*This is Part II in a series describing the methodology the Price Guide uses to come up with dollar values for players. If you haven’t already done so, you might be interested in reading Part I, which discusses how standard scores are used to build the initial player values.*

In our previous example, we had a standard Yahoo setup with 12 teams and 9 hitters per team, for 108 total players drafted. In this league, there will be 12 players drafted at each position.

Notice that, in an auction, the last catcher drafted will go for $1, and the last 1B will also go for $1. This is true even though the last 1B is expected to produce much better stats than the last C. And that’s the key point: Despite the variance in expected production, the last players drafted at each position have the exact same value.

With this in mind, we want to adjust our values so that the last players picked at each position have equal values. In our sample league, the 12th best SS according to Marcel is Ryan Theriot, with a value of -2.97. The 12th best catcher is much worse–Chris Iannetta at -6.26. So for all of the SS, then, we will add 2.97 (i.e. subtract -2.97). For catchers we will add 6.26.

Now Theriot and Iannetta have the same value (0), and there are exactly 11 SS and 11 C with positive values. When this adjustment is done for all of the players, there will be exactly 108 players that have a value of zero or greater.

Notice just how huge of a bump this is for catchers. Before, Mauer, Martin, and McCann looked like 4th and 5th round selections (or $15-20 players). Now they land in the top of the 2nd round–worth upwards up $35.

The change is less dramatic for the other positions. Typically, middle infielders will get a small increase of $1 or $2; corner infielders (and often outfielders) will see a slight drop.

**Flex Positions**

There are a couple of complications when trying to find replacement levels. The first is dealing with “flex” positions like utility/DH, corner-infield, and middle-infield. To handle these, the Price Guide first marks all of the players that are above the replacement level at each of the regular positions. In our sample league, it marks 12 players at each of the primary positions, 96 in all.

Since our sample league uses a DH, the Price Guide finds the top 12 unmarked players and sets the DH replacement level at the 12th. David Ortiz is the top unmarked player, followed by Jim Thome. The remaining 10 are the best of the rest, typically 1B, OF, and 3B. For each player that is counted as a DH, that player’s value is used as the new replacement level for his primary position.

So the previous replacement level for 1B was -0.71, the value of James Loney as the 12th best 1B. But with the DH position, it turns out that 1B like Joey Votto, Conor Jackson, and Adam LaRoche are also worth drafting. The new replacement level for 1B drops to -2.07, which is LaRoche’s value as the 15th best 1B.

**Multi-Position Eligibility**

The second issue is handling players who are eligible at more than one position. Their value should be based on the most valuable position they are eligible at. However, if I move all of the multi-positional players to the most valuable position, it makes that position less valuable (because there is more talent available). Their old positions become more valuable, because we have fewer quality players to choose from.

There’s a possibility of getting stuck moving players back and forth between positions trying to find the most valuable position. Because of this, the Price Guide assumes the positions are ranked as follows (from greatest to least):

C

SS

2B

3B

CF

LF

RF

OF

1B

MI

CI

Util

That works for most leagues, but there may be situations where it is less than optimal. I haven’t discovered a better way to handle it programmatically, and it shouldn’t make much difference most of the time.

For a straight draft, once we have done the positional adjustments, we’re done! The players should all be ranked correctly. For an auction, however, the final step is converting our adjusted values into dollar values. That shouldn’t take long and will be covered in Part III.