Calculating \$\$\$ Values - Fantasy Baseball Cafe 2014

## Calculating \$\$\$ Values

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### Calculating \$\$\$ Values

Hi everyone,

First of all, let me apologize to the people who responded to my last post that I didn't reply to. I had to actualy work for a couple of days, and when I got back on the Cafe, I noticed my post had fallen a couple pages down so I assumed there were no more responses. Anyways, this is sort of where I intended to go with the old post anyways.

I noticed that there was a thread a few days back where someone asked about how people calculate their own dollar values, well here goes:

quick disclaimer: Lots of the ideas I use here are based on an article I read that was written in 1999 which I've unfortunately lost the link to. So if you wrote a auction dollar value article in '99 and it seems like I'm stealing some of your ideas I'm sorry.

My calculations are based on a 12 team league, \$260 cap, with the following positions, C, C, 1B, 2B, 3B, SS, MI, CI, OF, OF, OF, OF, OF, UT, P x 9. You can adjust everything below to fit pretty much any league format.

First you need to define your player universe. This is based on how many players are required for each position. For the league I described above you would take the top:
24 catchers, 18 1B-2B-3B-SS, 60 OF, 12 UT (best left regardless of position, note that a Bench slot would be treated the exact same as a Utility slot), and the top 108 pitchers. The question for this portion would be how do I decide who say the top 18 shortstops are? Well if you have a simple rankings formula like the one I described here: http://www.fantasybaseballcafe.com/foru ... hp?t=91582
then that makes this process very simple. Otherwise you can just eyeball a list of the players eligible at each position and pick the ones that you see fit. I don't think it's a big deal if you get the bottom few guys wrong at each position, since you don't exactly want to get stuck with the 24th best catcher on your team anyways.

You know what? I'm out of smokes and I need some coffee. Back in 5.

To be continued...
Last edited by Elijah on Mon Jan 17, 2005 10:40 am, edited 1 time in total.
Elijah
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Home Cafe: Baseball
Location: Toronto

Ok, the next part of calculating dollar values comes from baseballprospecticus' Value over replacement player. The basic theory behind this in terms of roto leagues is that at any point during the season you could find on the waiver wire a 'replacement player'. This player is basically the average of the players left at his position who are not included in the baseball universe which we described above. What I came up with when I was calculating the replacement player values was the following (remember these are based on my predictions, yours may differ):

Position R HR RBI SB AVG
C 70 8 64 1 .255
1B,3B,OF 70 15 68 4 .268
2B, SS 70 10 68 4 .268

Pitchers W K SV ERA WHIP
9.5 50 0 3.95 1.44

Oh and since you are using different replacement players for different positions, you're automatically integrating position scarcity into your dollar figures!

Since we could in theory find a replacement player on the waiver wire at any point during the season, a players statistics only have value if they are above a replacement players. A players value in any given category is found by subtracting a replacement players stats at his position from his projected stats (or his actual if you're doing a retroactive look). The one position that differs is Avg. which you subtract the replacement AVG from the players then multiply by At Bats. For pitchers ERA and WHIP you do the opposite of AVG, you subtract the players projection from the replacement levels then multiply by IP. I call the numbers that are found by doing this 'Category Values'.
Lets take Vladdy as an example. I have him projected to have the following stats next year:

117, 38, 120, 16, .336, with 592 At bats. Once you subtract the replacement players stats for OF's from above, Vladdy has the following category values:

47, 23, 52, 12, 40 (remember AVG category value = (actual avg - replacement avg) x AB.

Now lets try a pitcher, my projected stats for Randy Johnson:

22, 260, 0, 3.15, 1.12, with 234 IP.

Once we subtract a replement pitchers stats (or for ERA and WHIP we subtract his stats from a replacements), RJ has the following category values:

12.5, 210, 0, 187, 75

Once you do this for all the players in your baseball universe (excel should be useful for this ), you can add up the total category values at each position and this will give you what I call.. uh 'Total Category Value'.... I'm so creative .

Coming up: Putting a dollar value on your Category Values.
Last edited by Elijah on Mon Jan 17, 2005 11:54 am, edited 2 times in total.
Elijah
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Next we have to decide how much money we're spending on Hitters and Pitchers, and then decide wether we're going to put any extra weight on any given stats.

