rotochamp I agree with Roto. If you have a league that is somewhat different from traditional scoring/ roster types just research the prior drafts over the past couple years to determine how many of each position are drafted to calculate your “replacement” level. I.e. in my league we draft about 160 SPs so the 160th ranked SP in my projections gets a value of 0.

The second part is normalizing the stats to compare across each position. In a pts based H2H league this is easy because it is just a simple number based off projections, however in category based rotisserie leagues you need to create a value that weights each scoring category appropriately and combines into a single value. I think what Zack is doing with the z-scores by position handles this.

@verd14: i think that your final issue is a good one. when you are playing by categories, it doesn’t matter if your players are all 10s overall compared to all 9s overall for your opponent if your players get all their value from home runs. because say you just blow your opponent out of the water in home runs and therefore take RBI as well. but then your opponent has all speedy high average guys so they win runs, avg and SB. then your overall team score is a lot higher, filled with “better” players, but you lose the week because it was all the value was centered in one category. simplifying value down to one number does not take into account the 5×5 nature of fantasy. it needs to find a value for each 5×5 category and then you try to get the highest overall value IN EACH CATEGORY instead of just combining them all, that way you have a good balance on your team and can win individual categories. basically, it’s a long winded way of saying you should do a value above positional average for each category instead of combining them all into one number.