If you just got done reading how to determine replacement level players you have got to be asking yourself what is wrong with this ranking? Well, the problem can be pinpointed all the way back to the original zscore calculations. When calculating the zscores for the statistical categories we used every player that had at least one plate appearance. This means that the average HR per player is getting reduced by the late season call ups and the early season injuries. These incomplete data sets will have a negative impact on the accuracy of their distribution.
When looking at the 2012 hitters, the average number of games played for all hitters was 79.2 games. This means that we are evaluating top level talent off of streaky performances and pretty much nonsense averages dragged down by players ranked 1000+. To get more reflective data from the player pool that will actually be used, the Fantasy Baseball Calculator spreadsheet does something fairly clever.
Because all of the players have aleady been identified that will theoretically serve a purpose in the league, we can compare how much their stats will deviate from one another by stricly looking at their stats alone!
For instance, in the yahoo default settings, for all the players that have been identified to have given value the average number of home runs for each of those players is 20.43. This is a significant change over the league wide 2012 average of 7.76. The standard deviation of this data comes in at a slightly more 9.90.
Remember our Players A, B, and C?
Well just for fun we will bring them back, only this time calculate their HR zscores with these new values in mind:
Player  HR  zscore: mean = 20.43 ; SD = 9.90 
Player A

35

1.47

Player B

20

0.04

Player C

12

0.85

These look a little differently don't they? Whereas Player A was 1.631 higher than Player B with every player taken in account, he is only 1.51 higher now. For comparison, I will calculate the rest of the 5x5 hitter calcs with the new means and standard deviations:
Player  R  zscore: mean = 77.83 ; SD = 16.18 
Player A

100

1.37

Player B

105

1.68

Player C

130

3.22

Player  RBI  zscore: mean = 75.93 ; SD = 21.23 
Player A

100

1.13

Player B

89

0.62

Player C

75

0.04

Player  SB  zscore: mean = 13.68 ; SD = 12.16 
Player A

10

0.30

Player B

5

0.71

Player C

65

4.22

Player  xBA ; sum hit = 18621 sum ab = 66093  zscore: mean = 5.89* ; SD = 9.94 
Player A

1.78

0.77

Player B

4.47

1.04

Player C

15.78

2.18

Player  z HR  z R  z RBI  z SB  z xBA  z total 
Player A

1.47

1.37

1.13

0.30

0.77

4.44

Player B

0.04

1.68

0.62

0.71

1.04

2.59

Player C

0.85

3.22

0.04

4.22

2.18

8.73