For a 12 team \$260 cap league you have a total of \$3120. I personally like to use roughly 2/3's of my salary cap on hitting, which gives us \$2120 on hitting, \$1000 on pitching.

If we were treating all stats equally, using the numbers above each hitting category would have \$424 in total, and each pitching category would have \$200. Now it seems to me that if a given category is more consistent than another, it makes sense to put extra weight on that category to reflect this. Basically 'riskier stats' deserve less of your roto dollars on draft day. I no longer have the data to back this up but for the hitting categories I found them in order of consistancy to be: HR, RBI, R, SB, AVG. Therefore, the total dollar values I like to assign to each of the hitting categories is:
HR - \$499, RBI - \$474, R - \$424, SB - \$374, AVG - \$349. The pitching categories seem to be roughly equal in terms of consistancy so I leave them with a total value of \$200 each.

Almost done.

Now that we know the 'Total Category Value' for each stat (remember this is the sum of each players 'Category Value', in your baseball universe), you simply divide the Dollars you are spending on a given stat by the Total Category Value to give you a coeffient for any given players Category Value. As an example, all the players in the baseball universe for the league I described above have a total category value of 1522 for HR. So if you're using my dollar values we are spending \$499 on HR's so we divide 499 by 1522, which gives us 0.33 as a coefficient. To put it another way, every HR hit by a player over a replacement players is worth \$0.33 (rounded).

You'll notice that some players have negatives in some category values. This shows that they are actually hurting your team in that category by being below a replacement players. That doesn't mean they're worthless though. If we made up an outfielder with the following stats: 100 R, 0 HR, 70 RBI, 70 SB, .300 AVG with 600 AB's. He would be worth \$30 dollars even though he lost \$4.95 (-15*0.33) by having 15 less HR's than a replacement player at his position.

If you wanted to skip all the steps above and just wanted to use my formula with your projections, you could just plug in the following coefficients:

R 0.20
HR 0.34
RBI 0.22
SB 0.37
AVG 0.23 (you multiply this by (actual - replacement) x ab)

W 1.08
K 0.02
SV 0.24
ERA 0.08 (multiply by (replacement - actual) x IP).
WHIP 0.06 (same as ERA).

So anyways to get a players final dollar value you multiply each of his category values by the coefficient at that stat then add them all up.

I can already picture people complaining that SB's should have a much higher coefficient than HR's. It was alot sketchier with my previous formula, but these ones are based on what I feel are very sound mathematical theories and formulas, but you're welcome to change anything to how you see fit!

Coming up I'll post my Dollar Values for the 2005 season. Remeber these are based on 'my' predictions which may vary greatly from your own. This is *not* a comment on my projections article, I strongly urge you to punch your own projections into the process that I described above to get your own dollar values.

And that's it. Please feel free to critisize, question, or comment on any of the above.

Elijah
Last edited by Elijah on Mon Jan 17, 2005 11:56 am, edited 1 time in total.
Elijah
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Joined: 9 Jan 2005
Home Cafe: Baseball
Location: Toronto

If you are in the Veteran Keeper Friday Funnies slow draft that is going on right now... STOP READING!!!!!!!!!!

Pos, Player/Team, Projected: R, HR, RBI, SB, AVG, \$ Value

1B A. Pujols, StL 132 45 124 5 0.334 \$43
OF V. Guerrero, Ana 117 38 120 16 0.336 \$42
OF C. Beltran, ??? 117 35 103 41 0.274 \$39
3B A. Rodriguez, NYY 115 40 111 25 0.289 \$37
SS M. Tejada, Bal 106 33 141 5 0.305 \$36
1B T. Helton, Col 118 32 110 3 0.348 \$34
2B A. Soriano, Tex 97 33 97 33 0.290 \$34
OF B. Abreu, Phi 107 25 103 30 0.302 \$33
OF M. Ramirez, Bos 108 41 119 2 0.314 \$32
OF G. Sheffield, NYY 116 36 115 8 0.298 \$31
OF B. Bonds, SF 125 40 100 6 0.315 \$31
3B S. Rolen, StL 106 33 120 6 0.305 \$29
OF I. Suzuki, Sea 104 9 60 35 0.353 \$29
3B A. Beltre, Sea 92 38 110 6 0.313 \$28
OF L. Berkman, Hou 105 30 106 8 0.309 \$27
OF J. Edmonds, StL 99 40 105 7 0.298 \$26
OF J. Damon, Bos 119 18 87 22 0.298 \$26
3B M. Mora, Bal 106 25 94 11 0.327 \$26
1B D. Ortiz, Bos 88 38 127 0 0.297 \$26
OF C. Crawford, TB 95 9 65 55 0.291 \$25
SS M. Young, Tex 110 20 91 12 0.308 \$25
OF C. Lee, Mil 101 31 100 11 0.299 \$25
1B J. Thome, Phi 100 44 110 0 0.275 \$24
SS D. Jeter, NYY 108 20 73 22 0.297 \$23
OF H. Matsui, NYY 105 29 108 3 0.296 \$23
1B M. Teixeira, Tex 95 38 107 4 0.285 \$23
OF J. Drew, LA 111 29 87 10 0.299 \$23
OF J. Pierre, Fla 99 3 47 49 0.320 \$22
OF M. Cabrera, Fla 94 31 109 4 0.290 \$22
C V. Martinez, Cle 88 25 108 0 0.283 \$22
3B H. Blalock, Tex 104 32 107 2 0.279 \$21
C I. Rodriguez, Det 84 19 84 7 0.326 \$21
SS J. Rollins, Phi 110 13 70 28 0.281 \$21
OF A. Dunn, Cin 100 42 94 8 0.257 \$21
1B D. Lee, ChC 91 31 96 14 0.276 \$21
3B A. Ramirez, ChC 91 33 101 1 0.303 \$20
3B A. Huff, TB 90 29 101 4 0.300 \$20
2B J. Kent, LA 93 24 100 7 0.292 \$20
OF M. Alou, SF 95 34 95 3 0.289 \$20
SS C. Guillen, Det 92 20 90 10 0.307 \$19
C J. Lopez, Bal 80 25 87 0 0.313 \$19
1B C. Delgado, ??? 84 34 115 0 0.285 \$19
OF S. Podsednik, CHW 88 12 42 66 0.254 \$19
OF B. Giles, SD 96 24 94 9 0.287 \$18
OF S. Finley, Ana 90 33 90 11 0.274 \$18
SS R. Furcal, Atl 107 14 58 28 0.281 \$18
OF C. Patterson, ChC 87 23 72 30 0.270 \$17
2B M. Loretta, SD 98 15 72 5 0.330 \$17
OF L. Walker, StL 89 27 83 10 0.300 \$17
1B S. Casey, Cin 92 21 91 2 0.314 \$17
DH T. Hafner, Tex 90 26 97 3 0.296 \$17
1B P. Konerko, CWS 78 36 107 1 0.273 \$16
2B B. Boone, Sea 81 26 91 11 0.275 \$16
OF J. Guillen, Was 83 27 98 5 0.292 \$16
1B J. Bagwell, Hou 100 25 92 7 0.270 \$16
SS N. Garciaparra, ChC 87 17 85 8 0.308 \$16
OF V. Wells, Tor 88 25 90 8 0.285 \$15
OF A. Rowand, CWS 91 23 67 16 0.306 \$15
SS E. Renteria, Bos 85 11 78 20 0.296 \$15
OF R. Winn, Sea 87 14 80 22 0.288 \$15
3B D. Wright, NYM 85 25 85 10 0.293 \$15
OF A. Jones, Atl 88 31 95 6 0.264 \$15
OF L. Ford, Min 89 15 72 20 0.299 \$15
2B M. Giles, Atl 82 18 62 19 0.313 \$15
3B M. Lowell, Fla 85 28 89 5 0.289 \$15
OF T. Hunter, Min 81 24 86 19 0.269 \$15
OF M. Lawton, Pit 100 19 68 20 0.270 \$14
OF G. Anderson, Ana 85 25 86 3 0.304 \$14
1B S. Green, LA 92 28 88 5 0.270 \$14
3B E. Chavez, Oak 88 29 84 7 0.277 \$14
1B B. Wilkerson, Mon 105 29 68 13 0.258 \$14
1B J. Morneau, Min 75 33 102 0 0.271 \$13
DH E. Durazo, Ari 83 23 87 2 0.306 \$13
C J. Mauer, Min 72 24 68 4 0.308 \$13
OF J. Burnitz, Col 86 30 85 5 0.271 \$13
OF M. Ordonez, ??? 80 25 90 2 0.300 \$13
1B P. Nevin, SD 76 25 101 0 0.289 \$13
C J. Posada, NYY 74 22 86 1 0.273 \$12
3B C. Jones, Atl 80 29 98 3 0.265 \$12
3B C. Blake, Cle 91 26 85 5 0.269 \$12
SS O. Cabrera, Ana 77 11 75 25 0.269 \$11
OF W. Pena, Cin 70 35 90 7 0.258 \$11
OF T. Nixon, Bos 80 25 80 1 0.314 \$11
C J. Varitek, Bos 66 19 74 8 0.290 \$11
2B L. Castillo, Fla 92 3 55 25 0.296 \$11
OF R. Baldelli, TB 81 15 75 19 0.282 \$11
OF G. Jenkins, Mil 85 27 90 2 0.267 \$11
OF E. Byrnes, Oak 87 19 69 16 0.280 \$11
OF C. Wilson, Pit 90 28 85 3 0.264 \$11
OF J. Bay, Pit 80 26 85 4 0.282 \$11
2B C. Utley, Phi 72 26 85 8 0.266 \$11
OF S. Sosa, ChC 78 37 86 0 0.261 \$10
2B B. Roberts, Bal 100 4 51 28 0.273 \$10
OF M. Cameron, NYM 76 28 76 22 0.236 \$10
C J. Kendall, Oak 83 4 52 10 0.317 \$10
OF M. Grissom, SF 78 22 87 5 0.283 \$10
2B M. Bellhorn, Bos 92 18 80 6 0.263 \$10
OF C. Biggio, Hou 100 22 62 8 0.276 \$10
OF L. Gonzalez, Ari 87 22 85 4 0.270 \$10
OF K. Griffey Jr., Cin 74 30 90 2 0.261 \$9
3B V. Castilla, Was 85 25 85 1 0.269 \$9
2B R. Durham, SF 91 15 60 11 0.283 \$9
OF R. Sanders, StL 67 24 72 20 0.263 \$9
OF J. Jones, Min 72 23 79 12 0.266 \$8
SS J. Lugo, TB 79 9 70 19 0.274 \$8
C M. Piazza, NYM 70 21 75 0 0.271 \$8
2B J. Uribe, CWS 79 20 68 9 0.274 \$8
C J. Estrada, Atl 56 9 85 0 0.314 \$8
3B G. Atkins, Col 75 15 85 0 0.315 \$8
2B J. Reyes, NYM 74 5 32 43 0.275 \$7
C P. Lo Duca, Fla 68 12 74 3 0.283 \$7
C J. Buck, KC 72 24 70 2 0.255 \$7
3B D. McPherson, Ana 75 25 75 11 0.255 \$7
1B L. Overbay, Mil 77 15 82 2 0.297 \$7
1B S. Hillenbrand, Ari 69 16 83 2 0.303 \$7
1B M. Sweeney, KC 70 21 80 4 0.293 \$7
2B J. Vidro, Mon 75 15 75 3 0.299 \$7
OF P. Burrell, Phi 85 25 83 2 0.251 \$7
SS O. Vizquel, SF 82 7 56 18 0.283 \$6
C A. Pierzynski, CHW 60 15 79 1 0.281 \$6
SS B. Crosby, Oak 70 25 75 7 0.255 \$6
OF K. Millar, Bos 74 19 76 1 0.294 \$6
OF M. Bradley, LA 72 17 66 15 0.275 \$6
1B R. Palmeiro, Bal 75 24 85 2 0.260 \$6
OF M. Kotsay, Oak 76 14 59 8 0.305 \$5
OF R. Gload, CWS 56 14 88 0 0.321 \$5
SS R. Adams, Tor 65 15 65 7 0.306 \$5
C M. Lieberthal, Phi 63 17 68 1 0.281 \$5
C J. Closser, Col 45 15 70 2 0.315 \$5
OF B. Williams, NYY 85 21 72 2 0.269 \$5
SS J. Wilson, Pit 78 10 59 7 0.296 \$5
OF R. Ibanez, Sea 72 17 70 3 0.301 \$5
OF R. Hidalgo, Tex 71 25 81 5 0.250 \$5
SS C. Barmes, Col 91 13 65 0 0.281 \$4
SS J. Valentin, LA 74 29 71 8 0.222 \$4
OF J. Cruz Jr., TB 77 21 76 10 0.244 \$4
3B R. Branyan, Mil 70 32 79 3 0.234 \$4
2B T. Walker, ChC 78 17 67 1 0.279 \$4
OF A. Kearns, Cin 75 21 75 6 0.255 \$4
2B D. Jimenez, Cin 74 12 63 12 0.269 \$4
SS C. Guzman, Was 83 7 60 12 0.273 \$4
OF J. Reed, Sea 88 0 45 20 0.300 \$3
OF K. Mench, Tex 69 25 71 0 0.277 \$3
3B C. Koskie, Tor 70 22 71 7 0.260 \$3
OF J. Conine, Fla 60 15 83 5 0.280 \$3
OF S. Stewart, Min 67 14 60 8 0.305 \$3
SS A. Berroa, KC 73 11 55 16 0.264 \$2
SS K. Greene, SD 67 15 65 7 0.273 \$2
2B O. Infante, Det 69 16 55 13 0.264 \$2
OF C. Floyd, NYM 60 20 68 10 0.268 \$2
OF K. Lofton, Phi 91 7 36 20 0.278 \$2
OF P. Wilson, Col 63 18 78 8 0.254 \$2
C M. Barrett, ChC 56 16 63 1 0.272 \$1
C R. Hernandez, SD 50 18 64 1 0.272 \$0
1B J. Giambi, NYY 70 26 81 1 0.227 \$0
OF C. Everett, CWS 64 17 73 3 0.269 \$0
OF J. Encarnacion, Fla 67 17 70 9 0.250 \$0
SS A. Gonzalez, Fla 63 21 77 3 0.235 -\$1
OF M. Stairs, KC 54 21 70 1 0.269 -\$2
C B. Santiago, Pit 42 14 59 3 0.275 -\$2
C M. Olivo, Sea 55 15 47 8 0.235 -\$3
OF J. Payton, Bos 64 12 61 3 0.271 -\$4
C K. Hill, Ari 30 10 60 10 0.250 -\$5
C J. LaRue, Cin 47 14 54 1 0.248 -\$6
C R. Barajas, Tex 47 13 58 0 0.240 -\$6
C B. Molina, Ana 36 10 56 0 0.274 -\$7
C T. Hall, TB 38 9 56 0 0.255 -\$8
C B. Schneider, Mon 39 11 49 0 0.255 -\$9
Elijah
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Player/Team, Projected: W, K, SV, ERA, WHIP, \$ Value

J. Santana, Min 19 257 0 2.83 1.03 \$41
R. Johnson, NYY 22 260 0 3.15 1.12 \$38
J. Schmidt, SF 17 228 0 2.96 1.05 \$34
P. Martinez, NYM 14 235 0 3.00 1.03 \$30
C. Schilling, Bos 15 219 0 3.17 1.04 \$28
R. Oswalt, Hou 18 192 0 3.26 1.21 \$28
T. Hudson, Atl 15 138 0 3.05 1.20 \$28
R. Halladay, Tor 17 175 0 3.30 1.22 \$27
E. Gagne, LA 5 122 50 1.83 0.83 \$26
C. Zambrano, ChC 14 181 0 3.03 1.29 \$25
M. Prior, ChC 15 229 0 3.15 1.23 \$25
J. Peavy, SD 16 190 0 3.25 1.27 \$23
M. Rivera, NYY 4 65 49 1.87 1.06 \$21
B. Sheets, Mil 14 213 0 3.49 1.14 \$21
O. Perez, Pit 12 217 0 3.30 1.10 \$20
B. Lidge, Hou 3 137 45 2.44 1.01 \$19
J. Nathan, Min 5 87 44 2.10 1.01 \$19
K. Wood, ChC 15 233 0 3.54 1.24 \$19
A. Burnett, Fla 15 176 0 3.45 1.17 \$19
B. Wagner, Phi 3 79 41 2.16 0.85 \$19
K. Foulke, Bos 6 79 32 2.26 0.93 \$18
F. Rodriguez, Ana 2 114 45 2.23 1.00 \$18
M. Mulder, Stl 17 139 0 3.65 1.21 \$18
J. Smoltz, Atl 2 95 45 2.55 1.10 \$16
L. Hernandez, Mon 13 175 0 3.59 1.26 \$16
G. Maddux, ChC 16 137 0 3.79 1.19 \$15
J. Beckett, Fla 14 190 0 3.66 1.26 \$15
A. Benitez, Fla 3 69 36 2.03 1.05 \$14
J. Marquis, StL 15 136 0 3.60 1.35 \$14
J. Isringhausen, StL 4 71 45 2.82 1.03 \$14
O. Perez, LA 12 137 0 3.61 1.16 \$13
C. Pavano, NYY 17 137 0 3.85 1.30 \$13
J. Vazquez, Ari 13 190 0 3.75 1.20 \$13
F. Cordero, Tex 4 83 38 2.44 1.30 \$13
A. Pettitte, Hou 16 163 0 3.84 1.28 \$13
G. Mota, Fla 3 84 35 2.79 1.10 \$13
M. Mussina, NYY 16 178 0 3.95 1.20 \$13
W. Williams, SD 13 142 0 3.70 1.20 \$13
K. Brown, NYY 12 153 0 3.61 1.25 \$13
B. Zito, Oak 14 161 0 3.77 1.28 \$13
O. Dotel, Oak 3 113 36 2.96 1.06 \$12
B. Webb, Ari 10 167 0 3.50 1.30 \$12
M. Buehrle, CWS 16 145 0 3.92 1.28 \$12
A. Leiter, Fla 12 134 0 3.53 1.39 \$11
T. Hoffman, SD 3 56 41 2.40 0.97 \$11
C. Carpenter, StL 12 165 0 3.76 1.21 \$11
N. Lowry, SF 14 162 0 3.83 1.29 \$11
J. Westbrook, Cle 13 106 0 3.68 1.32 \$11
M. Clement, Bos 14 180 0 3.90 1.25 \$11
D. Bush, Tor 11 138 0 3.70 1.23 \$10
V. Padilla, Phi 13 127 0 3.75 1.28 \$10
D. Wells, Bos 14 95 0 3.88 1.23 \$10
B. Madritsch, Sea 11 135 0 3.67 1.30 \$10
B. Penny, LA 12 139 0 3.77 1.30 \$9
B. Arroyo, Bos 13 163 0 3.95 1.22 \$9
Z. Greinke, KC 12 130 0 3.85 1.17 \$9
C. Cordero, Mon 3 83 33 2.96 1.35 \$9
D. Kolb, Atl 2 21 43 2.99 1.14 \$8
R. Harden, Oak 12 167 0 3.85 1.30 \$8
B. Looper, NYM 3 58 32 3.10 1.27 \$8
S. Trachsel, NYM 13 113 0 3.84 1.38 \$8
T. Glavine, NYM 12 103 0 3.76 1.35 \$8
K. Escobar, Ana 14 180 0 4.04 1.35 \$7
B. Radke, Min 13 127 0 4.00 1.21 \$7
D. Willis, Fla 11 140 0 3.82 1.35 \$7
W. Miller, Hou 8 152 0 3.62 1.33 \$7
D. Lowe, LA 14 110 0 4.00 1.35 \$6
T. Percival, Det 2 44 34 2.92 1.20 \$6
C. Sabathia, Cle 12 141 0 3.99 1.32 \$5
F. Garcia, CWS 13 170 0 4.14 1.27 \$5
R. Ortiz, Ari 12 144 0 3.94 1.41 \$5
B. Colon, Ana 15 162 0 4.24 1.29 \$5
B. Lawrence, SD 13 124 0 4.07 1.33 \$4
T. Lilly, Tor 12 159 0 4.09 1.29 \$4
R. Lopez, Bal 13 139 0 4.15 1.34 \$4
R. Wolf, Phi 11 154 0 4.10 1.28 \$4
J. Lieber, Phi 14 129 0 4.23 1.31 \$3
J. Pineiro, Sea 12 157 0 4.17 1.30 \$3
D. Baez, TB 4 70 30 3.92 1.32 \$3
K. Millwood, Phi 14 171 0 4.28 1.33 \$3
J. Moyer, Sea 13 130 0 4.21 1.28 \$3
J. Bonderman, Det 11 165 0 4.15 1.30 \$3
M. Morris, StL 12 134 0 4.20 1.26 \$3
J. Mesa, Pit 5 44 37 4.16 1.51 \$2
J. Washburn, Ana 13 117 0 4.31 1.28 \$2
J. Thomson, Atl 13 130 0 4.28 1.32 \$1
K. Wells, Pit 8 144 0 3.94 1.40 \$1
J. Suppan, StL 12 110 0 4.38 1.36 -\$2
K. Rogers, Tex 16 120 0 4.55 1.44 -\$2
J. Lackey, Ana 13 143 0 4.50 1.39 -\$3
A. Eaton, SD 10 151 0 4.44 1.30 -\$3
D. Graves, Cin 3 50 36 4.57 1.38 -\$3
M. Batista, Tor 10 118 3 4.31 1.43 -\$3
T. Wakefield, Bos 8 137 1 4.30 1.31 -\$3
R. Drese, Tex 13 99 0 4.49 1.44 -\$3
V. Zambrano, NYM 14 145 0 4.54 1.54 -\$4
M. Redman, Pit 8 120 0 4.26 1.37 -\$4
E. Loaiza, CWS/NYY 15 151 0 4.68 1.40 -\$4
J. Weaver, LA 11 130 0 4.46 1.37 -\$4
E. Milton, Phi 14 154 0 4.76 1.32 -\$5
R. Ortiz, Ana 10 99 0 4.57 1.38 -\$6
B. Tomko, SF 12 113 0 4.54 1.40 -\$6
S. Ponson, Bal 12 122 0 4.60 1.42 -\$6
J. Garland, CWS 12 111 0 4.73 1.38 -\$8
N. Robertson, Det 12 155 0 4.91 1.41 -\$10
C. Lidle, Cin/Phi 11 119 0 5.01 1.35 -\$13
R. Dickey, Tex 12 114 2 5.63 1.63 -\$26
Elijah
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EXCELLENT series of posts Elijah A thorough explaination done as well as any paysite expert could. Not only do we get the 'how' to...we get the 'why' you do what you do in each step.
dannahann
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how did I miss this ..

Great post ...
This become an FAQ or something ...
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wrveres
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Nice work, thanks

I can't wait til I'm done my projections and can FINALLY get some dollar values completed.

And if anybody wants some additional info on this type of thing, here are a couple links:

VBD

How to Value Players for Rotisserie Baseball

One is for football but I think it's easy enough to transfer over to baseball.

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LBJackal
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Thanks guys!

When this post quickly fell off the first page with no responses, I just kinda assumed it sucked.

Re-reading what I wrote, I didn't really mean for it to sound like I was taking credit for inventing much of the process... but I do think I may have explained it in an easier to understand way than any other I've found previously. Hope it was helpful!
Elijah
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Wow. Great post!
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 • Toronto at Baltimore(7:05 pm)
 • Boston at Pittsburgh(7:05 pm)
 • Washington at Atlanta(7:10 pm)
 • Miami at NY Mets(7:10 pm)
 • NY Yankees at Tampa Bay(7:10 pm)
 • Cincinnati at Chi Cubs(8:05 pm)
 • Cleveland at Houston(8:10 pm)
 • Chi White Sox at Kansas City(8:10 pm)
 • Detroit at Minnesota(8:10 pm)
 • Milwaukee at St. Louis(8:15 pm)
 • Seattle at LA Angels(10:05 pm)
 • Texas at Oakland(10:05 pm)
 • Philadelphia at San Diego(10:10 pm)